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 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: 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: 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.

Abstract: Systems and methods for generating a mission for a self-driving material-transport vehicle are presented. The system comprises at least one self-driving material-transport vehicle, at least one programmable logic controller, at least one field instrument, and at least one non-transitory computer-readable medium in communication with at least one processor. An application signal is received from the programmable logic controller based on an activation signal from the field instrument. A mission is generated by the application signal and a mission template, and the mission is transmitted to the self-driving material-transport vehicle. In some cases, the application signal may be based on OPC-UA, and the mission and/or mission template may be based on a REST protocol.

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 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.

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: There is provided an electrically-powered material-transport vehicle having a vehicle-charging contact on one side of the vehicle, and a second vehicle-charging contact on the opposite side of the vehicle. The vehicle has a load-bearing cap that covers the top of the vehicle, and a cap elevator for raising and lowering the cap. The cap can be raised and lowered to a transit position, a payload-engagement position, a charging position, and a maintenance position. In the transit position and payload-engagement position, the cap covers the vehicle-charging contacts so that they are not exposed. In the charging position, the cap is raised so that the vehicle-charging contacts are exposed. The vehicle can enter a charging-dock with the cap in the charging position in order to recharge the vehicle's battery.

Abstract: 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.

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: 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.

Abstract: Systems and methods for electronically mapping a facility are presented. The method comprises obtaining a CAD file that includes graphical representations of a facility. An occupancy-map image is generated based on the CAD file. A sensor, such as a sensor on a self-driving vehicle, is used to detect a sensed feature within the facility. Based on the sensed feature, the occupancy-map image can be updated, since the sensed feature was not one of the known features in the CAD file prior to the sensed feature being detected by the sensor.

Abstract: Systems and methods for measuring a fleet of self-driving vehicles are disclosed. The system comprises one or more self-driving vehicles, non-transitory computer-readable media in communication with the vehicles, a fleet-management system in communication with the media and vehicles, and a server in communication with the media. The fleet-management system is configured to store vehicle status records comprising a vehicle status pertaining to each of the one or more vehicles, and a timestamp in a vehicle status log on the media. The server has a processor that is configured to generate a fleet-performance report based on the vehicle status log.

Abstract: An augmentation module is described for an automated guided vehicle (AGV) deployed in a facility and including a control module for controlling a drive mechanism based on navigational data received from a navigation sensor. The module includes a inter-module communications interface connected to the control module; a memory; and a processor connected to the communications interface and the memory. The processor is configured to: obtain an operational command; generate control data to execute the operational command; convert the control data to simulated sensor data; and send the simulated sensor data to the control module.