This disclosure relates generally to optical scanning and, more particularly, to a light detection and ranging (LiDAR) system having fiber-based transmitter channels and fiber-based receiver channels.
Light detection and ranging (LiDAR) systems use light pulses to create an image or point cloud of the external environment. Some typical LiDAR systems include a light source, a light transmitter, a light steering system, and a light receiver and detector. The light source generates a light beam that is directed by the light steering system in particular directions when being transmitted from the LiDAR system. When a transmitted light beam is scattered by an object, a portion of the scattered light returns to the LiDAR system as a return light pulse. The light receiver receives the return light pulse and the detector detects the return light pulse. Using the difference between the time that the return light pulse is detected and the time that a corresponding light pulse in the light beam is transmitted, the LiDAR system can determine the distance to the object using the speed of light. The light steering system can direct light beams along different paths to allow the LiDAR system to scan the surrounding environment and produce images or point clouds. LiDAR systems can also use techniques other than time-of-flight and scanning to measure the surrounding environment.
Embodiments provided in this disclosure use a collimation lens and multiple transmitter channels having multiple transmitter optical fibers. Adjacent transmitter optical fibers are disposed at a preconfigured pitch. By configuring the pitch between the transmitter optical fibers in the array and/or the focal length of the collimation lens, a desired angular channel spacing of the transmitter channels can be obtained. Using multiple transmitter channels with a properly configured angular channel spacing, the scanning performance of the LiDAR system can be improved. Further, the dimension and complexity of the transmitter can be reduced such that the LiDAR system is more compact.
In one embodiment, a LiDAR system comprising a plurality of transmitter channels is provided. The plurality of transmitter channels comprise transmitter optical fibers disposed in an optical fiber housing at a pre-determined pitch from one another. A collimation lens is positioned to be optically coupled to the plurality of transmitter channels to receive a plurality of transmission light beams transmitted from the transmitter optical fibers. The collimation lens is configured to collimate the plurality of transmission light beams. A combination of the plurality of transmitter channels and the collimation lens is configured to transmit a plurality of collimated transmission light beams at an angular separation from each other to provide an angular channel spacing that is related to the pre-determined pitch.
Embodiments provided in this disclosure also use multiple receiver channels having multiple receiver optical fibers. The multiple receiver optical fibers can share a collection lens, thereby reducing the dimensions of the transceiver of a LiDAR system. Furthermore, because optical fibers are physically flexible, detector assemblies for detecting return light can be flexibly distributed such that they are positioned sufficiently apart from one another. As a result, both the optical crosstalk and electrical crosstalk between adjacent detector assemblies can be reduced or minimized. This in turn improves the detection accuracy and the overall performance of the LiDAR system.
In one embodiment, a LiDAR system comprising a plurality of transmitter channels and a plurality of receiver channels is provided. The plurality of transmitter channels are configured to transmit a plurality of transmission light beams to a field-of-view at a plurality of different transmission angles. The LiDAR system further comprises a collection lens disposed to receive and redirect return light obtained based on the plurality of transmission light beams illuminating one or more objects within the field-of-view. The LiDAR system further comprises a plurality of receiver channels optically coupled to the collection lens. Each of the receiver channels is optically aligned based on a transmission angle of a corresponding transmission light beam. The LiDAR system further comprises a plurality of detector assemblies optically coupled to the plurality of receiver channels. Each of the receiver channels directs redirected return light to a detector assembly of the plurality of detector assemblies.
The present application can be best understood by reference to the figures described below taken in conjunction with the accompanying drawing figures, in which like parts may be referred to by like numerals.
To provide a more thorough understanding of the present invention, the following description sets forth numerous specific details, such as specific configurations, parameters, examples, and the like. It should be recognized, however, that such description is not intended as a limitation on the scope of the present invention but is intended to provide a better description of the exemplary embodiments.
Throughout the specification and claims, the following terms take the meanings explicitly associated herein, unless the context clearly dictates otherwise:
The phrase “in one embodiment” as used herein does not necessarily refer to the same embodiment, though it may. Thus, as described below, various embodiments of the disclosure may be readily combined, without departing from the scope or spirit of the invention.
As used herein, the term “or” is an inclusive “or” operator and is equivalent to the term “and/or,” unless the context clearly dictates otherwise.
The term “based on” is not exclusive and allows for being based on additional factors not described unless the context clearly dictates otherwise.
As used herein, and unless the context dictates otherwise, the term “coupled to” is intended to include both direct coupling (in which two elements that are coupled to each other contact each other) and indirect coupling (in which at least one additional element is located between the two elements). Therefore, the terms “coupled to” and “coupled with” are used synonymously. Within the context of a networked environment where two or more components or devices are able to exchange data, the terms “coupled to” and “coupled with” are also used to mean “communicatively coupled with”, possibly via one or more intermediary devices.
Although the following description uses terms “first,” “second,” etc. to describe various elements, these elements should not be limited by the terms. These terms are only used to distinguish one element from another. For example, a first sensor could be termed a second sensor and, similarly, a second sensor could be termed a first sensor, without departing from the scope of the various described examples. The first sensor and the second sensor can both be sensors and, in some cases, can be separate and different sensors.
In addition, throughout the specification, the meaning of “a”, “an”, and “the” includes plural references, and the meaning of “in” includes “in” and “on”.
Although some of the various embodiments presented herein constitute a single combination of inventive elements, it should be appreciated that the inventive subject matter is considered to include all possible combinations of the disclosed elements. As such, if one embodiment comprises elements A, B, and C, and another embodiment comprises elements B and D, then the inventive subject matter is also considered to include other remaining combinations of A, B, C, or D, even if not explicitly discussed herein. Further, the transitional term “comprising” means to have as parts or members, or to be those parts or members. As used herein, the transitional term “comprising” is inclusive or open-ended and does not exclude additional, unrecited elements or method steps.
