Abstract: This disclosure describes a low-profile, high-load, and hands-free ball-balancing omnidirectional rolling system with multiple human-robot interfaces for modular and adaptive design configurations and input control interfaces. The disclosed platform uses a self-balancing ball-based robot to allow for a safe, compact, high-load, self-balancing and intuitive mobility device for a person with lower-limb disability. Advanced driving assistance such as obstacle avoidance and semi-autonomous navigation between predefined locations is also disclosed.

Abstract: Certain embodiments of the present invention provide robotic control modules for use in a robotic control system of a vehicle, including structures, systems and methods, that can provide (i) a robotic control module that has multiple functional circuits, such as a processor and accompanying circuits, an actuator controller, an actuator amplifier, a packet network switch, and a power supply integrated into a mountable and/or stackable package/housing; (ii) a robotic control module with the noted complement of circuits that is configured to reduce heat, reduce space, shield sensitive components from electro-magnetic noise; (iii) a robotic control system utilizing robotic control modules that include the sufficiently interchangeable functionality allowing for interchangeability of modules; and (iv) a robotic control system that distributes the functionality and processing among a plurality of robotic control modules in a vehicle.

Abstract: An autonomous vehicle having an interface for payloads that allows integration of various payloads. A vehicle control system controls an autonomous vehicle, receives data, and transmits a control signal on at least one network. A payload is adapted to detachably connect to the autonomous vehicle and includes a network interface configured to receive the control signal from the vehicle control system over the at least one network. The vehicle control system may encapsulate payload data and transmit the payload data over the at least one network, including Ethernet or CAN networks. The payload may be a laser scanner, a radio, chemical detection system, or GPS unit. In certain embodiments, the payload is a camera mast unit, where the camera communicates with the autonomous vehicle control system to detect and avoid obstacles. The camera mast unit may be interchangeable, and may include structures for receiving additional payload components.

Abstract: Systems and methods for switching between autonomous and manual operation of a vehicle are described. A mechanical control system can receive manual inputs from a mechanical operation member to operate the vehicle in manual mode. An actuator can receive autonomous control signals generated by a controller. When the actuator is engaged, it operates the vehicle in an autonomous mode, and when disengaged, the vehicle is operated in manual mode. Operating the vehicle in an autonomous mode can include automatically controlling steering, braking, throttle, and transmission. A system may also allow the vehicle to be operated via remote command.

Abstract: Certain embodiments of the present invention provide robotic control modules for use in a robotic control system of a vehicle, including structures, systems and methods, that can provide (i) a robotic control module that has multiple functional circuits, such as a processor and accompanying circuits, an actuator controller, an actuator amplifier, a packet network switch, and a power supply integrated into a mountable and/or stackable package/housing; (ii) a robotic control module with the noted complement of circuits that is configured to reduce heat, reduce space, shield sensitive components from electro-magnetic noise; (iii) a robotic control system utilizing robotic control modules that include the sufficiently interchangeable functionality allowing for interchangeability of modules; and (iv) a robotic control system that distributes the functionality and processing among a plurality of robotic control modules in a vehicle.

Abstract: Certain embodiments of the present invention provide robotic control modules for use in a robotic control system of a vehicle, including structures, systems and methods, that can provide (i) a robotic control module that has multiple functional circuits, such as a processor and accompanying circuits, an actuator controller, an actuator amplifier, a packet network switch, and a power supply integrated into a mountable and/or stackable package/housing; (ii) a robotic control module with the noted complement of circuits that is configured to reduce heat, reduce space, shield sensitive components from electro-magnetic noise; (iii) a robotic control system utilizing robotic control modules that include the sufficiently interchangeable functionality allowing for interchangeability of modules; and (iv) a robotic control system that distributes the functionality and processing among a plurality of robotic control modules in a vehicle.

Abstract: Embodiments of the invention provide systems and methods for obstacle avoidance. In some embodiments, a robotically controlled vehicle capable of operating in one or more modes may be provided. Examples of such modes include teleoperation, waypoint navigation, follow, and manual mode. The vehicle may include an obstacle detection and avoidance system capable of being implemented with one or more of the vehicle modes. A control system may be provided to operate and control the vehicle in the one or more modes. The control system may include a robotic control unit and a vehicle control unit.

Abstract: A speed control method of a vehicle including the steps of obtaining a steering angle, a velocity error and a distance error. The velocity and the distance error being determined by mathematical combinations of a GPS position, a required path and speed set points. The steering angle, velocity errors and distance error are applied to fuzzy logic membership functions to produce an output that is applied to a velocity rule base. An output from the velocity rule base is defuzzified to produce a speed signal.

