Patent Application
20240142984
Autonomous or semi-autonomous mobile robots can be deployed in facilities such as warehouses, manufacturing facilities, healthcare facilities, or the like, e.g., to transport items within the relevant facility. To navigate a facility, a mobile robot may generate a path through the facility based on a previously generated map of the facility, e.g., indicating the locations of various obstacles in the facility. The location of obstacles may change over time, however, rendering the map less accurate, which may impede navigation by the mobile robots.
The accompanying figures, where like reference numerals refer to identical or functionally similar elements throughout the separate views, together with the detailed description below, are incorporated in and form part of the specification, and serve to further illustrate embodiments of concepts that include the claimed invention, and explain various principles and advantages of those embodiments.
Skilled artisans will appreciate that elements in the figures are illustrated for simplicity and clarity and have not necessarily been drawn to scale. For example, the dimensions of some of the elements in the figures may be exaggerated relative to other elements to help to improve understanding of embodiments of the present invention.
The apparatus and method components have been represented where appropriate by conventional symbols in the drawings, showing only those specific details that are pertinent to understanding the embodiments of the present invention so as not to obscure the disclosure with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein.
Examples disclosed herein are directed to a method in a computing device including: storing an initial map representing objects within a facility; receiving sensor data from a mobile robot deployed in the facility, the sensor data representing a portion of the facility within a field of view of the mobile robot; determining, based on the received sensor data, whether a map update criterion is satisfied; in response to determining that the map update criterion is satisfied, generating a map update representing updated objects within the facility; applying the map update to the initial map to generate an updated map; and storing the updated map.
Additional examples disclosed herein are directed to a computing device, comprising: a memory storing an initial map representing objects within a facility; and a processor configured to: receive sensor data from a mobile robot deployed in the facility, the sensor data representing a portion of the facility within a field of view of the mobile robot; determine, based on the received sensor data, whether a map update criterion is satisfied; in response to determining that the map update criterion is satisfied, generate a map update representing updated objects within the facility; apply the map update to the initial map to generate an updated map; and store the updated map in the memory.
In other examples, the facility 100 can include fewer aisles 112 than shown, or more aisles 112 than shown in
The items 108 may be handled according to a wide variety of processes, depending on the nature of the facility 100. In some examples, the facility 100 is a shipping facility, distribution facility, or the like, and the items 108 can be placed on the support structures 104 for storage, and subsequently retrieved for shipping from the facility. Placement and/or retrieval of the items 108 to and/or from the support structures can be performed or assisted by mobile robots 120-1 and 120-2. A greater number of robots 120 can be deployed in the facility 100 than the two robots 120 shown in
Each robot 120 can be configured to track its pose (e.g., location and orientation) within the facility 100, e.g., in a coordinate system 124 previously established in the facility 100. The robots 120 can navigate autonomously within the facility 100, e.g., travelling to assigned locations to receive and/or deposit items 108. The items 108 can be deposited into or onto the robots 120, and removed from the robots 120, by human workers and/or mechanized equipment such as robotic arms and the like deployed in the facility 100. The locations to which each robot 120 navigates can be assigned to the robots 120 by a central server 128. That is, the server 128 is configured to assign tasks to the robots 120. Each task can include either or both of one or more locations to travel to, and one or more actions to perform at those locations. For example, the server 128 can assign a task to the robot 120-1 to travel to a location defined in the coordinate system 124, and to await the receipt of one or more items 108 at that location.
Tasks can be assigned to the robots via the exchange of messages between the server 128 and the robots 120, e.g., over a suitable combination of local and wide-area networks implementing communications links 130-1, 130-2 with the robots 120. The server 128 can be deployed at the facility 100, or remotely from the facility 100. In some examples, the server 128 is configured to assign tasks to robots 120 at multiple facilities, and need not be physically located in any of the individual facilities.
To navigate to a given location in the facility 100 (e.g., a target location assigned to a mobile robot 120 by the server 128), a robot 120 can generate a path through the facility from its current pose to the target location. The path is generated based on a map of the facility, e.g., stored in a repository 132 at the server 128. Each robot 120 can, for example, periodically obtain a copy of the map from the server 128 for local storage and use in navigational functions such as path generation. The map stored at the server 128 represents objects within the facility 100, but generally does not represent all objects in the facility 100. Rather, the map represents permanent or semi-permanent objects (e.g., static objects that are not relocated, or are relocated infrequently) such as walls, doorways, the support structures 104, and the like. Each robot 120 can also maintain a local map of transient obstacles observed via sensor data, and can consult both maps to generate and execute navigational paths.
Although the objects represented in the “master” map at the server 132 may be relocated infrequently, when they are relocated, or when such objects are removed or added to the facility, the map in the repository 132 may become outdated. The robots 120 may therefore be provided with outdated map data by the server 128, and may therefore become mislocalized and/or generate navigational paths that intersect with objects located in previously empty space.
