Abstract: Methods and systems are provided for traction detection and control of a self-driving vehicle. The self-driving vehicle has drive motors that drive drive-wheels according to a drive-motor speed. Traction detection and control can be obtained by measuring the vehicle speed with a sensor such as a LiDAR or video camera, and measuring the wheel speed of the drive wheels with a sensor such as a rotary encoder. The difference between the measured vehicle speed and the measured wheel speeds can be used to determine if a loss of traction has occurred in any of the wheels. If a loss of traction is detected, then a recovery strategy can be selected from a list of recovery strategies in order to reduce the effects of the loss of traction.

Abstract: 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.

Abstract: Apparatus, systems and methods for providing smart pick-up and drop-off are presented. The apparatus comprises at least one vertical support member and at least one storage shelf supported by the at least one vertical support member. A payload transfer surface, supported by the vertical support members, is located below the lowest storage shelf. The payload transfer surface has an access channel so that a self-driving material-transport vehicle equipped with a lift appliance can pick up or drop off a payload on the payload transfer surface. A sensor associated with the payload transfer surface senses the presence or absence of a payload on the payload transfer surface, and sends a signal to a fleet-management system in communication with the self-driving material-transport vehicle.

Abstract: 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.

Abstract: Systems and methods of unmanned vehicles having self-calibrating sensors and actuators are provided. The unmanned vehicle comprises a communication interface and a processor for controlling a propulsion system of the vehicle and receiving sensor data from one or more sensors of the vehicle. The processor is configured to operate in a guided calibration mode by controlling the propulsion system according to commands received from an external guided control system, while processing the sensor data to determine a degree of certainty on a calibration the sensor data and a position of the vehicle. The processor determines that the degree of certainty is above a threshold value associated with safe operation of the propulsion system in an autonomous calibration mode, and subsequently switch operation of the propulsion system to the autonomous calibration mode based on the determination that the degree of certainty is above the threshold value.

Abstract: 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.

Abstract: A mobile platform for materials transport is provided. The platform includes a pair of suspension devices that in turn include a pair of rocker beams which can be rotated between two positions: a first position where central wheels attached thereto can be used to drive the platform; and a second position where the central wheels are retracted and the platform can be rolled on end wheels without the friction of the central wheels, and an associated drive system, impeding movement of the platform. Furthermore, data from sensors and/or load cells can be used to control movement of the platform; specifically shifts in load distribution and/or sensed forces at the suspension devices can indicate that a load (and/or materials) has shifted and/or is shifting and movement of the platform is adjusted accordingly, for example to prevent the platform and/or the load (and/or materials) from tipping.

Abstract: 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.

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 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 sender device implements an auxiliary transport protocol by: storing routing records containing respective content type indicators, message source identifiers and message destination identifiers. A first record contains an initial content type indicator and a destination identifier corresponding to a sender device relay. A second record contains an extended content type indicator and a destination identifier corresponding to a sender device bridge. The sender device generates and routes an initial message having a payload and the initial content type indicator to the relay via a primary transport protocol according to the first record; at the relay, generates an extended message having the payload and the extended content type indicator, and routes the message to the bridge via the primary protocol according to the second record; at the bridge, generates a converted extended message; and transmits the converted extended message to a receiver device via the auxiliary protocol.

Abstract: Systems and methods for utilizing fleets of robots are disclosed. The method comprises receiving a task with a computing device, and retrieving, from a memory, battery-charge attributes associated, respectively, with at least three robots. A determination is made that the first battery-charge attribute is greater than the second battery-charge attribute, which is greater than the third battery-charge attribute. The battery-charge attributes are evaluated against a criterion. After determining that the first and second battery-charge attributes satisfy the criterion, the first and second robots are added to a selection set. After determining that the third battery-charge attribute does not satisfy the criterion, the third robot is omitted from the selection set. The selection is then optimized based on the first and second battery-charge attributes, and then one of the first and second robots is selected from the selection set to perform an action associated with the task request.

Abstract: 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.

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: An autonomous vehicle is disclosed. The vehicle comprises a chassis, two or more drive wheels extending below the chassis, a drive motor housed within the chassis for driving the drive wheels, and a payload surface on top of the chassis for carrying a payload. An illumination system, for emitting light from at least one portion of the chassis, is mounted substantially around the entire perimeter of the chassis. The illumination system may be implemented using an array of light-emitting diodes (“LEDs”) that are arranged as segments. For example, there may be “headlight” segments on the front left and front right corners of the chassis.

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.

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: An electric vehicle charging interface device is provided. The device includes a chassis having a top, a bottom, a front side, and a back side opposite the front side, the chassis configured to move between an uncompressed position and a compressed position relative to a longitudinal axis. The device further includes two electrodes extending from the front side of the chassis, and, a biasing portion configured to bias the chassis towards the uncompressed position.

Abstract: A mobile platform for materials transport is provided. The platform includes a pair of suspension devices that in turn include a pair of rocker beams which can be rotated between two positions: a first position where central wheels attached thereto can be used to drive the platform; and a second position where the central wheels are retracted and the platform can be rolled on end wheels without the friction of the central wheels, and an associated drive system, impeding movement of the platform. Furthermore, data from sensors and/or load cells can be used to control movement of the platform; specifically shifts in load distribution and/or sensed forces at the suspension devices can indicate that a load (and/or materials) has shifted and/or is shifting and movement of the platform is adjusted accordingly, for example to prevent the platform and/or the load (and/or materials) from tipping.