The present disclosure relates to light detection and ranging (LiDAR), and in particular to LiDAR systems and methods for use in a vehicle.
Systems exist that enable vehicles to be driven semi-autonomously or fully autonomously. Such systems may use one or more range finding, mapping, or object detection systems to provide sensory input to assist in semi-autonomous or fully autonomous vehicle control. Many of these systems are relatively large and bulky and thus require a relatively large amount of space on the vehicle. In addition, many of these systems are relatively power intensive.
Embodiments discussed herein refer to a relatively compact and energy efficient LiDAR system that uses a multi-plane mirror as part of its scanning system.
In one embodiment, a light detection and ranging (LiDAR) system for use with a vehicle is provided. The system can include a housing configured to be mounted to a windshield of the vehicle. The housing can include a transceiver module operative to transmit and receive light energy, a polygon structure that defines a lateral angle of the field of view of the LiDAR system, and a moveable mirror positioned to redirect light energy passing between the transceiver module and the polygon structure, the moveable mirror operative to control an exit angle of light being redirected by the polygon structure, wherein the exit angle corresponds to a particular angle within a vertical field of view of the LiDAR system
In another embodiment, a light detection and ranging (LiDAR) system can include a transceiver module operative to transmit and receive light energy, a structure that defines a lateral angle of the field of view of the LiDAR system, and a multi-plane mirror positioned to redirect light energy passing between the transceiver module and the structure, the multi-plane mirror operative to control an exit angle of light being redirected by the structure, wherein the exit angle corresponds to a particular angle within a vertical field of view of the LiDAR system.
In yet another embodiment, a light detection and ranging (LiDAR) system can include a transceiver module operative to transmit and receive light energy, a first mirror that defines a vertical angle of a field of view of the LiDAR system and oscillates in one of a direct drive mode and a resonant drive mode, and a second mirror that defines a horizontal angle of the field of view of the LiDAR system oscillates in one of a direct drive mode and a resonant drive mode, wherein the first mirror oscillates along a plane that is orthogonal to an oscillation plane of the second mirror.
A further understanding of the nature and advantages of the embodiments discussed herein may be realized by reference to the remaining portions of the specification and the drawings.
Illustrative embodiments are now described more fully hereinafter with reference to the accompanying drawings, in which representative examples are shown. Indeed, the disclosed communication systems and methods may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Like numbers refer to like elements throughout.
In the following detailed description, for purposes of explanation, numerous specific details are set forth to provide a thorough understanding of the various embodiments. Those of ordinary skill in the art will realize that these various embodiments are illustrative only and are not intended to be limiting in any way. Other embodiments will readily suggest themselves to such skilled persons having the benefit of this disclosure.
In addition, for clarity purposes, not all of the routine features of the embodiments described herein are shown or described. One of ordinary skill in the art would readily appreciate that in the development of any such actual embodiment, numerous embodiment-specific decisions may be required to achieve specific design objectives. These design objectives will vary from one embodiment to another and from one developer to another. Moreover, it will be appreciated that such a development effort might be complex and time-consuming but would nevertheless be a routine engineering undertaking for those of ordinary skill in the art having the benefit of this disclosure.
WMLS 150 can be a front facing, forward scanning system that captures lateral and vertical resolution of the 3D space existing in front of the vehicle. The lateral and vertical resolution can define the field of view of WMLS 150. In some embodiments, the lateral field of view is greater than the vertical field of view. For example, the lateral field of view can range from 100-180 degrees, or 110-170 degrees, or can be 120 degrees, whereas the vertical field of view can range from 20-50 degrees, 25-45 degrees, or 40 degrees. The ranging distance of the field of view can be set to any desired distance. For example, the ranging distance may be 50-300 meters, 100-200 meters, or 150 meters.
The facets number of polygon structure 230 is determined to accommodate horizontal FOV. The facet of polygon can be parallel or non-parallel to its symmetric axis. Polygon structure 230 may be constructed from a metal such as aluminum, a plastic, or other material that can have a polished or mirrored surface. Polygon structure may be selectively masked to control the lateral dispersion of light energy being projected in accordance with the field of view of WMLS 200. Polygon structure 230 is operative to spin about axis 231 in a first direction at a substantially constant speed. The axis 231 can be coincident to structure 230 symmetrical axis or it can be tilted with an angle to structure 230 symmetrical axis, which can effectively increase resolution in vertical angle of z. A motor such as a DC motor may control the spin of structure 230. The final shape of polygon can be trimmed (i.e., chop off the sharp corner or tip to reduce overall weight, chamfer the sharp edge to reduce air resistance) for better operation performance.
Transceiver module 220 may be placed on a movable platform (not shown) that can change the position or pointing of transceiver module 220 within housing 201. The platform may move the entire module 220 in the directions of arrow 221. Alternatively, the platform may rotate module 220 along the directions of arrow 222. Moving transceiver module 220 enables WMLS 200 to increase its resolution by capturing image data that exists in gaps caused by the lenses being used in transceiver module 220.
Gaps may exist between the angles represented by vectors A-D. That is, gaps exist between vectors A and B (shown as A/B Gap), B and C (shown as B/C Gap), and C and D (shown as C/D Gap). In this case, the angle between A and D defines the vertical field of view. The LiDAR systems according to embodiments discussed herein take these gaps into account by moving transceiver module 220 (as shown in
Light energy emanating from light source 510 may be collimated by lens 520, which may be, for example, a cylindrical lens, before the light energy is dispersed by lens group 530. Lens group 530 can include any suitable number of lenses to control, for example, the vertical angle of the field of view. As shown, lens group 530 can include lenses 531-534. Each of lenses 531-534 may independently direct light energy according to non-overlapping angles shown as vectors A, B, C, and D. Each lens corresponds to a particular range of angles, as explained above in connection with
It should be understood that the steps in
It should be understood that the steps in
Dual plane mirror 1040 may oscillate about axis 1050 in the direction as shown by arrow 1051. Dual plane mirror 1040 can be constructed as a mirror structure including reflective plane members 1041 and 1042 connected together at transition point 1043 and oriented at an angle, a, with respect to each other. When dual plane mirror 1040 oscillates about axis 1050, it partially rotates in a first direction along the path shown by arrow 1051 until reaches a first transition point, at which point it reverses direction and partially rotates in a second direction along the same path shown by arrow 1051 until it reaches a second transition point, at which point it reverses direction and partially rotates along the first direction. As dual plane mirror 1040 oscillates, reflective plate members 1041 and 1042 take turns redirecting light energy between polygon 1030 and transceiver 1020, depending on the instantaneous position of mirror 1040 within the oscillation cycle.