Throughout the following disclosure, numerous references may be made regarding servers, services, interfaces, engines, modules, clients, peers, portals, platforms, or other systems formed from computing devices. It should be appreciated that the use of such terms is deemed to represent one or more computing devices having at least one processor (e.g., ASIC, FPGA, PLD, DSP, x86, ARM, RISC-V, ColdFire, GPU, multi-core processors, etc.) configured to execute software instructions stored on a computer readable tangible, non-transitory medium (e.g., hard drive, solid state drive, RAM, flash, ROM, etc.). For example, a server can include one or more computers operating as a web server, database server, or other type of computer server in a manner to fulfill described roles, responsibilities, or functions. One should further appreciate the disclosed computer-based algorithms, processes, methods, or other types of instruction sets can be embodied as a computer program product comprising a non-transitory, tangible computer readable medium storing the instructions that cause a processor to execute the disclosed steps. The various servers, systems, databases, or interfaces can exchange data using standardized protocols or algorithms, possibly based on HTTP, HTTPS, AES, public-private key exchanges, web service APIs, known financial transaction protocols, or other electronic information exchanging methods. Data exchanges can be conducted over a packet-switched network, a circuit-switched network, the Internet, LAN, WAN, VPN, or other type of network.
As used in the description herein and throughout the claims that follow, when a system, engine, server, device, module, or other computing element is described as being configured to perform or execute functions on data in a memory, the meaning of “configured to” or “programmed to” is defined as one or more processors or cores of the computing element being programmed by a set of software instructions stored in the memory of the computing element to execute the set of functions on target data or data objects stored in the memory.
It should be noted that any language directed to a computer should be read to include any suitable combination of computing devices or network platforms, including servers, interfaces, systems, databases, agents, peers, engines, controllers, modules, or other types of computing devices operating individually or collectively. One should appreciate the computing devices comprise a processor configured to execute software instructions stored on a tangible, non-transitory computer readable storage medium (e.g., hard drive, FPGA, PLA, solid state drive, RAM, flash, ROM, etc.). The software instructions configure or program the computing device to provide the roles, responsibilities, or other functionality as discussed below with respect to the disclosed apparatus. Further, the disclosed technologies can be embodied as a computer program product that includes a non-transitory computer readable medium storing the software instructions that causes a processor to execute the disclosed steps associated with implementations of computer-based algorithms, processes, methods, or other instructions. In some embodiments, the various servers, systems, databases, or interfaces exchange data using standardized protocols or algorithms, possibly based on HTTP, HTTPS, AES, public-private key exchanges, web service APIs, known financial transaction protocols, or other electronic information exchanging methods. Data exchanges among devices can be conducted over a packet-switched network, the Internet, LAN, WAN, VPN, or other type of packet switched network; a circuit switched network; cell switched network; or other type of network.
A LiDAR system may have one or more transmitter channels for transmitting laser beams. In some embodiments, using multiple transmitter channels, the LiDAR system transmits multiple light beams to scan the external environment. The LiDAR system's scanning resolution and speed can be improved by using multiple light beams compared to using just a single light beam. Furthermore, multiple transmitter channels facilitate reducing the requirement for moving a scanning optical device, such as a polygon mirror. For example, by using multiple transmitter channels, the rotational speed of the polygon mirror can be reduced while still allowing the LiDAR system to scan the same or similar areas of a field-of-view. On the other hand, multiple transmitter channels (e.g., four or more channels) may make it difficult to keep the LiDAR system compact. For example, if each transmitter channel has its own collimation lens and other optical and/or electrical components, the dimension of the transmitter may increase significantly. The complexity of the transmitter may increase too, making it less robust and reliable. Oftentimes, a compact LiDAR system may be needed to fit into small spaces in a vehicle (e.g., corner spaces, rearview mirrors, or the like). A reliable transmitter in a LiDAR system is also desired because the LiDAR system frequently must operate under large variations of environment conditions including temperature, humidity, vibration, etc. Therefore, there is a need for a compact and reliable LiDAR system with multiple transmitter channels.
Embodiments disclosed herein use multiple transmitter channels comprising an array of transmitter optical fibers. At least the end portions of the transmitter optical fibers are positioned to have a precision pitch between adjacent transmitter fibers. One or more collimation lenses are used to generate collimated transmission light beams for all transmitter channels. By configuring the pitch between the transmitter optical fibers and/or the focal length of the collimation lens, a desired angular channel spacing can be obtained. The angular channel spacing is a parameter that measures or represents the degree of angular separation between the light beams transmitted by the multiple transmitter channels to scan an FOV. When the adjacent transmitter channels are configured to have the proper angular channel spacing the multiple transmission light beams are positioned sufficiently apart at a desired angular separation to scan different areas within an FOV, providing a good coverage of the scanned areas and improving the scan resolution and speed. Therefore, the scanning performance of the LiDAR system can be improved by using multiple transmitter channels configured to have a proper angular channel spacing.
Furthermore, one or more embodiments in this disclosure also use a single collimation lens to form collimated transmission light beams for all transmitter channels. As a result, many transmitter channels can be assembled into a space corresponding to a single collimation lens, thereby reducing the dimensions of the transceiver and making the LiDAR system more compact. Moreover, by sharing a single collimation lens among the multiple transmitter channels, the complexity of the alignment of the transmitter assembly is reduced. It is understood, however, that multiple collimation lenses may be used in other embodiments.
A LiDAR system may also have one or more receiver channels corresponding to the one or more transmitter channels. For example, a particular transmitter channel transmits a light beam to an FOV. The light beam reaches an object. A portion of the light beam is scattered and/or reflected, thereby forming return light. A receiver channel corresponding to the particular transmitter channel receives the return light. Often, the quantity of the receiver channels is the same as that of the transmitter channels. Thus, for example, if a LiDAR system has four transmitter channels, there are correspondingly four receiver channels. If the multiple receiver channels share some optical components (e.g., a collection lens), certain components of the different receiver channels (e.g., photodetectors for different receiver channels) need to be placed close to one another. Moreover, in conventional technologies, because certain optical components are shared by multiple receiver channels, photodetector circuitry may need to be fixed at certain locations. This configuration causes undesired optical scattering and/or electrical crosstalk. Furthermore, photodetectors of the receiver channels may have placement errors, thereby further worsening the receiver performance. On the other hand, if each receiver channel has its own receiver optical components (e.g., the collection lens), the dimension of the receiver may increase significantly, making it difficult to fit into small spaces in a vehicle. The complexity of the receiver may increase too, making it less robust and reliable. As described above, a compact LiDAR system may be needed to fit into small spaces in a vehicle. And a reliable receiver in a LiDAR system is also desired because the LiDAR system frequently has to operate under large variations of environment conditions including temperature, humidity, vibration, etc. Therefore, there is a need for a compact and reliable LiDAR system with multiple receiver channels.