Updating the map at the server 128, e.g., in response to relocating a support structure 104, may be performed by manual editing of the map, but manual editing is error-prone and may be as likely to lead to navigational errors as the previous (outdated) map. The server 128 is therefore configured, as discussed below, to implement certain functions to evaluate sensor data from the robots 120 and update the map at least partially automatically.
Before discussing the functionality implemented by the robot 120 in greater detail, certain components of the server 128 are discussed in connection with
As shown in
The server 128 can further include an output device such as a display 146, and an input device 148, such as a touch screen integrated with the display 146, a keyboard and mouse, or the like. The display 146 is controllable by the processor 134 to render various information thereon, and the input device 148 receives input from an operator of the server 128 such as a worker 150 in the facility 100, and provides data representing such input to the processor 134. The display 146 and input device 148 are illustrated as components of the server 128 for simplicity, but can also be implemented as components of another computing device distinct from the server 128 and connected with the server 128 via a the previously mentioned networks. For example, the other computing device can execute a web browser application to communicate with the server 128 and receive data therefrom for presentation on the display 146.
Turning to
The chassis 200 also supports receptacles, shelves, or the like, to support items 108 during transport. For example, the robot 120 can include a selectable combination of receptacles 212. In the illustrated example, the chassis 200 supports a rack 208, e.g., including rails or other structural features configured to support receptacles 212 at variable heights above the chassis 200. The receptacles 212 can therefore be installed and removed to and from the rack 208, enabling distinct combinations of receptacles 212 to be supported by the robot 120.
The robot 120 can also include an output device, such as a display 216. In the illustrated example, the display 216 is mounted above the rack 208, but it will be apparent that the display 216 can be disposed elsewhere on the robot 120 in other examples. The display 216 can include an integrated touch screen or other input device, in some examples, The robot 120 can also include other output devices in addition to or instead of the display 216. For example, the robot 120 can include one or more speakers, light emitters such as strips of light-emitting diodes (LEDs) along the rack 208, and the like.
The chassis 200 of the robot 120 also supports various other components, including a processor 220, e.g., one or more central processing units (CPUs), graphics processing units (GPUs), or dedicated hardware controllers such as application specific integrated circuits (ASICs). The processor 220 is communicatively coupled with a non-transitory computer readable medium such as a memory 224, e.g., a suitable combination of volatile and non-volatile memory elements. The processor 220 is also coupled with a communications interface 228, such as a wireless transceiver enabling the robot 120 to communicate with other computing devices, such as the server 128 and other robots 120. The communications interface 228 can also include, in some examples, a wired interface such as a Universal Serial Bus (USB) controller and one or more USB ports, or the like.
The memory 224 stores various data used for autonomous or semi-autonomous navigation, including an application 232 executable by the processor 220 to implement navigational and other task execution functions. In some examples, the above functions can be implemented via multiple distinct applications stored in the memory 224.
The chassis 200 can also support a sensor 240, such as one or more cameras and/or depth sensors (e.g., lidars, depth cameras, time-of-flight cameras, or the like) coupled with the processor 220. The sensor(s) 240 are configured to capture image and/or depth data depicting at least a portion of the physical environment of the robot 120. Data captured by the sensor(s) 240 can by used by the processor 220 for navigational purposes, e.g., path planning, obstacle avoidance, and the like, as well as for updating a map of the facility in some examples.
The sensors 240 have respective fields of view (FOVs). For example, a first FOV 242a corresponds to a laser scanner, such as a lidar sensor disposed on a forward-facing surface of the chassis 200. The FOV 242a can be substantially two-dimensional, e.g., extending forwards in a substantially horizontal plane. A second FOV 242b corresponds to a camera (e.g., a depth camera, a color camera, or the like) also mounted on the forward-facing surface of the chassis 200. As will be apparent, a wide variety of other optical sensors can be disposed on the chassis 200 and/or the rack 208, with respective FOVs 242.
The components of the robot 120 that consume electrical power can be supplied with such power from a battery 244, e.g., implemented as one or more rechargeable batteries housed in the chassis 200 and rechargeable via a charging port (not shown) or other suitable charging interface.
Turning to
The performance of the method 300 involves the collection of sensor data at the server 128 from one or more of the robots 120, and the processing of the collected sensor data to update the map of the facility 100 stored at the server 128. The sensor data can be collected from mobile robots 120 operating autonomously, e.g., to complete tasks assigned to the robots 120 by the server 128. The sensor data can also, in some examples, be collected from mobile robots 120 operating in a piloted mode, in which a human operator such as the worker 150 directs the movements of a robot 120. Blocks 305a and 305b can optionally be performed to initiate data collection using the piloted mode. In the present example performance of the method 300, blocks 305a and 305b are omitted, and sensor data is collected from robots 120 operating autonomously. Blocks 305a and 305b are discussed in greater detail further below.