A vertical scanning rate refers to the rate at which the LiDAR system can traverse its entire vertical field of view. The scanning rate can vary depending on the manner in which the dual plane mirror is driven. The dual plane mirror can be driven using a direct drive or a resonant drive. Direct drive is typically used for relatively slow scanning rates (e.g., up to around 30 Hertz) and a resonant drive is typically used for relatively faster scanning rates (e.g., greater than 5 Hertz). Direct drives may be limited in their ability to operate at faster scanning rates because the power required support the scanning rate is the cube of the frequency. This may be because a strong anti-current is needed to reverse direction. Thus, while a faster scan rate may be desirable, it may not be practical in implementation. For example, in a system such as WLMS 300, which uses a direct drive, increased scanning rates may be realized with the cost of a significant power penalty. This may be because significant energy must be expended to reverse direction of the single plane mirror's movement. In addition, because a single plane mirror is being used in a direct drive mode, the scanning density is relatively higher at the top and low ends of the vertical field of view, and the center region of the field of view has a relatively low scanning density. See, for example, chart 1310 of
In a system such as WLMS 1000, which uses a dual plane mirror, increased scanning rates can be achieved using a resonant drive mode. The resonant drive mode can leverage a “spring” or potential energy to operate at relatively higher frequencies without an exponential (e.g., cube of the frequency) power penalty. Using a dual plane mirror in resonance mode can result in a scanning density that is relatively higher in the middle portion of the field of view as compared to the top and bottom portions. See, for example, chart 1320 of
At time t0, dual plane mirror 1120 is rotating counterclockwise, and is located at a transition point between the two planes of dual plane mirror 1120. At time t1, dual plane mirror 1120 continues rotating counterclockwise and the exit beam is at exit beam angle 1140. At angle 1140, the light energy emitted by transceiver 1110 interacts with a portion of polygon structure 1130 (as shown) and is directed at a negative angle with respect to a horizontal plane (shown by the dashed lines). At time t2, dual plane mirror 1120 reaches a transition point wherein its velocity becomes zero before rotating clockwise. At time t2 the exit beam is at angle 1150, which is directed at an angle coplanar with the horizontal plane (as shown by the dashed line). At time t3, dual plane mirror 1120 continues rotating clockwise and reaches the same position as it occupied at time t1. Exit beam angle 1140 may also exist at time, t3. At time t4, dual plane mirror 1120 continues rotating clockwise and reaches the same position it occupied at time t0, a transition point between the two planes of dual plane mirror 1120. At time t5, dual plane mirror 1120 continues rotating clockwise and has exit beam angle 1160, which shows that the light is redirected at a positive angle with respect to the horizontal plane (shown by the dashed line). At time t6 dual plane mirror 1120 reaches a transition point wherein its velocity becomes zero before rotating counterclockwise. At time t6, exit beam angle 1150 exists and is identical to the exit beam angles at times t1 and t3. At time t7 dual plane mirror 1120 continues rotating counterclockwise and reaches the same position it occupied at time t5, at which point it has exit beam angle 1160. At time t8 dual plane mirror 1120 continues rotating counterclockwise and reaches the same position it occupied at times t0 and t4, a transition point between the two planes of dual plane mirror 1120. It should be appreciated that the depiction of the arrows are merely illustrative.
At each position in time illustrated for mirror 1210 and dual plane mirror 1220, corresponding relative velocities are shown. Velocities of both mirror 1210 and dual plane mirror 1220 are assumed to be equal in
Energy is required to decelerate or accelerate a mirror such as mirror 1210 or dual plane mirror 1220. Energy required to change mirror direction increases exponentially as a function of system average velocity. Mirrors in systems such as WLMS 300 or WLMS 1000 move in order to provide vertical resolution for the light energy as it interacts with transceiver modules such as transceiver module 320 or transceiver module 1020. As illustrated in
A third benefit of a dual plane mirror such as dual plane mirror 1220 compared to a mirror such as mirror 1210 is improved resolution distribution. For LiDAR design considerations, the more time light energy is directed to the center of polygon structures such as polygon structure 1230, the greater resolution in the center of the range, a desirable design characteristic. Velocity and exit angles are shown in
For a dual plane mirror such as dual plane mirror 1220, exit angles 1221 that are co-planer with a horizontal plane (shown by dashed lines) can occur at times, tDP,0 and tDP,6 and the velocity of mirror 1220 is approximately zero. After time, tDP,0, mirror 1220 is moving the clockwise direction. At time tDP,1 the velocity is approximately low-medium and exit angle 1222 exists. Exit angle 1222 may be partially negative with respect to the horizontal plane (shown by dashed lines). At time tDP,2 the velocity is approximately medium-high and exit angle 1223 exists. Exit angle 1223 may be max negative with respect to the horizontal plane (shown by dashed lines). At time tDP,3 mirror 1220 is at the transition point between planes, and also represents the point at which mirror 1220 is moving at a maximum velocity and the exit angle transitions form the max negative angle to a max positive angle. At time tDP,4 mirror 1220 is moving with an approximate velocity of medium-high and yields exit angle 1224, which corresponds to a max positive angle with respect to a horizontal plane (shown by dashed lines). At time tDP,5 mirror 1220 is moving with an approximate velocity of low-medium and yields exit angle 1225, which corresponds to a partial positive angle with respect to a horizontal plane (shown by dashed lines). At time tDP,6 mirror 1220 is moving with an approximate velocity of zero (as it is transitioning from clockwise rotation to counterclockwise rotation) and yields exit angle 1221, which corresponds to an angle coplanar to a horizontal plane (shown by dashed lines).
The vertical resolution produced by use of mirror 1220 results in a higher concentration of exit angles (or resolution) near the horizontal plane than any other exit angle. See chart 1320 of
For energy reduction, the mirror of a LiDAR system may also be designed as a polygon structure rotating fully about a central axis. This design may eliminate directional transition points during scan cycles and thus may reduce system energy consumption. Polygon 1420 (three-sided), polygon 1430 (four-sided), polygon 1440 (five-sided), and polygon 1450 (six-sided) are illustrations of polygonal mirror structures that may rotate about a central axis and redirect light energy without directional transitions. These polygonal mirrors are shown for illustrative purposes; polygonal mirrors with different number of surfaces are possible.
In some embodiments, vehicle 900 can operate under solely control of a human operator, but the various sensors and systems of the vehicle and the road conditions (e.g., road and the path traveled, other vehicles, stop signs, traffic lights, various events occurring outside of the vehicle) can be monitored and recorded.
Vehicle 900 can include various subsystems such as a propulsion system 902, a sensor system 904, a control system 906, one or more peripherals 908, as well as a power supply 910, a computer system 912, and a user interface 916. Vehicle 900 may include more or fewer subsystems and each subsystem can include multiple elements. Further, each of the subsystems and elements of vehicle 900 can be interconnected. Thus, one or more of the described functions of the vehicle 900 may be divided up into additional functional or physical components, or combined into fewer functional or physical components. In some further examples, additional functional and/or physical components may be added to the examples illustrated by
Propulsion system 902 may include components operable to provide powered motion for the vehicle 900. Depending upon the embodiment, the propulsion system 902 can include an engine/motor 918, an energy source 919, a transmission 920, and wheels/tires 921. The engine/motor 918 can be any combination of an internal combustion engine, an electric motor, steam engine, Stirling engine, or other types of engines and/or motors. In some embodiments, the engine/motor 918 may be configured to convert energy source 919 into mechanical energy. In some embodiments, the propulsion system 902 can include multiple types of engines and/or motors. For instance, a gas-electric hybrid car can include a gasoline engine and an electric motor. Other examples are possible.