Embodiments disclosed herein use multiple receiver channels comprising multiple receiver optical fibers. The multiple receiver optical fibers use one or more collection lenses. In one embodiment, the receiver optical fiber can share a single collection lens, thereby reducing the dimensions of the transceiver of a LiDAR system. In turn, this makes the LiDAR system more compact. Furthermore, because optical fibers are physically flexible, detector assemblies for detecting return light can be flexibly distributed. Detector assemblies can be placed at any desired locations while still being coupled to their respective receiver optical fibers to receive return light. For example, adjacent detector assemblies can be placed at different locations sufficiently further away from each other. As a result, both the optical crosstalk and electrical crosstalk between adjacent detector assemblies can be reduced. An optical fiber typically has a limited acceptance angle defined by its core and cladding materials, thereby providing spatial filtering to reduce the amount of stray light and optical crosstalk. Moreover, adjacent receiver optical fibers can be positioned at a precise pitch from each other. The precision positioning of the receiver optical fibers further reduces alignment error such that return light generated from different transmission light beams are accurately aligned with the corresponding receiver optical fiber. The return light can thus be received properly at the corresponding receiver optical fiber with reduced or minimum loss or crosstalk. Embodiments of present invention are described below in details.
In typical configurations, motor vehicle 100 comprises one or more LiDAR systems 110 and 120A-120F. Each of LiDAR systems 110 and 120A-120F can be a scanning-based LiDAR system and/or a non-scanning LiDAR system (e.g., a flash LiDAR). A scanning-based LiDAR system scans one or more light beams in one or more directions (e.g., horizontal and vertical directions) to detect objects in a field-of-view (FOV). A non-scanning based LiDAR system transmits laser light to illuminate an FOV without scanning. For example, a flash LiDAR is a type of non-scanning based LiDAR system. A flash LiDAR can transmit laser light to simultaneously illuminate an FOV using a single light pulse or light shot.
A LiDAR system is often an essential sensor of a vehicle that is at least partially automated. In one embodiment, as shown in
LiDAR system(s) 210 can include one or more of short-range LiDAR sensors, medium-range LiDAR sensors, and long-range LiDAR sensors. A short-range LiDAR sensor measures objects located up to about 20-40 meters from the LiDAR sensor. Short-range LiDAR sensors can be used for, e.g., monitoring nearby moving objects (e.g., pedestrians crossing street in a school zone), parking assistance applications, or the like. A medium-range LiDAR sensor measures objects located up to about 100-150 meters from the LiDAR sensor. Medium-range LiDAR sensors can be used for, e.g., monitoring road intersections, assistance for merging onto or leaving a freeway, or the like. A long-range LiDAR sensor measures objects located up to about 150-300 meters. Long-range LiDAR sensors are typically used when a vehicle is travelling at high speed (e.g., on a freeway), such that the vehicle's control systems may only have a few seconds (e.g., 6-8 seconds) to respond to any situations detected by the LiDAR sensor. As shown in
With reference still to
Other vehicle onboard sensors(s) 230 can also include radar sensor(s) 234. Radar sensor(s) 234 use radio waves to determine the range, angle, and velocity of objects. Radar sensor(s) 234 produce electromagnetic waves in the radio or microwave spectrum. The electromagnetic waves reflect off an object and some of the reflected waves return to the radar sensor, thereby providing information about the object's position and velocity. Radar sensor(s) 234 can include one or more of short-range radar(s), medium-range radar(s), and long-range radar(s). A short-range radar measures objects located at about 0.1-30 meters from the radar. A short-range radar is useful in detecting objects located nearby the vehicle, such as other vehicles, buildings, walls, pedestrians, bicyclists, etc. A short-range radar can be used to detect a blind spot, assist in lane changing, provide rear-end collision warning, assist in parking, provide emergency braking, or the like. A medium-range radar measures objects located at about 30-80 meters from the radar. A long-range radar measures objects located at about 80-200 meters. Medium- and/or long-range radars can be useful in, for example, traffic following, adaptive cruise control, and/or highway automatic braking. Sensor data generated by radar sensor(s) 234 can also be provided to vehicle perception and planning system 220 via communication path 233 for further processing and controlling the vehicle operations.
Other vehicle onboard sensor(s) 230 can also include ultrasonic sensor(s) 236. Ultrasonic sensor(s) 236 use acoustic waves or pulses to measure object located external to a vehicle. The acoustic waves generated by ultrasonic sensor(s) 236 are transmitted to the surrounding environment. At least some of the transmitted waves are reflected off an object and return to the ultrasonic sensor(s) 236. Based on the return signals, a distance of the object can be calculated. Ultrasonic sensor(s) 236 can be useful in, for example, check blind spot, identify parking spots, provide lane changing assistance into traffic, or the like. Sensor data generated by ultrasonic sensor(s) 236 can also be provided to vehicle perception and planning system 220 via communication path 233 for further processing and controlling the vehicle operations.
In some embodiments, one or more other sensor(s) 238 may be attached in a vehicle and may also generate sensor data. Other sensor(s) 238 may include, for example, global positioning systems (GPS), inertial measurement units (IMU), or the like. Sensor data generated by other sensor(s) 238 can also be provided to vehicle perception and planning system 220 via communication path 233 for further processing and controlling the vehicle operations. It is understood that communication path 233 may include one or more communication links to transfer data between the various sensor(s) 230 and vehicle perception and planning system 220.
In some embodiments, as shown in
With reference still to
Sharing sensor data facilitates a better perception of the environment external to the vehicles. For instance, a first vehicle may not sense a pedestrian that is behind a second vehicle but is approaching the first vehicle. The second vehicle may share the sensor data related to this pedestrian with the first vehicle such that the first vehicle can have additional reaction time to avoid collision with the pedestrian. In some embodiments, similar to data generated by sensor(s) 230, data generated by sensors onboard other vehicle(s) 250 may be correlated or fused with sensor data generated by LiDAR system(s) 210, thereby at least partially offloading the sensor fusion process performed by vehicle perception and planning system 220.
