Abstract: Systems and methods for autonomous provision replenishment are disclosed. Parts used in a manufacturing process are stored in an intermediate stock queue. When the parts are consumed by the manufacturing process and the number of parts in the queue falls below a threshold, a provision-replenishment signal is generated. One or more self-driving material-transport vehicles, a fleet-management system, and a provision-notification device.

Abstract: Systems and methods for flexible conveyance in an assembly-line or manufacturing process are disclosed. A fleet of self-driving vehicles and a fleet-management system can be used to convey workpieces through a sequence of workstations at which operations are performed in order to produce a finished assembly. An assembly can be transported to a first workstation using a self-driving vehicle, where an operation is performed on the assembly. Subsequently, the assembly can be transported to a second workstation using the self-driving vehicle. The operation can be performed on the assembly while it is being conveyed by the self-driving vehicle.

Abstract: 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.

Abstract: A system, method and apparatus for executing tasks with unmanned vehicles is provided. The system includes an unmanned vehicle comprising: a chassis; a propulsion system configured to move the chassis; sensor(s) configured to sense features around the chassis; a memory storing feature reference data; a communication interface; and a processor configured to: receive, using the interface, a command having task data and a location associated with a given feature; control the propulsion system to move the chassis to the location; while the chassis is moving to the location, determine, using the sensor(s), that the given feature is detected based on the feature reference data; and, responsive to the given feature being detected, control the propulsion system to execute a task based on the task data.

Abstract: Systems and methods for flexible conveyance in an assembly-line or manufacturing process are disclosed. A fleet of self-driving vehicles and a fleet-management system can be used to convey workpieces through a sequence of workstations at which operations are performed in order to produce a finished assembly. An assembly can be transported to a first workstation using a self-driving vehicle, where an operation is performed on the assembly. Subsequently, the assembly can be transported to a second workstation using the self-driving vehicle. The operation can be performed on the assembly while it is being conveyed by the self-driving vehicle.

Abstract: A system for remote viewing and control of self-driving vehicles includes: an execution subsystem for deployment at an execution location containing a self-driving vehicle. The execution subsystem includes: a capture assembly to capture multimedia data depicting the execution location, and a server to receive the multimedia data and transmit the multimedia data for presentation at an operator location remote from the execution location. The server relays operational commands and operational status data between the self-driving vehicle and the operator location. The system includes an operator subsystem for deployment at the operator location, including: a display assembly, and a computing device to: (a) establish a connection with the server; (b) receive the multimedia data from the server and control the display assembly to present the multimedia data; and (c) receive control commands and transmit the control commands to the server for execution by the self-driving vehicle.

Abstract: 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.

Abstract: Systems and methods for monitoring a fleet of self-driving vehicles are disclosed. The system comprises one or more self-driving vehicles having at least one sensor for collecting current state information, a fleet-management system, and computer-readable media for storing reference data. The method comprises autonomously navigating a self-driving vehicle in an environment, collecting current state information using the vehicle's sensor, comparing the current state information with the reference data, identifying outlier data in the current state information, and generating an alert based on the outlier data. A notification based on the alert may be sent to one or more monitoring devices according to the type and severity of the outlier.

Abstract: Systems and methods for process tending with a robot arm are presented. The system comprises a robot arm and robot arm control system mounted on a self-driving vehicle, and a server in communication with the vehicle and/or robot arm control system. The vehicle has a vehicle control system for storing a map and receiving a waypoint based on a process location provided by the server. The robot arm control system stores at programs that is executable by the robot arm. The vehicle control system autonomously navigates the vehicle to the waypoint based on the map, and the robot arm control system selects a target program from the stored programs based on the process location and/or a process identifier.

Abstract: Systems and methods for autonomous provision replenishment are disclosed. Parts used in a manufacturing process are stored in an intermediate stock queue. When the parts are consumed by the manufacturing process and the number of parts in the queue falls below a threshold, a provision-replenishment signal is generated. One or more self-driving material-transport vehicles, a fleet-management system, and a provision-notification device.