Energy source 919 can represent a source of energy that may, in full or in part, power the engine/motor 918. That is, the engine/motor 918 can be configured to convert the energy source 919 into mechanical energy. Examples of energy sources 919 include gasoline, diesel, other petroleum-based fuels, propane, other compressed gas-based fuels, ethanol, solar panels, batteries, and other sources of electrical power. The energy source(s) 919 can additionally or alternatively include any combination of fuel tanks, batteries, capacitors, and/or flywheels. The energy source 919 can also provide energy for other systems of the vehicle 900.
Transmission 920 can include elements that are operable to transmit mechanical power from the engine/motor 918 to the wheels/tires 921. To this end, the transmission 920 can include a gearbox, clutch, differential, and drive shafts. The transmission 920 can include other elements. The drive shafts can include one or more axles that can be coupled to the one or more wheels/tires 921.
Wheels/tires 921 of vehicle 900 can be configured in various formats, including a unicycle, bicycle/motorcycle, tricycle, or car/truck four-wheel format. Other wheel/tire geometries are possible, such as those including six or more wheels. Any combination of the wheels/tires 921 of vehicle 900 may be operable to rotate differentially with respect to other wheels/tires 921. The wheels/tires 921 can represent at least one wheel that is fixedly attached to the transmission 920 and at least one tire coupled to a rim of the wheel that can make contact with the driving surface. The wheels/tires 921 can include any combination of metal and rubber, or another combination of materials.
Sensor system 904 may include a number of sensors configured to sense information about an environment of the vehicle 900. For example, the sensor system 904 can include a Global Positioning System (GPS) 922, an inertial measurement unit (IMU) 924, a RADAR unit 926, a laser rangefinder/LIDAR unit 928, and a camera 930. The sensor system 904 can also include sensors configured to monitor internal systems of the vehicle 900 (e.g., O2 monitor, fuel gauge, engine oil temperature). Other sensors are possible as well.
One or more of the sensors included in sensor system 904 can be configured to be actuated separately and/or collectively in order to modify a position and/or an orientation of the one or more sensors.
GPS 922 may be any sensor configured to estimate a geographic location of the vehicle 900. To this end, GPS 922 can include a transceiver operable to provide information regarding the position of the vehicle 900 with respect to the Earth.
IMU 924 can include any combination of sensors (e.g., accelerometers and gyroscopes) configured to sense position and orientation changes of the vehicle 900 based on inertial acceleration.
RADAR unit 926 may represent a system that utilizes radio signals to sense objects within the local environment of the vehicle 900. In some embodiments, in addition to sensing the objects, the RADAR unit 926 may additionally be configured to sense the speed and/or heading of the objects. Similarly, laser rangefinder or LIDAR unit 928 may be any sensor configured to sense objects in the environment in which the vehicle 900 is located using lasers. Depending upon the embodiment, the laser rangefinder/LIDAR unit 928 can include one or more laser sources, a laser scanner, and one or more detectors, among other system components. The laser rangefinder/LIDAR unit 928 can be configured to operate in a coherent (e.g., using heterodyne detection) or an incoherent detection mode.
Camera 930 can include one or more devices configured to capture a plurality of images of the environment of vehicle 900. Camera 930 can be a still camera or a video camera.
Control system 906 may be configured to control operation of vehicle 900 and its components. Accordingly, control system 906 can include various elements include steering unit 932, throttle 934, brake unit 936, a sensor fusion algorithm 938, a computer vision system 940, a navigation/pathing system 942, and an obstacle avoidance system 944.
Steering unit 932 can represent any combination of mechanisms that may be operable to adjust the heading of vehicle 900. Throttle 934 can be configured to control, for instance, the operating speed of the engine/motor 918 and, in turn, control the speed of the vehicle 900. Brake unit 936 can include any combination of mechanisms configured to decelerate the vehicle 900. Brake unit 936 can use friction to slow wheels/tires 921. In other embodiments, the brake unit 936 can convert the kinetic energy of wheels/tires 921 to electric current. The brake unit 936 may take other forms as well. The brake unit 936 may control braking of the vehicle 900, for example, using a braking algorithm that takes into account input from one or more units of the sensor system 904.
Sensor fusion algorithm 938 may be an algorithm (or a computer program product storing an algorithm) configured to accept data from the sensor system 904 as an input. The data may include, for example, data representing information sensed at the sensors of the sensor system 904. The sensor fusion algorithm 938 can include, for instance, a Kalman filter, Bayesian network, or other algorithm. The sensor fusion algorithm 938 can further provide various assessments based on the data from sensor system 904. Depending upon the embodiment, the assessments can include evaluations of individual objects and/or features in the environment of vehicle 900, evaluation of a particular situation, and/or evaluate possible impacts based on the particular situation. Other assessments are possible.
Computer vision system 940 may be any system operable to process and analyze images captured by camera 930 in order to identify objects and/or features in the environment of vehicle 900 that can include traffic signals, road way boundaries, and obstacles. Computer vision system 940 can use an object recognition algorithm, a Structure From Motion (SFM) algorithm, video tracking, and other computer vision techniques. In some embodiments, the computer vision system 940 can be additionally configured to map an environment, track objects, estimate the speed of objects, etc.
Navigation and pathing system 942 may be any system configured to determine a driving path for the vehicle 900, for example, by referencing navigation data such as geographical or map data. The navigation and pathing system 942 may additionally be configured to update the driving path dynamically while the vehicle 900 is in operation. In some embodiments, the navigation and pathing system 942 can be configured to incorporate data from the sensor fusion algorithm 938, the GPS 922, and one or more predetermined maps so as to determine the driving path for vehicle 900. Obstacle avoidance system 944 can represent a control system configured to identify, evaluate, and avoid or otherwise negotiate potential obstacles in the environment of the vehicle 900. Control system 906 may additionally or alternatively include components other than those shown and described.
Peripherals 908 may be configured to allow interaction between the vehicle 900 and external sensors, other vehicles, other computer systems, and/or a user. For example, peripherals 908 can include a wireless communication system 946, a touchscreen 948, a microphone 950, and/or a speaker 952. In an example embodiment, peripherals 908 can provide, for instance, means for a user of the vehicle 900 to interact with the user interface 916. To this end, touchscreen 948 can provide information to a user of vehicle 900. User interface 916 can also be operable to accept input from the user via the touchscreen 948. The touchscreen 948 may be configured to sense at least one of a position and a movement of a user's finger via capacitive sensing, resistance sensing, or a surface acoustic wave process, among other possibilities. Touchscreen 948 may be capable of sensing finger movement in a direction parallel or planar to the touchscreen surface, in a direction normal to the touchscreen surface, or both, and may also be capable of sensing a level of pressure applied to the touchscreen surface. Touchscreen 948 may be formed of one or more translucent or transparent insulating layers and one or more translucent or transparent conducting layers. Touchscreen 948 may take other forms as well.