In some embodiments, intelligent infrastructure system(s) 240 are used to provide sensor data separately or together with LiDAR system(s) 210. Certain infrastructures may be configured to communicate with a vehicle to convey information and vice versa. Communications between a vehicle and infrastructures are generally referred to as V2I (vehicle to infrastructure) communications. For example, intelligent infrastructure system(s) 240 may include an intelligent traffic light that can convey its status to an approaching vehicle in a message such as “changing to yellow in 5 seconds.” Intelligent infrastructure system(s) 240 may also include its own LiDAR system mounted near an intersection such that it can convey traffic monitoring information to a vehicle. For example, a left-turning vehicle at an intersection may not have sufficient sensing capabilities because some of its own sensors may be blocked by traffic in the opposite direction. In such a situation, sensors of intelligent infrastructure system(s) 240 can provide useful, and sometimes vital, data to the left-turning vehicle. Such data may include, for example, traffic conditions, information of objects in the direction the vehicle is turning to, traffic light status and predictions, or the like. These sensor data generated by intelligent infrastructure system(s) 240 can be provided to vehicle perception and planning system 220 and/or vehicle onboard LiDAR system(s) 210, via communication paths 243 and/or 241, respectively. Communication paths 243 and/or 241 can include any wired or wireless communication links that can transfer data. For example, sensor data from intelligent infrastructure system(s) 240 may be transmitted to LiDAR system(s) 210 and correlated or fused with sensor data generated by LiDAR system(s) 210, thereby at least partially offloading the sensor fusion process performed by vehicle perception and planning system 220. V2V and V2I communications described above are examples of vehicle-to-X (V2X) communications, where the “X” represents any other devices, systems, sensors, infrastructure, or the like that can share data with a vehicle.
With reference still to
In other examples, sensor data generated by other vehicle onboard sensor(s) 230 may have a lower resolution (e.g., radar sensor data) and thus may need to be correlated and confirmed by LiDAR system(s) 210, which usually has a higher resolution. For example, a sewage cover (also referred to as a manhole cover) may be detected by radar sensor 234 as an object towards which a vehicle is approaching. Due to the low-resolution nature of radar sensor 234, vehicle perception and planning system 220 may not be able to determine whether the object is an obstacle that the vehicle needs to avoid. High-resolution sensor data generated by LiDAR system(s) 210 thus can be used to correlated and confirm that the object is a sewage cover and causes no harm to the vehicle.
Vehicle perception and planning system 220 further comprises an object classifier 223. Using raw sensor data and/or correlated/fused data provided by sensor fusion sub-system 222, object classifier 223 can detect and classify the objects and estimate the positions of the objects. In some embodiments, object classifier 233 can use machine-learning based techniques to detect and classify objects. Examples of the machine-learning based techniques include utilizing algorithms such as region-based convolutional neural networks (R-CNN), Fast R-CNN, Faster R-CNN, histogram of oriented gradients (HOG), region-based fully convolutional network (R-FCN), single shot detector (SSD), spatial pyramid pooling (SPP-net), and/or You Only Look Once (Yolo).
Vehicle perception and planning system 220 further comprises a road detection sub-system 224. Road detection sub-system 224 localizes the road and identifies objects and/or markings on the road. For example, based on raw or fused sensor data provided by radar sensor(s) 234, camera(s) 232, and/or LiDAR system(s) 210, road detection sub-system 224 can build a 3D model of the road based on machine-learning techniques (e.g., pattern recognition algorithms for identifying lanes). Using the 3D model of the road, road detection sub-system 224 can identify objects (e.g., obstacles or debris on the road) and/or markings on the road (e.g., lane lines, turning marks, crosswalk marks, or the like).
Vehicle perception and planning system 220 further comprises a localization and vehicle posture sub-system 225. Based on raw or fused sensor data, localization and vehicle posture sub-system 225 can determine position of the vehicle and the vehicle's posture. For example, using sensor data from LiDAR system(s) 210, camera(s) 232, and/or GPS data, localization and vehicle posture sub-system 225 can determine an accurate position of the vehicle on the road and the vehicle's six degrees of freedom (e.g., whether the vehicle is moving forward or backward, up or down, and left or right). In some embodiments, high-definition (HD) maps are used for vehicle localization. HD maps can provide highly detailed, three-dimensional, computerized maps that pinpoint a vehicle's location. For instance, using the HD maps, localization and vehicle posture sub-system 225 can determine precisely the vehicle's current position (e.g., which lane of the road the vehicle is currently in, how close it is to a curb or a sidewalk) and predict vehicle's future positions.
Vehicle perception and planning system 220 further comprises obstacle predictor 226. Objects identified by object classifier 223 can be stationary (e.g., a light pole, a road sign) or dynamic (e.g., a moving pedestrian, bicycle, another car). For moving objects, predicting their moving path or future positions can be important to avoid collision. Obstacle predictor 226 can predict an obstacle trajectory and/or warn the driver or the vehicle planning sub-system 228 about a potential collision. For example, if there is a high likelihood that the obstacle's trajectory intersects with the vehicle's current moving path, obstacle predictor 226 can generate such a warning. Obstacle predictor 226 can use a variety of techniques for making such a prediction. Such techniques include, for example, constant velocity or acceleration models, constant turn rate and velocity/acceleration models, Kalman Filter and Extended Kalman Filter based models, recurrent neural network (RNN) based models, long short-term memory (LSTM) neural network based models, encoder-decoder RNN models, or the like.
With reference still to
Vehicle control system 280 controls the vehicle's steering mechanism, throttle, brake, etc., to operate the vehicle according to the planned route and movement. Vehicle perception and planning system 220 may further comprise a user interface 260, which provides a user (e.g., a driver) access to vehicle control system 280 to, for example, override or take over control of the vehicle when necessary. User interface 260 can communicate with vehicle perception and planning system 220, for example, to obtain and display raw or fused sensor data, identified objects, vehicle's location/posture, etc. These displayed data can help a user to better operate the vehicle. User interface 260 can communicate with vehicle perception and planning system 220 and/or vehicle control system 280 via communication paths 221 and 261 respectively, which include any wired or wireless communication links that can transfer data. It is understood that the various systems, sensors, communication links, and interfaces in
LiDAR system 300 can also include other components not depicted in
Laser source 310 outputs laser light for illuminating objects in a field of view (FOV). Laser source 310 can be, for example, a semiconductor-based laser (e.g., a diode laser) and/or a fiber-based laser. A semiconductor-based laser can be, for example, an edge emitting laser (EEL), a vertical cavity surface emitting laser (VCSEL), or the like. A fiber-based laser is a laser in which the active gain medium is an optical fiber doped with rare-earth elements such as erbium, ytterbium, neodymium, dysprosium, praseodymium, thulium and/or holmium. In some embodiments, a fiber laser is based on double-clad fibers, in which the gain medium forms the core of the fiber surrounded by two layers of cladding. The double-clad fiber allows the core to be pumped with a high-power beam, thereby enabling the laser source to be a high-power fiber laser source.