Abstract: A system, method and apparatus for executing tasks with unmanned vehicles is provided. The system includes an unmanned vehicle comprising: a chassis; a propulsion system configured to move the chassis; sensor(s) configured to sense features around the chassis; a memory storing feature reference data; a communication interface; and a processor configured to: receive, using the interface, a command having task data and a location associated with a given feature; control the propulsion system to move the chassis to the location; while the chassis is moving to the location, determine, using the sensor(s), that the given feature is detected based on the feature reference data; and, responsive to the given feature being detected, control the propulsion system to execute a task based on the task data.

Abstract: Systems and methods for flexible conveyance in an assembly-line or manufacturing process are disclosed. A fleet of self-driving vehicles and a fleet-management system can be used to convey workpieces through a sequence of workstations at which operations are performed in order to produce a finished assembly. An assembly can be transported to a first workstation using a self-driving vehicle, where an operation is performed on the assembly. Subsequently, the assembly can be transported to a second workstation using the self-driving vehicle. The operation can be performed on the assembly while it is being conveyed by the self-driving vehicle.

Abstract: 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.

Abstract: Systems and methods for self-driving collision prevention are presented. The system comprises a self-driving vehicle safety system, having one or more sensors in communication with a control system. The control system is configured determine safety fields and instruct the sensors to scan a region corresponding to the safety fields. The control system determines exclusion regions, and omits the exclusion regions from the safety field. The safety system may also include capability reduction parameters that can be used to constrain the drive system of the vehicle, for example, by restricting turning radius and speed in accordance with the safety fields.

Abstract: Systems and methods for operating robotic equipment in a controlled zone are presented. The system comprises one or more self-driving material-transport vehicles having at least one sensor, non-transitory computer-readable media, and a processor in communication with the at least one sensor and media. The media stores computer instructions that configure the processor to move the vehicle towards the controlled zone in a normal mode of operation, capture environmental data associated with the controlled zone using the at least one sensor, determine environmental-change data based on comparing the captured environmental data with known-good environmental data, and operating the vehicle in a safe mode of operation based on the environmental-change data.

Abstract: Systems and methods for process tending with a robot arm are presented. The system comprises a robot arm and robot arm control system mounted on a self-driving vehicle, and a server in communication with the vehicle and/or robot arm control system. The vehicle has a vehicle control system for storing a map and receiving a waypoint based on a process location provided by the server. The robot arm control system stores at programs that is executable by the robot arm. The vehicle control system autonomously navigates the vehicle to the waypoint based on the map, and the robot arm control system selects a target program from the stored programs based on the process location and/or a process identifier.

Abstract: Systems and methods for operating robotic equipment in a controlled zone are presented. The system comprises one or more self-driving material-transport vehicles having at least one sensor, non-transitory computer-readable media, and a processor in communication with the at least one sensor and media. The media stores computer instructions that configure the processor to move the vehicle towards the controlled zone in a normal mode of operation, capture environmental data associated with the controlled zone using the at least one sensor, determine environmental-change data based on comparing the captured environmental data with known-good environmental data, and operating the vehicle in a safe mode of operation based on the environmental-change data.

Abstract: 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.

Abstract: Systems and methods for WiFi mapping an industrial facility are disclosed. The system comprises a self-driving vehicle having a WiFi transceiver. The self-driving vehicle communicates with a fleet-management using the WiFi transceiver, via a WiFi access point. The self-driving vehicle receives a mission from the fleet-management system, and moves to a destination location based on the mission, using autonomous navigation. While executing the mission, the self-driving vehicle simultaneously measures the received signal strength indication of the WiFi access point and other WiFi access points in the facility, and stores the received signal strength indication in association with the location at which the received signal strength indication was measured.

Abstract: A system for controlling a fleet of unmanned vehicles includes a plurality of unmanned vehicles connected to a computing device. The computing device stores a dynamic attribute and a static attribute respective to each of the plurality of unmanned vehicles. The computing device is configured to: receive a task request including (i) an item identifier of an item, (ii) an action type defining an action to be performed respective to the item, and (iii) a location identifier of a location at which to perform the action; responsive to receiving the request, retrieve the stored dynamic attributes and static attributes; based on a comparison of the task request with the dynamic attributes and the static attributes, select one of the plurality of unmanned vehicles; and transmit, via the network, a command to the selected unmanned vehicle to perform the action respective to the item at the location.