In other instances, peripherals 908 may provide means for the vehicle 900 to communicate with devices within its environment. Microphone 950 may be configured to receive audio (e.g., a voice command or other audio input) from a user of vehicle 900. Similarly, speakers 952 may be configured to output audio to the user of vehicle 900.
In one example, wireless communication system 946 can be configured to wirelessly communicate with one or more devices directly or via a communication network. For example, wireless communication system 946 can use 3G cellular communication, such as CDMA, EVDO, GSM/GPRS, or 4G cellular communication, such as WiMAX or LTE. Alternatively, wireless communication system 946 can communicate with a wireless local area network (WLAN), for example, using WiFi. In some embodiments, wireless communication system 946 can communicate directly with a device, for example, using an infrared link, Bluetooth, or ZigBee. Other wireless protocols, such as various vehicular communication systems, are possible within the context of the disclosure. For example, the wireless communication system 946 can include one or more dedicated short range communications (DSRC) devices that can include public and/or private data communications between vehicles and/or roadside stations.
Power supply 910 may provide power to various components of vehicle 900 and can represent, for example, a rechargeable lithium-ion or lead-acid battery. In some embodiments, one or more banks of such batteries can be configured to provide electrical power. Other power supply materials and configurations are possible. In some embodiments, the power supply 910 and energy source 919 can be implemented together, as in some all-electric cars.
Many or all of the functions of vehicle 900 can be controlled by computer system 912. Computer system 912 may include at least one processor 913 (which can include at least one microprocessor) that executes instructions 915 stored in a non-transitory computer readable medium, such as the data storage 914. Computer system 912 may also represent a plurality of computing devices that may serve to control individual components or subsystems of the vehicle 900 in a distributed fashion.
In some embodiments, data storage 914 may contain instructions 915 (e.g., program logic) executable by processor 913 to execute various functions of vehicle 900, including those described above in connection with
Vehicle 900 may include a user interface 916 for providing information to or receiving input from a user of vehicle 900. User interface 916 can control or enable control of content and/or the layout of interactive images that can be displayed on the touchscreen 948. Further, user interface 916 can include one or more input/output devices within the set of peripherals 908, such as wireless communication system 946, touchscreen 948, microphone 950, and the speaker 952.
Port 960 may be a port through which vehicle 900 receives power to charge power supply 910 and to communicate data stored in data store 914.
Computer system 912 may control the function of vehicle 900 based on inputs received from various subsystems (e.g., propulsion system 902, sensor system 104, and control system 906), as well as from user interface 916. For example, computer system 912 may utilize input from control system 906 in order to control steering unit 932 to avoid an obstacle detected by sensor system 904 and obstacle avoidance system 944. Depending upon the embodiment, computer system 912 can be operable to provide control over many aspects of vehicle 900 and its subsystems.
The components of vehicle 900 can be configured to work in an interconnected fashion with other components within or outside their respective systems. For instance, in an example embodiment, camera 930 can capture a plurality of images that can represent information about a state of an environment of vehicle 900 operating in an autonomous or manual mode. The environment can include every conceivable type of data that can be observed and collected by vehicle 900. For example, the environment can include the road and all aspects associated with the road such as temperature, composition of the road (e.g., concrete or asphalt), moisture level, lanes, curbs, turn lanes, cross walks, stop lights, stop signs, yield signs and other traffic signs, and barricades. The environment can include objects such as other vehicles, people, random debris in or adjacent to the road.
Computer system 912 can monitor and log the environmental inputs in conjunction with operational states of the vehicle. The operational states can refer to operational and control parameters of the vehicle such as speed, trajectory, steering input, acceleration input, and brake input, and also can include results of driver input or AI driver input. This way, regardless of whether the vehicle is operating in autonomous mode or under human control, computer system 912 can simultaneously log the environmental inputs and the operational states to provide a comprehensive vehicle log.
The vehicle log data acquired from the vehicle using embodiments discussed herein can be used in a number of different ways. For example, the vehicle log data and results from either manual driving data or autonomous driving data that is contains can be used to train vehicle AI offline based on actual recorded data and actual decisions made and the results of those decisions. The vehicle log data from one vehicle may include data pertaining to hundreds, thousands, or hundreds of thousands of driving miles. Thus, the data acquired from just one vehicle is a relatively rich environment for training vehicle AI. The training data may be further enriched by aggregating vehicle log data from numerous vehicles and users, thus providing additional resources for training and improving vehicle AI. The aggregated vehicle log data can represent hundreds of thousands, millions, or an ever increasing number of trips, across various road conditions and driving situations, and the actions taken in response thereto that can be used to train the AI.
In addition, the AI training can occur offline and not during real driving conditions. This way, the vehicle AI can run simulations based on the aggregated vehicle logs to without having to actually drive the vehicle. In some embodiments, the vehicle AI may be fed road conditions and driving situations as inputs, and the results performed by the vehicle AI may be compared to the actual results stored in the log. The vehicle AI can be trained based on a comparison of the results.
The vehicle log data, which includes sensor specific data gathered during a trip as well as all of the decisions and outcomes of those decisions, can be part of the information that the vehicle AI uses to train. In some embodiments, the results of the AI training can include what sensors are needed in the vehicle (and where they are located) and what sensors are not. For example, AI training can be performed with log data having a sensor (e.g., camera) in a first location on the vehicle and a second location on the vehicle. The results of AI driving performance based on both sensor locations can be compared and decisions can be made as to which sensor configuration yields the better result. This sensor based training can be used to evaluate an infinite number of sensor configurations, and the vehicle AI can be tuned to work with one or more of those sensor configurations.
The aggregate vehicle log data may be used to provide additional information regarding the wear and tear on vehicles overall. For example, if the brakes are worn down to 30% of normal, the vehicle log data can reflect how the vehicle reacts when these brakes are applied. The vehicle AI can be trained to take wear and tear into account and can adjust vehicle operation to compensate for that wear and tear. For example, the vehicle AI may cause the brakes to be applied earlier if the brake wear is below a certain threshold.
The vehicle log data, which may contain serval gigabytes or terabytes of data, can be transferred to a remote server (not shown) for further analysis. For example, the log may be transferred from data storage 914 to data storage associated with remote server.
The remote server may include an autonomous vehicle driving platform that can apply analytics (e.g., similar to some of the examples discussed above) to the log. The autonomous vehicle driving platform (AVDP) may include one or more algorithms capable of autonomously controlling operation of a vehicle. In one embodiment, the AVDP may assess the log to determine whether any updates or modifications are needed for the one or more algorithms to improve autonomous vehicle operation. In another embodiment, the AVDP may use the log to build one or more algorithms that can autonomously control operation of a vehicle. In yet another embodiment, the AVDP run simulations using the environmental inputs received in the log and compare the simulation results to the actual monitored actions of the vehicle (which are also included in the log).