In some embodiments, laser source 310 comprises a master oscillator (also referred to as a seed laser) and power amplifier (MOPA). The power amplifier amplifies the output power of the seed laser. The power amplifier can be a fiber amplifier, a bulk amplifier, or a semiconductor optical amplifier. The seed laser can be a diode laser (e.g., a Fabry-Perot cavity laser, a distributed feedback laser), a solid-state bulk laser, or a tunable external-cavity diode laser. In some embodiments, laser source 310 can be an optically pumped microchip laser. Microchip lasers are alignment-free monolithic solid-state lasers where the laser crystal is directly contacted with the end mirrors of the laser resonator. A microchip laser is typically pumped with a laser diode (directly or using a fiber) to obtain the desired output power. A microchip laser can be based on neodymium-doped yttrium aluminum garnet (Y3Al5O12) laser crystals (i.e., Nd:YAG), or neodymium-doped vanadate (i.e., ND:YVO4) laser crystals.
In some variations, fiber-based laser source 400 can be controlled (e.g., by control circuitry 350) to produce pulses of different amplitudes based on the fiber gain profile of the fiber used in fiber-based laser source 400. Communication path 312 couples fiber-based laser source 400 to control circuitry 350 (shown in
Referencing
It is understood that the above descriptions provide non-limiting examples of a laser source 310. Laser source 310 can be configured to include many other types of light sources (e.g., laser diodes, short-cavity fiber lasers, solid-state lasers, and/or tunable external cavity diode lasers) that are configured to generate one or more light signals at various wavelengths. In some examples, light source 310 comprises amplifiers (e.g., pre-amplifiers and/or booster amplifiers), which can be a doped optical fiber amplifier, a solid-state bulk amplifier, and/or a semiconductor optical amplifier. The amplifiers are configured to receive and amplify light signals with desired gains.
With reference back to
Laser beams provided by laser source 310 may diverge as they travel to transmitter 320. Therefore, transmitter 320 often comprises a collimating lens configured to collect the diverging laser beams and produce more parallel optical beams with reduced or minimum divergence. The collimated optical beams can then be further directed through various optics such as mirrors and lens. A collimating lens may be, for example, a single plano-convex lens or a lens group. The collimating lens can be configured to achieve any desired properties such as the beam diameter, divergence, numerical aperture, focal length, or the like. A beam propagation ratio or beam quality factor (also referred to as the M2 factor) is used for measurement of laser beam quality. In many LiDAR applications, it is important to have good laser beam quality in the generated transmitting laser beam. The M2 factor represents a degree of variation of a beam from an ideal Gaussian beam. Thus, the M2 factor reflects how well a collimated laser beam can be focused on a small spot, or how well a divergent laser beam can be collimated. Therefore, laser source 310 and/or transmitter 320 can be configured to meet, for example, scan resolution requirement while maintaining desired M2 factor.
One or more of the light beams provided by transmitter 320 are scanned by steering mechanism 340 to a FOV. Steering mechanism 340 scans light beams in multiple dimensions (e.g., in both the horizontal and vertical dimension) to facilitate LiDAR system 300 to map the environment by generating a 3D point cloud. Steering mechanism 340 will be described in more detail below. The laser light scanned to an FOV may be scattered or reflected by an object in the FOV. At least a portion of the scattered or reflected light returns to LiDAR system 300.
A light detector detects the return light focused by the optical receiver and generates current and/or voltage signals proportional to the incident intensity of the return light. Based on such current and/or voltage signals, the depth information of the object in the FOV can be derived. One exemplary method for deriving such depth information is based on the direct TOF (time of flight), which is described in more detail below. A light detector may be characterized by its detection sensitivity, quantum efficiency, detector bandwidth, linearity, signal to noise ratio (SNR), overload resistance, interference immunity, etc. Based on the applications, the light detector can be configured or customized to have any desired characteristics. For example, optical receiver and light detector 330 can be configured such that the light detector has a large dynamic range while having a good linearity. The light detector linearity indicates the detector's capability of maintaining linear relationship between input optical signal power and the detector's output. A detector having good linearity can maintain a linear relationship over a large dynamic input optical signal range.
To achieve desired detector characteristics, configurations or customizations can be made to the light detector's structure and/or the detector's material system. Various detector structure can be used for a light detector. For example, a light detector structure can be a PIN based structure, which has a undoped intrinsic semiconductor region (i.e., an “i” region) between a p-type semiconductor and an n-type semiconductor region. Other light detector structures comprise, for example, a APD (avalanche photodiode) based structure, a PMT (photomultiplier tube) based structure, a SiPM (Silicon photomultiplier) based structure, a SPAD (single-photon avalanche diode) based structure, and/or quantum wires. For material systems used in a light detector, Si, InGaAs, and/or Si/Ge based materials can be used. It is understood that many other detector structures and/or material systems can be used in optical receiver and light detector 330.
A light detector (e.g., an APD based detector) may have an internal gain such that the input signal is amplified when generating an output signal. However, noise may also be amplified due to the light detector's internal gain. Common types of noise include signal shot noise, dark current shot noise, thermal noise, and amplifier noise (TIA). In some embodiments, optical receiver and light detector 330 may include a pre-amplifier that is a low noise amplifier (LNA). In some embodiments, the pre-amplifier may also include a TIA-transimpedance amplifier, which converts a current signal to a voltage signal. For a linear detector system, input equivalent noise or noise equivalent power (NEP) measures how sensitive the light detector is to weak signals. Therefore, they can be used as indicators of the overall system performance. For example, the NEP of a light detector specifies the power of the weakest signal that can be detected and therefore it in turn specifies the maximum range of a LiDAR system. It is understood that various light detector optimization techniques can be used to meet the requirement of LiDAR system 300. Such optimization techniques may include selecting different detector structures, materials, and/or implement signal processing techniques (e.g., filtering, noise reduction, amplification, or the like). For example, in addition to or instead of using direct detection of return signals (e.g., by using TOF), coherent detection can also be used for a light detector. Coherent detection allows for detecting amplitude and phase information of the received light by interfering the received light with a local oscillator. Coherent detection can improve detection sensitivity and noise immunity.
