Clearpath Robotics Inc.

Various systems and methods for collision avoidance for autonomous mobile robots operating within a facility using short-range position sharing are disclosed herein. The systems and methods involve a first autonomous mobile robot broadcasting a low power presence signal via a short-range communication protocol, detecting a response signal from a second autonomous mobile robot and transmitting to the second autonomous mobile robot, a state signal including at least a current position and a current velocity of the first autonomous mobile robot. The second autonomous mobile robot determines its future positions along its trajectory and modifies its trajectory in response to determining a risk of collision, based on its future positions and predicted future positions of the first autonomous mobile robot. The predicted future positions are determined based at least on the current position and the current velocity of the first autonomous mobile robot.

Systems and methods for providing distributed computation among a plurality of industrial edge devices are provided. A method includes operating a virtual orchestrator in communication with the plurality of industrial edge devices to: receive one or more computational tasks; monitor a current computational capacity at the plurality of industrial edge devices to predict availability of computational capacity at each industrial edge device; project a future computational capacity at the plurality of industrial edge devices; identify available computational capacity for the one or more computational tasks based on the current computational capacity and the future computational capacity; for each computational task, determine a network bandwidth requirement for completing the computational task at one or more industrial edge devices; and allocate the one or more computational tasks among the industrial edge devices according to the available computational capacity and a network bandwidth efficiency based on the determined network bandwidth requirement.

Systems and methods for operating a mobile robot is disclosed. The system can include a pair of stereo imaging devices mounted on the mobile robot, a memory storing a current baseline, and a processor. The pair of stereo imaging devices include a first and a second imaging device. The current baseline is representative of a distance between the first and the second imaging devices. The processor is operable to: autonomously navigate the mobile robot to a visual target; while the visual target is within viewing range, capture an image of the visual target; generate a plurality of depth measurements from the image; compare the plurality of depth measurements with corresponding depth estimates; and update the current baseline based on the comparisons. The mobile robot is operable to autonomously execute a mission within an environment; and while executing the mission, use the current baseline for sensing the environment.

A method and system are provided for characterizing a vehicle motion of an autonomous mobile robot in response to a triggering event. The method and system involve an autonomous mobile robot and a vehicle processor operable to navigate the autonomous mobile robot. The system further includes a motion characterization system coupled to the autonomous mobile robot, the motion characterization system comprising an odometry system operable to collect vehicle motion data associated with the vehicle motion; a triggering component; a storage component for storing an event start time, an event end time and the vehicle motion data between the event start time and the event end time; and a motion characterization processor operable to: receive an initialization input to initiate the triggering event; generate a trigger signal to cause the triggering component to cause the triggering event; and identify the event start time and an event end time.

Systems and methods for autonomous lineside delivery to an assembly-line using a self-driving vehicle are disclosed, comprising receiving a part-supply schedule having a part identifier identifying a part to be supplied, an assembly-line location to be supplied with the part, and a delivery time for supplying the part to the assembly-line location. A mission is generated based on the schedule, and sent to a self-driving vehicle. The self-driving vehicle executes the mission such that the part is supplied to the assembly-line location in accordance with the part-supply schedule.

Systems and methods for autonomous lineside delivery to an assembly-line using a self-driving vehicle are disclosed, comprising receiving a part-supply schedule having a part identifier identifying a part to be supplied, an assembly-line location to be supplied with the part, and a delivery time for supplying the part to the assembly-line location. A mission is generated based on the schedule, and sent to a self-driving vehicle. The self-driving vehicle executes the mission such that the part is supplied to the assembly-line location in accordance with the part-supply schedule.

There is provided a driver-support system for use with a human-operated material-transport vehicle, and methods for using the same. The system has at least one sensor, a human-vehicle interface, and a transceiver for communicating with a fleet-management system. The system also has a processor that is configured to provide a mapping application and a localization application based on information received from the sensor. The mapping application and localization application may be provided in a single localization-and-mapping (“SLAM”) application, which may obtain input from the sensor, for example, when the sensor is an optical sensor such as a LIDAR or video camera.

Systems and methods for autonomous lineside delivery to an assembly-line using a self-driving vehicle are disclosed, comprising receiving a part-supply schedule having a part identifier identifying a part to be supplied, an assembly-line location to be supplied with the part, and a delivery time for supplying the part to the assembly-line location. A mission is generated based on the schedule, and sent to a self-driving vehicle. The self-driving vehicle executes the mission such that the part is supplied to the assembly-line location in accordance with the part-supply schedule.

The various embodiments described herein generally relate to systems and methods for operating one or more self-driving vehicles. In some embodiments, the self-driving vehicles may include a vehicle processor being operable to: control the vehicle to navigate an operating environment in an initial vehicle navigation mode; monitor for one or more trigger conditions indicating a possible change for the vehicle navigation mode; detect a trigger condition; determine a prospective vehicle navigation mode associated with the detected trigger condition; determine whether to change from the initial vehicle navigation mode to the prospective vehicle navigation mode; and in response to determining to change from the initial vehicle navigation mode to the prospective vehicle navigation mode, adjust one or more vehicle attributes corresponding to the prospective vehicle navigation mode, otherwise continue to operate the vehicle in the initial vehicle navigation mode.

Systems and methods for providing inter-vehicle communication are disclosed. The method includes receiving, at a fleet management system, operating data from one or more self-driving vehicles via a communication network, and operating the fleet management system to determine a characteristic of a set of vehicles of one or more self-driving vehicles satisfies at least one communication condition. In response to determining the set of vehicles satisfies the at least one communication condition, the fleet management system can operate to select a stored data portion from a manager storage unit based at least on the characteristic of the set of vehicles; and transmit the data portion to the set of vehicles via the communication network. A method of providing inter-vehicle communication between one or more self-driving vehicles is also disclosed.