Although
It is believed that the disclosure set forth herein encompasses multiple distinct inventions with independent utility. While each of these inventions has been disclosed in its preferred form, the specific embodiments thereof as disclosed and illustrated herein are not to be considered in a limiting sense as numerous variations are possible. Each example defines an embodiment disclosed in the foregoing disclosure, but any one example does not necessarily encompass all features or combinations that may be eventually claimed. Where the description recites “a” or “a first” element or the equivalent thereof, such description includes one or more such elements, neither requiring nor excluding two or more such elements. Further, ordinal indicators, such as first, second or third, for identified elements are used to distinguish between the elements, and do not indicate a required or limited number of such elements, and do not indicate a particular position or order of such elements unless otherwise specifically stated.
Moreover, any processes described with respect to
It is to be understood that any or each module or state machine discussed herein may be provided as a software construct, firmware construct, one or more hardware components, or a combination thereof. For example, any one or more of the state machines or modules may be described in the general context of computer-executable instructions, such as program modules, that may be executed by one or more computers or other devices. Generally, a program module may include one or more routines, programs, objects, components, and/or data structures that may perform one or more particular tasks or that may implement one or more particular abstract data types. It is also to be understood that the number, configuration, functionality, and interconnection of the modules or state machines are merely illustrative, and that the number, configuration, functionality, and interconnection of existing modules may be modified or omitted, additional modules may be added, and the interconnection of certain modules may be altered.
Whereas many alterations and modifications of the present invention will no doubt become apparent to a person of ordinary skill in the art after having read the foregoing description, it is to be understood that the particular embodiments shown and described by way of illustration are in no way intended to be considered limiting. Therefore, reference to the details of the preferred embodiments is not intended to limit their scope.
This application is a continuation of U.S. application Ser. No. 16/242,567, filed Jan. 8, 2019, which claims the benefit of U.S. Provisional Application No. 62/615,280, filed Jan. 9, 2018, and U.S. Provisional Application No. 62/654,867, filed Apr. 9, 2018. The entire contents of these applications are hereby incorporated herein by reference.
Number | Name | Date | Kind |
---|---|---|---|
3897150 | Bridges et al. | Jul 1975 | A |
4412720 | Costa | Nov 1983 | A |
4464048 | Farlow | Aug 1984 | A |
4923263 | Johnson | May 1990 | A |
5006721 | Cameron et al. | Apr 1991 | A |
5157451 | Taboada | Oct 1992 | A |
5303084 | Pflibsen et al. | Apr 1994 | A |
5319434 | Croteau et al. | Jun 1994 | A |
5369661 | Yamaguchi et al. | Nov 1994 | A |
5442358 | Keeler et al. | Aug 1995 | A |
5546188 | Wangler et al. | Aug 1996 | A |
5579153 | Laming et al. | Nov 1996 | A |
5657077 | Deangelis et al. | Aug 1997 | A |
5736756 | Wakayama et al. | Apr 1998 | A |
5793491 | Wangler et al. | Aug 1998 | A |
5838239 | Stern et al. | Nov 1998 | A |
5864391 | Hosokawa et al. | Jan 1999 | A |
5926259 | Bamberger et al. | Jul 1999 | A |
5936756 | Nakajima | Aug 1999 | A |
6163378 | Khoury | Dec 2000 | A |
6175440 | Conemac | Jan 2001 | B1 |
6317202 | Hosokawa et al. | Nov 2001 | B1 |
6501586 | Takayama | Dec 2002 | B1 |
6594000 | Green et al. | Jul 2003 | B2 |
6650404 | Crawford | Nov 2003 | B1 |
6788445 | Goldberg et al. | Sep 2004 | B2 |
6788861 | Utsui et al. | Sep 2004 | B1 |
6950733 | Stopczynski | Sep 2005 | B2 |
7128267 | Reichenbach et al. | Oct 2006 | B2 |
7202941 | Munro | Apr 2007 | B2 |
7345271 | Boehlau et al. | Mar 2008 | B2 |
7382442 | Adachi et al. | Jun 2008 | B2 |
7440084 | Kane | Oct 2008 | B2 |
7440175 | Di et al. | Oct 2008 | B2 |
7489865 | Varshneya et al. | Feb 2009 | B2 |
7576837 | Liu et al. | Aug 2009 | B2 |
7583364 | Mayor et al. | Sep 2009 | B1 |
7830527 | Chen et al. | Nov 2010 | B2 |
7835068 | Brooks et al. | Nov 2010 | B1 |
7847235 | Krupkin et al. | Dec 2010 | B2 |
7869112 | Borchers et al. | Jan 2011 | B2 |
7936448 | Albuquerque et al. | May 2011 | B2 |
7969558 | Hall | Jun 2011 | B2 |
7982861 | Abshire et al. | Jul 2011 | B2 |
8072582 | Meneely | Dec 2011 | B2 |
8072663 | O'Neill et al. | Dec 2011 | B2 |
8471895 | Banks | Jun 2013 | B2 |
8736818 | Weimer et al. | May 2014 | B2 |
8749764 | Hsu | Jun 2014 | B2 |
8812149 | Doak | Aug 2014 | B2 |
8994928 | Shiraishi | Mar 2015 | B2 |
9041762 | Bai et al. | May 2015 | B2 |
9048616 | Robinson | Jun 2015 | B1 |
9065243 | Asobe et al. | Jun 2015 | B2 |
9086273 | Gruver et al. | Jul 2015 | B1 |
9194701 | Bosch | Nov 2015 | B2 |
9255790 | Zhu | Feb 2016 | B2 |
9300321 | Zalik et al. | Mar 2016 | B2 |
9304316 | Weiss et al. | Apr 2016 | B2 |
9316724 | Gehring et al. | Apr 2016 | B2 |
9354485 | Fermann et al. | May 2016 | B2 |