Steering mechanism 340 can be used with the transceiver (e.g., transmitter 320 and optical receiver and light detector 330) to scan the FOV for generating an image or a 3D point cloud. As an example, to implement steering mechanism 340, a two-dimensional mechanical scanner can be used with a single-point or several single-point transceivers. A single-point transceiver transmits a single light beam or a small number of light beams (e.g., 2-8 beams) to the steering mechanism. A two-dimensional mechanical steering mechanism comprises, for example, polygon mirror(s), oscillating mirror(s), rotating prism(s), rotating tilt mirror surface(s), or a combination thereof. In some embodiments, steering mechanism 340 may include non-mechanical steering mechanism(s) such as solid-state steering mechanism(s). For example, steering mechanism 340 can be based on tuning wavelength of the laser light combined with refraction effect, and/or based on reconfigurable grating/phase array. In some embodiments, steering mechanism 340 can use a single scanning device to achieve two-dimensional scanning or two devices combined to realize two-dimensional scanning.
As another example, to implement steering mechanism 340, a one-dimensional mechanical scanner can be used with an array or a large number of single-point transceivers. Specifically, the transceiver array can be mounted on a rotating platform to achieve 360-degree horizontal field of view. Alternatively, a static transceiver array can be combined with the one-dimensional mechanical scanner. A one-dimensional mechanical scanner comprises polygon mirror(s), oscillating mirror(s), rotating prism(s), rotating tilt mirror surface(s) for obtaining a forward-looking horizontal field of view. Steering mechanisms using mechanical scanners can provide robustness and reliability in high volume production for automotive applications.
As another example, to implement steering mechanism 340, a two-dimensional transceiver can be used to generate a scan image or a 3D point cloud directly. In some embodiments, a stitching or micro shift method can be used to improve the resolution of the scan image or the field of view being scanned. For example, using a two-dimensional transceiver, signals generated at one direction (e.g., the horizontal direction) and signals generated at the other direction (e.g., the vertical direction) may be integrated, interleaved, and/or matched to generate a higher or full resolution image or 3D point cloud representing the scanned FOV.
Some implementations of steering mechanism 340 comprise one or more optical redirection elements (e.g., mirrors or lenses) that steer return light signals (e.g., by rotating, vibrating, or directing) along a receive path to direct the return light signals to optical receiver and light detector 330. The optical redirection elements that direct light signals along the transmitting and receiving paths may be the same components (e.g., shared), separate components (e.g., dedicated), and/or a combination of shared and separate components. This means that in some cases the transmitting and receiving paths are different although they may partially overlap (or in some cases, substantially overlap).
With reference still to
Control circuitry 350 can also be configured and/or programmed to perform signal processing to the raw data generated by optical receiver and light detector 330 to derive distance and reflectance information, and perform data packaging and communication to vehicle perception and planning system 220 (shown in
LiDAR system 300 can be disposed in a vehicle, which may operate in many different environments including hot or cold weather, rough road conditions that may cause intense vibration, high or low humidities, dusty areas, etc. Therefore, in some embodiments, optical and/or electronic components of LiDAR system 300 (e.g., optics in transmitter 320, optical receiver and light detector 330, and steering mechanism 340) are disposed or configured in such a manner to maintain long term mechanical and optical stability. For example, components in LiDAR system 300 may be secured and sealed such that they can operate under all conditions a vehicle may encounter. As an example, an anti-moisture coating and/or hermetic sealing may be applied to optical components of transmitter 320, optical receiver and light detector 330, and steering mechanism 340 (and other components that are susceptible to moisture). As another example, housing(s), enclosure(s), and/or window can be used in LiDAR system 300 for providing desired characteristics such as hardness, ingress protection (IP) rating, self-cleaning capability, resistance to chemical and resistance to impact, or the like. In addition, efficient and economical methodologies for assembling LiDAR system 300 may be used to meet the LiDAR operating requirements while keeping the cost low.
It is understood by a person of ordinary skill in the art that
These components shown in
As described above, some LiDAR systems use the time-of-flight (TOF) of light signals (e.g., light pulses) to determine the distance to objects in a light path. For example, with reference to
Referring back to
By directing many light pulses, as depicted in
If a corresponding light pulse is not received for a particular transmitted light pulse, then it may be determined that there are no objects within a detectable range of LiDAR system 500 (e.g., an object is beyond the maximum scanning distance of LiDAR system 500). For example, in
In
The density of a point cloud refers to the number of measurements (data points) per area performed by the LiDAR system. A point cloud density relates to the LiDAR scanning resolution. Typically, a larger point cloud density, and therefore a higher resolution, is desired at least for the region of interest (ROI). The density of points in a point cloud or image generated by a LiDAR system is equal to the number of pulses divided by the field of view. In some embodiments, the field of view can be fixed. Therefore, to increase the density of points generated by one set of transmission-receiving optics (or transceiver optics), the LiDAR system may need to generate a pulse more frequently. In other words, a light source with a higher pulse repetition rate (PRR) is needed. On the other hand, by generating and transmitting pulses more frequently, the farthest distance that the LiDAR system can detect may be limited. For example, if a return signal from a distant object is received after the system transmits the next pulse, the return signals may be detected in a different order than the order in which the corresponding signals are transmitted, thereby causing ambiguity if the system cannot correctly correlate the return signals with the transmitted signals.
To illustrate, consider an exemplary LiDAR system that can transmit laser pulses with a repetition rate between 500 kHz and 1 MHz. Based on the time it takes for a pulse to return to the LiDAR system and to avoid mix-up of return pulses from consecutive pulses in a conventional LiDAR design, the farthest distance the LiDAR system can detect may be 300 meters and 150 meters for 500 kHz and 1 MHz, respectively. The density of points of a LiDAR system with 500 kHz repetition rate is half of that with 1 MHz. Thus, this example demonstrates that, if the system cannot correctly correlate return signals that arrive out of order, increasing the repetition rate from 500 kHz to 1 MHz (and thus improving the density of points of the system) may reduce the detection range of the system. Various techniques are used to mitigate the tradeoff between higher PRR and limited detection range. For example, multiple wavelengths can be used for detecting objects in different ranges. Optical and/or signal processing techniques are also used to correlate between transmitted and return light signals.