At block 305, the server 128 is configured to receive sensor data from one or more robots 120. The sensor data received at block 305 can include raw sensor data from the robots 120, such as point cloud data captured via cameras and/or laser scanners. The processor 220 of the robot 120, in other words, can be configured to control the sensors(s) 240 to capture sensor data, and can then transmit the sensor data to the server 128 via the communications interface 228. In other examples, the sensor data is received as local map data, as mentioned above, e.g., in the form of images generated at the robots 120 from sensor data. The sensor data received at block 305 also includes a pose of the robot 120 that captured the sensor data, and a timestamp indicating when the sensor data was captured. The robots 120 can be configured to periodically transmit sensor data to the server 128 during the execution of tasks assigned by the server 128. More generally, at block 305 the server 128 receives, from the robots 120, current observations representing the surroundings of the robots 120.
At block 310, having received sensor data from at least one of the robots 120, the server 128 is configured to determine whether the received sensor data (as well as any previously received and stored sensor data) satisfies one or more update criteria stored at the server 128. The update criteria define conditions that, if satisfied, indicate a mismatch between objects observed in the facility 100 by the robots 120, and objects represented in the current map stored in the repository 132. In other words, when the update criteria are satisfied, the physical layout of the facility 100 is likely to have changed sufficiently that the initial map in the repository 132 is outdated.
Turning to
A current pose of the robot 120-1 is illustrated on the map 400. As will be apparent to those skilled in the art, the pose of the robot 120-1 need not be stored within the map 400, but can be periodically reported to the server 128 by the robot 120-1 and stored in the memory 136.
As noted above, in response to receiving the sensor data, at block 310 the server 128 is configured to determine whether update criteria are met for any portion of the facility 100 represented in the sensor data. The determination at block 310 can include, for example, determining locations (in the coordinate system 124) of objects represented in the map 400, and the locations of objects represented in the sensor data 408, and determining distances between pairs of such objects (or more generally, between pairs of occupied regions). An update criterion can include a threshold distance between such objects, such that objects separated by less than the threshold distance do not meet the update criterion, while objects separated by more than the threshold distance meet the update criterion. A wide variety of other update criteria are also contemplated, including measuring a degree of overlap between objects in the sensor data 408 and the map 400 (with an affirmative determination at block 310 requiring an overlap below a threshold).
For example, turning to
Turning to
Further example update criteria evaluated at block 328 include determining whether a number of instances of sensor data representing matching sets of objects exceeds a consensus threshold. The instances of sensor data may also be required to occur over at least a predetermined time period. For example, if at least three distinct sets of sensor data, spanning a capture time period of at least four days, represent one or more matching objects and those matching objects do not match the map 400, the determination at block 310 is affirmative. In this example, the sensor data sets 600 all show the new position of the support structure 104a. The sensor data 600-2 also shows another object 604, but the determination at block 310 is negative in connection with the object 604, as no other sensor data set 600 contains the object 604. The object 604 is therefore likely to be transient, rather than a static object eligible for insertion into the map 400.
When the determination at block 310 is affirmative, as in the example of
In some examples, the processor 220 of a robot 120 can perform blocks 305, 310, and 315, e.g., based on locally captured and processed sensor data. The consensus-based criteria mentioned above may be limited to repeated observations of an occupied region of the facility 100 by that robot 120, in such examples. The map update generated at block 315 can, for example, be transmitted to the server 128 for approval or rejection at block 320.
At block 320, the server 128 is configured to determine whether the proposed update, e.g., presented in the notification 700, has been accepted. Prior to the determination at block 320, the update generated at block 315 is not applied to the map 400, but can instead be stored as a separate draft map, or simply as the portion 708 in isolation. When the determination at block 320 is negative (e.g., the element 716 in
When the determination at block 320 is affirmative, e.g., in response to selection of the element 712 in
Turning to
Referring again to
In addition, the server 128 can render indicators such as navigational errors 912 on the map that was current when the navigational errors 912 were detected (e.g., by receipt at the server 128 from one or more robots 120). Displaying navigational errors 912 or other indicators in the time lapse interface may assist operators in detecting and correcting mapping issues, such as the fact that the updated map 800 shown in the lower portion includes a virtual lane 404 that now intersects with an object, which may be associated with an increased incidence of navigational errors.
Returning to
In response to receiving the above command from the server 128, the robot 120-2 ceases autonomous navigation, and awaits manual control commands. The worker 150 can, for example, connect a controller (e.g., a video game controller or the like) to the communications interface 228 via Bluetooth, a USB dongle, or the like. The worker 150 can then directly control the path of the mobile robot 120-2. As the robot 120-2 travels under the control of the worker 150, the robot 120-2 captures sensor data and transmits the sensor data to the server 128, which receives the sensor data as described above in connection with block 305.