9368936 | Lenius et al. | Jun 2016 | B1 |
9510505 | Halloran et al. | Dec 2016 | B2 |
9575184 | Gilliland et al. | Feb 2017 | B2 |
9605998 | Nozawa | Mar 2017 | B2 |
9621876 | Federspiel | Apr 2017 | B2 |
9638799 | Goodwin et al. | May 2017 | B2 |
9696426 | Zuk | Jul 2017 | B2 |
9702966 | Batcheller et al. | Jul 2017 | B2 |
9804264 | Villeneuve et al. | Oct 2017 | B2 |
9810786 | Welford et al. | Nov 2017 | B1 |
9812838 | Villeneuve et al. | Nov 2017 | B2 |
9823353 | Eichenholz et al. | Nov 2017 | B2 |
9857468 | Eichenholz et al. | Jan 2018 | B1 |
9869754 | Campbell et al. | Jan 2018 | B1 |
9880278 | Uffelen et al. | Jan 2018 | B2 |
9880283 | Droz et al. | Jan 2018 | B2 |
9885778 | Dussan | Feb 2018 | B2 |
9897689 | Dussan | Feb 2018 | B2 |
9915726 | Bailey et al. | Mar 2018 | B2 |
9927915 | Frame et al. | Mar 2018 | B2 |
9958545 | Eichenholz et al. | May 2018 | B2 |
9989629 | LaChapelle | Jun 2018 | B1 |
10007001 | LaChapelle et al. | Jun 2018 | B1 |
10012732 | Eichenholz et al. | Jul 2018 | B2 |
10031214 | Rosenzweig et al. | Jul 2018 | B2 |
10042159 | Dussan et al. | Aug 2018 | B2 |
10061019 | Campbell et al. | Aug 2018 | B1 |
10073166 | Dussan | Sep 2018 | B2 |
10078133 | Dussan | Sep 2018 | B2 |
10084925 | LaChapelle | Oct 2018 | B2 |
10157630 | Vaughn et al. | Dec 2018 | B2 |
10191155 | Curatu | Jan 2019 | B2 |
10215847 | Scheim et al. | Feb 2019 | B2 |
10267898 | Campbell et al. | Apr 2019 | B2 |
10295656 | Li et al. | May 2019 | B1 |
10310058 | Campbell et al. | Jun 2019 | B1 |
10324170 | Enberg, Jr. et al. | Jun 2019 | B1 |
10324185 | McWhirter et al. | Jun 2019 | B2 |
10393877 | Hall et al. | Aug 2019 | B2 |
10429495 | Wang et al. | Oct 2019 | B1 |
10444356 | Wu et al. | Oct 2019 | B2 |
10451716 | Hughes et al. | Oct 2019 | B2 |
10466342 | Zhu et al. | Nov 2019 | B1 |
10502831 | Eichenholz | Dec 2019 | B2 |
10509112 | Pan | Dec 2019 | B1 |
10520602 | Villeneuve et al. | Dec 2019 | B2 |
10557923 | Watnik et al. | Feb 2020 | B2 |
10571567 | Campbell et al. | Feb 2020 | B2 |
10578720 | Hughes et al. | Mar 2020 | B2 |
10591600 | Villeneuve et al. | Mar 2020 | B2 |
10598790 | Rubin | Mar 2020 | B2 |
10627491 | Hall et al. | Apr 2020 | B2 |
10641872 | Dussan et al. | May 2020 | B2 |
10663564 | LaChapelle | May 2020 | B2 |
10663585 | McWhirter | May 2020 | B2 |
10663596 | Dussan et al. | May 2020 | B2 |
10684360 | Campbell | Jun 2020 | B2 |
10732281 | LaChapelle | Aug 2020 | B2 |
10768304 | Englard et al. | Sep 2020 | B2 |
10908262 | Dussan | Feb 2021 | B2 |
10908265 | Dussan | Feb 2021 | B2 |
10908268 | Zhou et al. | Feb 2021 | B2 |
10969475 | Li et al. | Apr 2021 | B2 |
10983218 | Hall et al. | Apr 2021 | B2 |
11002835 | Pan et al. | May 2021 | B2 |
11009605 | Li et al. | May 2021 | B2 |
11016192 | Pacala et al. | May 2021 | B2 |
11022688 | Eichenholz et al. | Jun 2021 | B2 |
11022689 | Villeneuve et al. | Jun 2021 | B2 |
11194048 | Burbank et al. | Dec 2021 | B1 |
20020136251 | Green et al. | Sep 2002 | A1 |
20040135992 | Munro | Jul 2004 | A1 |
20040222366 | Frick | Nov 2004 | A1 |
20050033497 | Stopczynski | Feb 2005 | A1 |
20050190424 | Reichenbach et al. | Sep 2005 | A1 |
20050195383 | Breed et al. | Sep 2005 | A1 |
20060071846 | Yanagisawa et al. | Apr 2006 | A1 |
20060132752 | Kane | Jun 2006 | A1 |
20060209373 | Kato | Sep 2006 | A1 |
20070091948 | Di et al. | Apr 2007 | A1 |
20070216995 | Bollond et al. | Sep 2007 | A1 |
20080174762 | Liu et al. | Jul 2008 | A1 |
20080193135 | Du et al. | Aug 2008 | A1 |
20090002678 | Tanaka et al. | Jan 2009 | A1 |
20090010644 | Varshneya et al. | Jan 2009 | A1 |
20090051926 | Chen | Feb 2009 | A1 |
20090059201 | Willner et al. | Mar 2009 | A1 |
20090067453 | Mizuuchi et al. | Mar 2009 | A1 |
20090091732 | Kato | Apr 2009 | A1 |
20090147239 | Zhu | Jun 2009 | A1 |
20090153644 | Naito | Jun 2009 | A1 |
20090262760 | Krupkin et al. | Oct 2009 | A1 |
20090316134 | Michael et al. | Dec 2009 | A1 |
20100006760 | Lee et al. | Jan 2010 | A1 |
20100020306 | Hall | Jan 2010 | A1 |
20100020377 | Borchers et al. | Jan 2010 | A1 |
20100027602 | Abshire et al. | Feb 2010 | A1 |
20100045965 | Meneely | Feb 2010 | A1 |
20100053715 | O'Neill | Mar 2010 | A1 |
20100128109 | Banks | May 2010 | A1 |
20100271614 | Albuquerque et al. | Oct 2010 | A1 |
20110063703 | Ishibe | Mar 2011 | A1 |
20110181864 | Schmitt et al. | Jul 2011 | A1 |
20120038903 | Weimer et al. | Feb 2012 | A1 |
20120124113 | Zalik et al. | May 2012 | A1 |
20120221142 | Doak | Aug 2012 | A1 |
20120260512 | Kretschmer et al. | Oct 2012 | A1 |
20130107016 | Federspeil | May 2013 | A1 |
20130116971 | Retkowski et al. | May 2013 | A1 |
20130241761 | Cooper et al. | Sep 2013 | A1 |
20130293867 | Hsu et al. | Nov 2013 | A1 |
20130293946 | Fermann et al. | Nov 2013 | A1 |
20130329279 | Nati et al. | Dec 2013 | A1 |
20130342822 | Shiraishi | Dec 2013 | A1 |
20140078514 | Zhu | Mar 2014 | A1 |
20140104594 | Gammenthaler | Apr 2014 | A1 |
20140347650 | Bosch | Nov 2014 | A1 |
20140350836 | Stettner et al. | Nov 2014 | A1 |
20150078123 | Batcheller et al. | Mar 2015 | A1 |
20150084805 | Dawber | Mar 2015 | A1 |
20150109603 | Kim et al. | Apr 2015 | A1 |
20150116692 | Zuk et al. | Apr 2015 | A1 |
20150139259 | Robinson | May 2015 | A1 |
20150158489 | Oh et al. | Jun 2015 | A1 |
20150229912 | Masalkar | Aug 2015 | A1 |