Various systems, apparatus, and methods described herein may be implemented using digital circuitry, or using one or more computers using well-known computer processors, memory units, storage devices, computer software, and other components. Typically, a computer includes a processor for executing instructions and one or more memories for storing instructions and data. A computer may also include, or be coupled to, one or more mass storage devices, such as one or more magnetic disks, internal hard disks and removable disks, magneto-optical disks, optical disks, etc.
Various systems, apparatus, and methods described herein may be implemented using computers operating in a client-server relationship. Typically, in such a system, the client computers are located remotely from the server computers and interact via a network. The client-server relationship may be defined and controlled by computer programs running on the respective client and server computers. Examples of client computers can include desktop computers, workstations, portable computers, cellular smartphones, tablets, or other types of computing devices.
Various systems, apparatus, and methods described herein may be implemented using a computer program product tangibly embodied in an information carrier, e.g., in a non-transitory machine-readable storage device, for execution by a programmable processor; and the method processes and steps described herein may be implemented using one or more computer programs that are executable by such a processor. A computer program is a set of computer program instructions that can be used, directly or indirectly, in a computer to perform a certain activity or bring about a certain result. A computer program can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.
A high-level block diagram of an exemplary apparatus that may be used to implement systems, apparatus and methods described herein is illustrated in
Processor 610 may include both general and special purpose microprocessors and may be the sole processor or one of multiple processors of apparatus 600. Processor 610 may comprise one or more central processing units (CPUs), and one or more graphics processing units (GPUs), which, for example, may work separately from and/or multi-task with one or more CPUs to accelerate processing, e.g., for various image processing applications described herein. Processor 610, persistent storage device 620, and/or main memory device 630 may include, be supplemented by, or incorporated in, one or more application-specific integrated circuits (ASICs) and/or one or more field programmable gate arrays (FPGAs).
Persistent storage device 620 and main memory device 630 each comprise a tangible non-transitory computer readable storage medium. Persistent storage device 620, and main memory device 630, may each include high-speed random access memory, such as dynamic random access memory (DRAM), static random access memory (SRAM), double data rate synchronous dynamic random access memory (DDR RAM), or other random access solid state memory devices, and may include non-volatile memory, such as one or more magnetic disk storage devices such as internal hard disks and removable disks, magneto-optical disk storage devices, optical disk storage devices, flash memory devices, semiconductor memory devices, such as erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM), digital versatile disc read-only memory (DVD-ROM) disks, or other non-volatile solid state storage devices.
Input/output devices 690 may include peripherals, such as a printer, scanner, display screen, etc. For example, input/output devices 690 may include a display device such as a cathode ray tube (CRT), plasma or liquid crystal display (LCD) monitor for displaying information to a user, a keyboard, and a pointing device such as a mouse or a trackball by which the user can provide input to apparatus 600.
Any or all of the functions of the systems and apparatuses discussed herein may be performed by processor 610, and/or incorporated in, an apparatus or a system such as LiDAR system 300. Further, LiDAR system 300 and/or apparatus 600 may utilize one or more neural networks or other deep-learning techniques performed by processor 610 or other systems or apparatuses discussed herein.
One skilled in the art will recognize that an implementation of an actual computer or computer system may have other structures and may contain other components as well, and that
With reference to
Referencing
In some embodiments, the pitch between the adjacent grooves is preconfigured to provide a desired angular channel spacing between adjacent transmitter channels (and thus a desired angular separation between the transmission light beams). For example, the pitch between adjacent grooves may be configured to be about 100-400 μm. As described in more detail below, transmitter optical fibers 810A-810D positioned with such a pitch have an angular channel spacing between about 0.5-2.5 degrees. As a result, the multiple transmission light beams are positioned 0.5-2.5 degrees apart from one another. The pitch between the adjacent grooves (and therefore between the adjacent transmitter optical fibers) can be precisely controlled to be the same or substantially the same (e.g., within a ±1 μm error) to provide the same or substantially the same angular channel spacing between the adjacent transmitter channels (and thus the angular separation between the transmission light beams). When the transmitter channels have proper angular channel spacings between them, the adjacent transmission light beams are positioned apart at a desired angular separation. The multiple transmission light beams can thus scan different areas within a FOV. The resulted scan pattern can have a desired high resolution. The transmitter described herein thus provides a good coverage of the scanned areas and improves the LiDAR system's scan resolution and speed.
Referencing still to
In some embodiments, one or more of the transmitter optical fibers 808A-808D comprise one or more single-mode optical fiber(s). A single-mode optical fiber includes a core with a very small diameter (e.g., a few micrometers) that only allows one transverse mode of light at the designed wavelength to travel through. As a result, the output beam quality can be close to the diffraction limit (e.g., M2≈1).
As shown in
As shown in
Angular channel spacing=pitch of the grooves for disposing the transmitter optical fibers/focal length of the collimation lens. [Eq. 1]
Therefore, to obtain a larger angular channel spacing, a larger pitch and/or a smaller focal length may be used, and vice versa.
By configuring the pitch between the transmitter optical fibers and/or the focal length of the collimation lens, the desired angular channel spacing can be obtained. In some embodiments, the angular channel spacing is determined based on one or more of a required LiDAR scan resolution, a region-of-interest (ROI) requirement, and a scan range of the field-of-view. For example, a smaller angular channel spacing (and/or a larger number of transmitter channels) may be required for a higher scanning resolution. An ROI area may need to be scanned with a higher resolution while a non-ROI area may use a lower resolution scan. Therefore, the scanning performance of the LiDAR system can be improved by using multiple transmitter channels having a properly configured angular channel spacing.
As described above, embodiments disclosed herein use multiple transmitter channels comprising an array of transmitter optical fibers. At least the end portions of the transmitter optical fibers are configured to have a precision pitch. A single collimation lens is used to form collimated transmission light beams for all transmitter channels. As a result, many transmitter channels can be assembled or integrated into the space corresponding to a single collimation lens, thereby reducing the dimensions of the transceiver and making the LiDAR system more compact. Moreover, the complexity of the alignment of the entire transmitter channel assembly 710 is also reduced because multiple transmitter channels share a single collimation lens.