When the sensor data received at block 305 is received from a robot 120 under manual control, the determination at block 310 is affirmative. For example, the determination at block 310 can be omitted when the piloted mode is active, or an update criterion can be configured to determine whether the sensor data was received from a robot 120 in the piloted mode. As will be apparent, the consensus-based features discussed earlier (e.g., a given feature in the facility 100 being observed by a number of robots 120 over a period of time) can therefore be bypassed. The server 128 is therefore configured to proceed to block 315, and generate a proposed update, based on the sensor data from block 305. The server 128 can be configured to present the proposed update on the display 146, e.g., in real time as the robot 120-2 is piloted within the facility 100, enabling the worker 150 or other staff to monitor sensor data collection.
For example, turning to
At block 320, e.g., in response to completion of the piloting of the robot 120-2 (e.g., as indicated by further input data from the input device 148 defining a command to release the robot 120-2 from the piloted mode, the server 128 can be configured to present an interface similar to that shown in
The functionality implemented by the server 128 thus enables updating maps for the facility 100 in an at least partially automated manner, avoiding the potential for erroneous edits to the maps that may result from manual updating.
In the foregoing specification, specific embodiments have been described. However, one of ordinary skill in the art appreciates that various modifications and changes can be made without departing from the scope of the invention as set forth in the claims below. Accordingly, the specification and figures are to be regarded in an illustrative rather than a restrictive sense, and all such modifications are intended to be included within the scope of present teachings.
The benefits, advantages, solutions to problems, and any element(s) that may cause any benefit, advantage, or solution to occur or become more pronounced are not to be construed as a critical, required, or essential features or elements of any or all the claims. The invention is defined solely by the appended claims including any amendments made during the pendency of this application and all equivalents of those claims as issued.
Moreover in this document, relational terms such as first and second, top and bottom, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. The terms “comprises,” “comprising,” “has”, “having,” “includes”, “including,” “contains”, “containing” or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises, has, includes, contains a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by “comprises . . . a”, “has . . . a”, “includes . . . a”, “contains . . . a” does not, without more constraints, preclude the existence of additional identical elements in the process, method, article, or apparatus that comprises, has, includes, contains the element. The terms “a” and “an” are defined as one or more unless explicitly stated otherwise herein. The terms “substantially”, “essentially”, “approximately”, “about” or any other version thereof, are defined as being close to as understood by one of ordinary skill in the art, and in one non-limiting embodiment the term is defined to be within 10%, in another embodiment within 5%, in another embodiment within 1% and in another embodiment within 0.5%. The term “coupled” as used herein is defined as connected, although not necessarily directly and not necessarily mechanically. A device or structure that is “configured” in a certain way is configured in at least that way, but may also be configured in ways that are not listed.
Certain expressions may be employed herein to list combinations of elements. Examples of such expressions include: “at least one of A, B, and C”; “one or more of A, B, and C”; “at least one of A, B, or C”; “one or more of A, B, or C”. Unless expressly indicated otherwise, the above expressions encompass any combination of A and/or B and/or C.
It will be appreciated that some embodiments may be comprised of one or more specialized processors (or “processing devices”) such as microprocessors, digital signal processors, customized processors and field programmable gate arrays (FPGAs) and unique stored program instructions (including both software and firmware) that control the one or more processors to implement, in conjunction with certain non-processor circuits, some, most, or all of the functions of the method and/or apparatus described herein. Alternatively, some or all functions could be implemented by a state machine that has no stored program instructions, or in one or more application specific integrated circuits (ASICs), in which each function or some combinations of certain of the functions are implemented as custom logic. Of course, a combination of the two approaches could be used.
Moreover, an embodiment can be implemented as a computer-readable storage medium having computer readable code stored thereon for programming a computer (e.g., comprising a processor) to perform a method as described and claimed herein. Examples of such computer-readable storage mediums include, but are not limited to, a hard disk, a CD-ROM, an optical storage device, a magnetic storage device, a ROM (Read Only Memory), a PROM (Programmable Read Only Memory), an EPROM (Erasable Programmable Read Only Memory), an EEPROM (Electrically Erasable Programmable Read Only Memory) and a Flash memory. Further, it is expected that one of ordinary skill, notwithstanding possibly significant effort and many design choices motivated by, for example, available time, current technology, and economic considerations, when guided by the concepts and principles disclosed herein will be readily capable of generating such software instructions and programs and ICs with minimal experimentation.
The Abstract of the Disclosure is provided to allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing Detailed Description, it can be seen that various features are grouped together in various embodiments for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separately claimed subject matter.