20150338270 | Williams et al. | Nov 2015 | A1 |
20150355327 | Goodwin et al. | Dec 2015 | A1 |
20160003946 | Gilliland et al. | Jan 2016 | A1 |
20160006914 | Neumann | Jan 2016 | A1 |
20160047896 | Dussan | Feb 2016 | A1 |
20160047900 | Dussan | Feb 2016 | A1 |
20160047902 | Ishikawa et al. | Feb 2016 | A1 |
20160061655 | Nozawa | Mar 2016 | A1 |
20160061935 | Mccloskey et al. | Mar 2016 | A1 |
20160100521 | Halloran et al. | Apr 2016 | A1 |
20160117048 | Frame et al. | Apr 2016 | A1 |
20160172819 | Ogaki | Jun 2016 | A1 |
20160178736 | Chung | Jun 2016 | A1 |
20160226210 | Zayhowski et al. | Aug 2016 | A1 |
20160245902 | Natnik | Aug 2016 | A1 |
20160291134 | Droz et al. | Oct 2016 | A1 |
20160313445 | Bailey et al. | Oct 2016 | A1 |
20160327646 | Scheim et al. | Nov 2016 | A1 |
20160356890 | Fried et al. | Dec 2016 | A1 |
20170003116 | Yee et al. | Jan 2017 | A1 |
20170153319 | Villeneuve et al. | Jun 2017 | A1 |
20170242104 | Dussan | Aug 2017 | A1 |
20170299721 | Eichenholz et al. | Oct 2017 | A1 |
20170307738 | Schwarz et al. | Oct 2017 | A1 |
20170365105 | Rao et al. | Dec 2017 | A1 |
20180040171 | Kundu et al. | Feb 2018 | A1 |
20180050704 | Tascione et al. | Feb 2018 | A1 |
20180059221 | Slobodyanyuk et al. | Mar 2018 | A1 |
20180059248 | O'Keeffe | Mar 2018 | A1 |
20180062345 | Bills et al. | Mar 2018 | A1 |
20180069367 | Villeneuve et al. | Mar 2018 | A1 |
20180113200 | Steinberg et al. | Apr 2018 | A1 |
20180152691 | Pacala et al. | May 2018 | A1 |
20180158471 | Vaughn et al. | Jun 2018 | A1 |
20180164439 | Droz et al. | Jun 2018 | A1 |
20180156896 | O'Keeffe | Jul 2018 | A1 |
20180188355 | Bao et al. | Jul 2018 | A1 |
20180188357 | Li et al. | Jul 2018 | A1 |
20180188358 | Li et al. | Jul 2018 | A1 |
20180188371 | Bao et al. | Jul 2018 | A1 |
20180210084 | Zwölfer et al. | Jul 2018 | A1 |
20180275274 | Bao et al. | Sep 2018 | A1 |
20180284234 | Curatu | Oct 2018 | A1 |
20180284237 | Campbell et al. | Oct 2018 | A1 |
20180284241 | Campbell et al. | Oct 2018 | A1 |
20180284242 | Campbell | Oct 2018 | A1 |
20180284286 | Eichenholz et al. | Oct 2018 | A1 |
20180286320 | Tardif et al. | Oct 2018 | A1 |
20180292532 | Meyers et al. | Oct 2018 | A1 |
20180329060 | Pacala et al. | Nov 2018 | A1 |
20180359460 | Pacala et al. | Dec 2018 | A1 |
20180364333 | Jungwirth et al. | Dec 2018 | A1 |
20190011567 | Pacala | Jan 2019 | A1 |
20190025428 | Li et al. | Jan 2019 | A1 |
20190101645 | Demersseman et al. | Apr 2019 | A1 |
20190101827 | Hansson et al. | Apr 2019 | A1 |
20190107607 | Danziger | Apr 2019 | A1 |
20190107623 | Campbell et al. | Apr 2019 | A1 |
20190120942 | Zhang et al. | Apr 2019 | A1 |
20190120962 | Gimpel et al. | Apr 2019 | A1 |
20190154804 | Eichenholz | May 2019 | A1 |
20190154807 | Steinkogler et al. | May 2019 | A1 |
20190154816 | Hughes | May 2019 | A1 |
20190180502 | Englard | Jun 2019 | A1 |
20190212416 | Li et al. | Jul 2019 | A1 |
20190250254 | Campbell et al. | Aug 2019 | A1 |
20190250270 | Suzuki et al. | Aug 2019 | A1 |
20190257924 | Li et al. | Aug 2019 | A1 |
20190265334 | Zhang et al. | Aug 2019 | A1 |
20190265336 | Zhang et al. | Aug 2019 | A1 |
20190265337 | Zhang et al. | Aug 2019 | A1 |
20190265339 | Zhang et al. | Aug 2019 | A1 |
20190277952 | Beuschel et al. | Sep 2019 | A1 |
20190310351 | Hughes et al. | Oct 2019 | A1 |
20190310368 | LaChapelle | Oct 2019 | A1 |
20190369215 | Wang et al. | Dec 2019 | A1 |
20190369258 | Hall et al. | Dec 2019 | A1 |
20190383915 | Li et al. | Dec 2019 | A1 |
20200033450 | Zhang | Jan 2020 | A1 |
20200142070 | Hall et al. | May 2020 | A1 |
20200256964 | Campbell et al. | Aug 2020 | A1 |
20200284906 | Eichenholz et al. | Sep 2020 | A1 |
20200319310 | Hall et al. | Oct 2020 | A1 |
20200400798 | Rezk et al. | Dec 2020 | A1 |
20210088630 | Zhang | Mar 2021 | A9 |
Number | Date | Country |
---|---|---|
1677050 | Oct 2005 | CN |
102084281 | Jun 2011 | CN |
202748802 | Feb 2013 | CN |
103403577 | Nov 2013 | CN |
204758260 | Nov 2015 | CN |
204885804 | Dec 2015 | CN |
108051868 | May 2018 | CN |
108132472 | Jun 2018 | CN |
207457508 | Jun 2018 | CN |
207557465 | Jun 2018 | CN |
108450025 | Aug 2018 | CN |
208314210 | Jan 2019 | CN |
208421228 | Jan 2019 | CN |
208705506 | Apr 2019 | CN |
106597471 | May 2019 | CN |
209280923 | Aug 2019 | CN |
108445468 | Nov 2019 | CN |
110031823 | Mar 2020 | CN |
108089201 | Apr 2020 | CN |
109116331 | Apr 2020 | CN |
109917408 | Apr 2020 | CN |
109116366 | May 2020 | CN |
109116367 | May 2020 | CN |
110031822 | May 2020 | CN |
211655309 | Oct 2020 | CN |
109188397 | Nov 2020 | CN |
109814086 | Nov 2020 | CN |
109917348 | Nov 2020 | CN |
110492856 | Nov 2020 | CN |
110736975 | Nov 2020 | CN |
109725320 | Dec 2020 | CN |
110780284 | Dec 2020 | CN |
110780283 | Jan 2021 | CN |
110784220 | Feb 2021 | CN |
212623082 | Feb 2021 | CN |
110492349 | Mar 2021 | CN |
109950784 | May 2021 | CN |
213182011 | May 2021 | CN |
213750313 | Jul 2021 | CN |
214151038 | Sep 2021 | CN |
109814082 | Oct 2021 | CN |
113491043 | Oct 2021 | CN |
214795200 | Nov 2021 | CN |
214795206 | Nov 2021 | CN |
214895784 | Nov 2021 | CN |
214895810 | Nov 2021 | CN |
215641806 | Jan 2022 | CN |
112639527 | Feb 2022 | CN |
215932142 | Mar 2022 | CN |
112578396 | Apr 2022 | CN |
4142702 | Jun 1993 | DE |
0 757 257 | Feb 1997 | EP |
1 237 305 | Sep 2002 | EP |
1 923 721 | May 2008 | EP |
