Clearpath Robotics Inc.

Other

Rockwell Automation Technologies Incorporated

James Servos

Ryan Christopher Gariepy

Shahab Kaynama

Alex Bencz

Yan Ma

Michael Irvine

Andrew Clifford Blakey

Peiyi Chen

Enrique Fernandez Perdomo

Nolan Lunscher

Simon Drexler

Matthew Lord

Yvan Geoffrey Rodrigues

Ivor Wanders

Jason Mercer

Roydyn Clayton

Jason Scharlach

Systems and methods for a stand-alone self-driving material-transport vehicle are provided. A method includes: displaying a graphical map on a graphical user-interface device based on a map stored in a storage medium of the vehicle, receiving a navigation instruction based on the graphical map, and navigating the vehicle based on the navigation instruction. As the vehicle navigates, it senses features of an industrial facility using its sensor system, and locates the features relative to the map. Subsequently, the vehicle stores the updated map including the feature on the vehicle's storage medium. The map can then be shared with other vehicles or a fleet-management system.

Stand-alone self-driving material-transport vehicle

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 operating one or more self-driving vehicles

The various embodiments described herein generally relate to an autonomous material transport vehicle, and systems and methods for operating an autonomous material transport vehicle. The autonomous material transport vehicle comprises: a sensing system operable to monitor an environment of the vehicle; a drive system for operating the vehicle; a processor operable to: receive a location of a load; initiate the drive system to navigate the vehicle to the location; following initiation of the drive system, operate the sensing system to monitor for one or more objects within a detection range; and in response to the sensing system detecting the one or more objects within the detection range, determine whether the load is within the detection range; and when the load is within the detection range, operate the drive system to position the vehicle for transporting the load, otherwise, determine a collision avoidance operation to avoid the one or more objects.

Autonomous material transport vehicles, and systems and methods of operating thereof

Systems and methods for updating an electronic map of a facility are disclosed. The electronic map includes a set of map nodes. Each map node has a stored image data associated with a position within the facility. The method includes collecting image data at a current position of a self-driving material-transport vehicle; searching the electronic map for at least one of a map node associated with the current position and one or more neighboring map nodes within a neighbor threshold to the current position; comparing the collected image data with the stored image data of the at least one of the map node and the one or more neighboring map nodes to determine a dissimilarity level. The electronic map may be updated based at least on the collected image data and the dissimilarity level. The image data represents one or more features observable from the current position.

Systems and methods for updating an electronic map

A system for path control for a mobile unmanned vehicle in an environment is provided. The system includes: a sensor connected to the mobile unmanned vehicle; the mobile unmanned vehicle configured to initiate a first fail-safe routine responsive to detection of an object in a first sensor region adjacent to the sensor; and a processor connected to the mobile unmanned vehicle. The processor is configured to: generate a current path based on a map of the environment; based on the current path, issue velocity commands to cause the mobile unmanned vehicle to execute the current path; responsive to detection of an obstacle in a second sensor region, initiate a second fail-safe routine in the mobile unmanned vehicle to avoid entry of the obstacle into the first sensor region and initiation of the first fail-safe routine.

Method, system and apparatus for self-driving vehicle obstacle avoidance

Systems, methods and apparatus are provided for handling operational constraints for unmanned vehicles. The system includes: a plurality of mobile unmanned vehicles for deployment in an environment; a computing device connected to the plurality of unmanned vehicles via a network, the computing device storing, in a memory, a plurality of operational constraints; each operational constraint including (i) a type identifier, (ii) an indication of a region of the environment, and (iii) a property defining a constraint on the operation of the unmanned vehicles within the region. The computing device is configured to: receive a request from one of the mobile unmanned vehicles, the request identifying an operational constraint; responsive to receiving the request, retrieve an operational constraint from the memory based on the request; and send the retrieved operational constraint to the one of the mobile unmanned vehicles.

Method, system and apparatus for handling operational constraints for control of unmanned vehicles

Systems and methods for obstacle avoidance with a self-driving vehicle are provided. The system comprises a processor connected to the self-driving vehicle and a sensor in communication with the processor. The sensor is configured to detect objects. The processor is configured to receive a measurement of the self-driving vehicle's speed, and define a sensor region based on the speed. The processor can determine that an object detected by the sensor is within the sensor region, and then initiate a fail-safe routine. The sensor region may be defined based on a range parameter. The sensor region may be defined based on the stopping distance of the vehicle. The sensor region may be redefined when the vehicle's speed changes.

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Kitchener, Canada

James Servos