As described above, a collimation lens can be used to collimate multiple transmission light beams to form collimated transmission light beams. In some embodiments, the collimation lens and the collection lens may be disposed side-by-side. In other embodiments, it is beneficial to have the collimated transmission light beams shifted to a location around the center of the collection lens. The transceiver thus may further comprise an optical beam-shifting system that redirects the collimated transmission light beams such that at least a part of the collimated transmission light beams is positioned within an optical receiving aperture of the collection lens. In some embodiments, an optical beam-shifting system includes one or more of prisms, lenses, and mirrors configured to redirect the collimated transmission light beams such that the redirected collimated transmission light beams are substantially parallel to the collimated transmission light beams.
As described above, when multiple transmission light beams are scanned into an FOV, some of the light may be reflected and/or scattered by objects in the FOV. The reflected or scattered light forms return light that is received and detected by the LiDAR system.
The optical crosstalk and APDs' placement errors may result in wrong signal intensities and/or wavelengths (e.g., if return light 1204A and 1204B have different wavelengths) being detected. In turn, the wrong signal intensities may result in reducing of the accuracy of determining various object parameters (e.g., distance, shape, speed, or the like). The overall LiDAR performance may thus be negatively impacted.
Furthermore, as illustrated in
As shown in
Referencing still to
In some embodiments, adjacent grooves are positioned at a predetermined pitch from each other. In one embodiment, the pitch between adjacent grooves is measured from the center lines of the adjacent grooves. The pitch between the adjacent grooves is preconfigured to a proper value such that receiver optical fibers 1310A-1310D are positioned to receive respective return light directed by the collection lens. As described above, the return light generated from different transmission light beams are directed by the collection lens at different angles. Therefore, the value of the pitch between adjacent grooves can also be determined based on the angular channel spacing of the transmitter channels. For example, the pitch between adjacent grooves may be configured to be about 200-2000 μm. Receiver optical fibers 1310A-1310D disposed with such a pitch can be used to receive return light generated from transmitter channels having an angular channel spacing of about 0.5-2.5 degrees. The pitch between the adjacent grooves, and the pitch between the adjacent receiver optical fibers, can be precisely controlled to be the same or substantially the same (e.g., within a ±10 μm error) such that the return light generated from different transmission light beams are received and directed properly to their respective receiver optical fibers. Referencing still to
In some embodiments, each of the receiver optical fibers 1310A-1310D comprises a multi-mode optical fiber. Compared to a single-mode optical fiber, a multi-mode optical fiber has a much larger core diameter (e.g., 50-1000 micrometers), which is much larger than the wavelength of the light carried in the multi-mode optical fiber. Because of the large core and thus the possibility of a large numerical aperture, a multi-mode optical fiber has greater light-gathering capacity than single-mode optical fiber. Thus, multi-mode optical fibers are more appropriate for receiving return light directed by the collection lens. Multi-mode optical fibers thus generally perform better than single-mode optical fibers when they are used in receiver channels.
In the embodiment shown in
Alignment optical fibers 1530A and 1530B do not carry return light to detector assemblies. Alignment optical fibers 1530A and 1530B facilitate alignment of the plurality of receiver optical fibers 1510A-1510D. Using alignment optical fiber 1530A as an example, light can be coupled to alignment optical fiber 1530A from the end opposite to the end where receiver optical fibers 1510A-1510B receive return light (i.e., from the end that is close to the detector assemblies coupled to receiver optical fibers 1510A-1510B). The light travels through alignment optical fiber 1530A and can be measured by a beam profiler as if the light is a transmission light beam. For example, the light received at the other end of the alignment optical fiber can be measured for the beam width, beam pointing, and beam rotation alignment. Once the alignment optical fiber 1530A is aligned, receiver optical fibers 1510A and 1510B are considered aligned too, because the receiver optical fibers and the alignment optical fiber are disposed at a precise pitch from one another.
In some embodiments, during operation, one or both alignment optical fibers 1530A and 1530B can be used to generate uniform illumination for other channels as reference signals. For example, alignment optical fiber 1530A may be used to provide a reference signal for measuring distances of one or more objects within the FOV. Alignment optical fibers 1530A and/or 1530B can be used to implement reference fiber 732 shown in
In some embodiments, as shown in
In some embodiments, detector assembly 1712 comprises a collimation lens 1716 optical coupled to a receiver optical fiber 1710. Collimation lens 1716 collimates the return light carried by receiver optical fiber 1710. Detector assembly further comprises a bandpass filter 1718 optically coupled to collimation lens 1716. Bandpass filter 1718 operates to filter out light having undesired wavelengths (e.g., sunlight or any other undesired light interference), thereby reducing optical noise and background light. In some embodiments, bandpass filter 1718 can be configured to have a narrow pass band. Bandpass filter 1718 can also have a small dimension and be cost-effective compared to larger bandpass filters. Bandpass filter 1718 is further optically coupled to a focusing lens 1720, which focuses the filtered return light to detector 1722. In some embodiments, detector 1722 can be an avalanche photodiode detector (APD) or any other desired type of detector. As shown in
While
Various exemplary embodiments are described herein. Reference is made to these examples in a non-limiting sense. They are provided to illustrate more broadly applicable aspects of the disclosed technology. Various changes may be made, and equivalents may be substituted without departing from the true spirit and scope of the various embodiments. In addition, many modifications may be made to adapt a particular situation, material, composition of matter, process, process act(s) or step(s) to the objective(s), spirit or scope of the various embodiments. Further, as will be appreciated by those with skill in the art, each of the individual variations described and illustrated herein has discrete components and features which may be readily separated from or combined with the features of any of the other several embodiments without departing from the scope or spirit of the various embodiments.
This application claims priority to U.S. Provisional Patent Application Ser. No. 63/155,297, filed Mar. 1, 2021, entitled “LIDAR RECEIVER FIBER ARRAY”, and U.S. Provisional Patent Application Ser. No. 63/209,856, filed Jun. 11, 2021, entitled “LIDAR TRANSMITTER FIBER ARRAY”. The contents of both applications are hereby incorporated by reference in their entirety for all purposes.
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