2 157 445 | Feb 2010 | EP |
2 395 368 | Dec 2011 | EP |
2 889 642 | Jul 2015 | EP |
1 427 164 | Mar 1976 | GB |
2000411 | Jan 1979 | GB |
S628119 | Jan 1987 | JP |
H0683998 | Mar 1994 | JP |
H11194018 | Jul 1999 | JP |
2007144667 | Jun 2007 | JP |
2008298520 | Dec 2008 | JP |
2009121836 | Jun 2009 | JP |
2010035385 | Feb 2010 | JP |
2016040662 | Mar 2016 | JP |
2017-003347 | Jan 2017 | JP |
2017-138301 | Aug 2017 | JP |
10-2012-0013515 | Feb 2012 | KR |
10-2013-0068224 | Jun 2013 | KR |
10-2018-0107673 | Oct 2018 | KR |
9816801 | Apr 1998 | WO |
2012040749 | Apr 2012 | WO |
2016056545 | Apr 2016 | WO |
2017110417 | Jun 2017 | WO |
2018125725 | Jul 2018 | WO |
2018129410 | Jul 2018 | WO |
2018126248 | Jul 2018 | WO |
2018129408 | Jul 2018 | WO |
2018129409 | Jul 2018 | WO |
2018129410 | Jul 2018 | WO |
2018175990 | Sep 2018 | WO |
2018182812 | Oct 2018 | WO |
2019079642 | Apr 2019 | WO |
2019165095 | Aug 2019 | WO |
2019165289 | Aug 2019 | WO |
2019165294 | Aug 2019 | WO |
2020013890 | Jan 2020 | WO |
Entry |
---|
JP2014115182A (Year: 2014). |
Chen, X, et al. (Feb. 2010). “Polarization Coupling of Light and Optoelectronics Devices Based on Periodically Poled Lithium Niobate,” Shanghai Jiao Tong University, China, Frontiers in Guided Wave Optics and Optoelectronics, 24 pages. |
Goldstein, R. (Apr. 1986) “Electro-Optic Devices in Review, The Linear Electro-Optic (Pockels) Effect Forms the Basis for a Family of Active Devices,” Laser & Applications, FastPulse Technology, Inc., 6 pages. |
International Preliminary Report on Patentability, dated Jul. 9, 2019, for International Application No. PCT/US2018/012703, 10 pages. |
International Preliminary Report on Patentability, dated Jul. 9, 2019, for International Application No. PCT/US2018/012704, 7 pages. |
International Preliminary Report on Patentability, dated Jul. 9, 2019, for International Application No. PCT/US2018/012705, 7 pages. |
International Search Report and Written Opinion, dated Jan. 17, 2020, for International Application No. PCT/US2019/019276, 14 pages. |
International Search Report and Written Opinion, dated Jul. 9, 2019, for International Application No. PCT/US2019/018987, 17 pages. |
International Search Report and Written Opinion, dated Sep. 18, 2018, for International Application No. PCT/US2018/012116, 12 pages. |
International Search Report and Written Opinion, dated May 3, 2019, for International Application No. PCT/US2019/019272, 16 pages. |
International Search Report and Written Opinion, dated May 6, 2019, for International Application No. PCT/US2019/019264, 15 pages. |
International Search Report and Written Opinion, dated Jan. 3, 2019, for International Application No. PCT/US2018/056577, 15 pages. |
International Search Report and Written Opinion, dated Mar. 23, 2018, for International Application No. PCT/US2018/012704, 12 pages. |
International Search Report and Written Opinion, dated Jun. 7, 2018, for International Application No. PCT/US2018/024185, 9 pages. |
International Preliminary Report on Patentability, dated Apr. 30, 2020, for International Application No. PCT/US2018/056577, 8 pages. |
European Search Report, dated Jul. 17, 2020, for EP Application No. 18776977.3, 12 pages. |
Extended European Search Report, dated Jul. 10, 2020, for EP Application No. 18736738.8, 9 pages. |
Gunzung, Kim, et al. (Mar. 2, 2016). “A hybrid 3D Lidar imager based on pixel-by-pixel scanning and DS- OCDMA,” p. Proceedings of Spie [Proceedings of SPIE ISSN 0277-786X vol. 10524], SPIE, US, vol. 9751, pp. 975119-975119-8. |
Extended European Search Report, dated Jul. 22, 2020, for EP Application No. 18736685.1, 10 pages. |
Gluckman, J. (May 13, 2016). “Design of the processing chain for a high-altitude, airborne, single-photon lidar mapping instrument,” Proceedings of SPIE; [Proceedings of SPIE ISSN 0277-786X vol. 10524], SPIE, US, vol. 9832, 9 pages. |
Office Action Issued in Japanese Patent Application No. 2019-536019 dated Nov. 30, 2021, 6 pages. |
European Search Report, dated Jun. 17, 2021, for EP Application No. 18868896.4, 7 pages. |
“Fiber laser,” Wikipedia, https://en.wikipedia.org/wiki/Fiber_laser, 6 pages. |
International Search Report and Written Opinion, dated Mar. 19, 2018, for International Application No. PCT/US2018/012705, 12 pages. |
International Search Report and Written Opinion, dated Mar. 20, 2018, for International Application No. PCT/US2018/012703, 13 pages. |
“Mirrors”, Physics LibreTexts, https://phys.libretexts.org/Bookshelves/Optics/Supplemental_Modules_(Components)/Mirrors, (2021), 2 pages. |
“Why Wavelengths Matter in Fiber Optics”, FirstLight, https://www.firstlight.net/why-wavelengths-matter-in-fiber-optics/, (2021), 5 pages. |
Vuthea et al., “A Design of Risley Scanner for LiDAR Applications,” 2018 International Conference on Optical MEMS and Nanophotonics (OMN), 2 pages. |
Notice of Allowance issued in Korean Patent Application No. 10-2021-7041437, dated Apr. 28, 2022, 6 pages. |
Number | Date | Country | |
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20230087322 A1 | Mar 2023 | US |
Number | Date | Country | |
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62615280 | Jan 2018 | US |
Number | Date | Country | |
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Parent | 16242567 | Jan 2019 | US |
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