Abstract: An autonomous vehicle and systems having an interface for payloads that allows integration of various payloads with relative ease. There is a vehicle control system for controlling an autonomous vehicle, receiving data, and transmitting a control signal on at least one network. A payload is adapted to detachably connect to the autonomous vehicle, the payload comprising a network interface configured to receive the control signal from the vehicle control system over the at least one network. The vehicle control system may encapsulate payload data and transmit the payload data over the at least one network, including Ethernet or CAN networks. The payload may be a laser scanner, a radio, a chemical detection system, or a Global Positioning System unit.

Abstract: A steering control method including the steps of obtaining a heading error, obtaining a velocity value, obtaining a distance error, applying the heading error and defuzzifying an output from a steering rule base. The velocity value and the distance error are applied along with the heading error to fuzzy logic membership functions to produce an output that is applied to a steering rule base. An output from the steering rule base is defuzzified to produce a steering signal.

Abstract: A steering control method including the steps of obtaining a heading error, obtaining a velocity value, obtaining a distance error, applying the heading error and defuzzifying an output from a steering rule base. The velocity value and the distance error are applied along with the heading error to fuzzy logic membership functions to produce an output that is applied to a steering rule base. An output from the steering rule base is defuzzified to produce a steering signal.

Abstract: A steering control method including the steps of obtaining a heading error, obtaining a velocity value, obtaining a distance error, applying the heading error and defuzzifying an output from a steering rule base. The velocity value and the distance error are applied along with the heading error to fuzzy logic membership functions to produce an output that is applied to a steering rule base. An output from the steering rule base is defuzzified to produce a steering signal.

Abstract: Embodiments of the invention provide systems and methods for obstacle avoidance. In some embodiments, a robotically controlled vehicle capable of operating in one or more modes may be provided. Examples of such modes include teleoperation, waypoint navigation, follow, and manual mode. The vehicle may include an obstacle detection and avoidance system capable of being implemented with one or more of the vehicle modes. A control system may be provided to operate and control the vehicle in the one or more modes. The control system may include a robotic control unit and a vehicle control unit.

Abstract: Embodiments of the invention provide systems and methods for obstacle avoidance. In some embodiments, a robotically controlled vehicle capable of operating in one or more modes may be provided. Examples of such modes include teleoperation, waypoint navigation, follow, and manual mode. The vehicle may include an obstacle detection and avoidance system capable of being implemented with one or more of the vehicle modes. A control system may be provided to operate and control the vehicle in the one or more modes. The control system may include a robotic control unit and a vehicle control unit.

Abstract: Systems and methods for switching between autonomous and manual operation of a vehicle are described. A mechanical control system can receive manual inputs from a mechanical operation member to operate the vehicle in manual mode. An actuator can receive autonomous control signals generated by a controller. When the actuator is engaged, it operates the vehicle in an autonomous mode, and when disengaged, the vehicle is operated in manual mode. Operating the vehicle in an autonomous mode can include automatically controlling steering, braking, throttle, and transmission. A system may also allow the vehicle to be operated via remote command.

Abstract: A human perception model for a speed control method obtains a steering angle, a velocity error and a distance error. The steering angle and a measure of operator aggressiveness are applied to the model. The output is defuzzified. The steering angle, the velocity error and the distance error are applied to fuzzy logic membership functions to produce an output that is applied to a velocity rule base. The measure of operator aggressiveness is input to the velocity rule base. The output from the velocity rule base is defuzzified to produce a speed signal.

Abstract: Systems and methods for switching between autonomous and manual operation of a vehicle are described. A mechanical control system can receive manual inputs from a mechanical operation member to operate the vehicle in manual mode. An actuator can receive autonomous control signals generated by a controller. When the actuator is engaged, it operates the vehicle in an autonomous mode, and when disengaged, the vehicle is operated in manual mode. Operating the vehicle in an autonomous mode can include automatically controlling steering, braking, throttle, and transmission. A system may also allow the vehicle to be operated via remote command.

Abstract: A vehicle steering control method including the steps of obtaining a heading error, obtaining a velocity value, obtaining a distance error, applying the heading error, inputting a measure of operator aggressiveness and defuzzifying an output from a steering rule base. The velocity value and the distance error are applied along with the heading error to fuzzy logic membership functions to produce an output that is applied to a steering rule base. A measure of the operator aggressiveness is input to the steering rule base. An output from the steering rule base is defuzzified to produce a steering signal.

Abstract: A reusable application framework for translating between a client and an external entity negotiates a first communication protocol with the client, receives an input request from the client, and parses the input request to extract client type and use case identifications. An application object module is configured for transferring the input request. A data mapper module is configured to extract input data from input requests having the client type identification, and maps the input data to an input bean. A use case handler module specific to at least one predefined task associated with the external entity receives the input bean. A broker module is configured to communicate with the external entity using a second communication protocol and inserts the input bean into a data stream of the second communication protocol for transfer to the external entity.

Abstract: A human perception model for a speed control method including the steps of obtaining a steering angle, a velocity error and a distance error. The method further includes the steps of applying the steering angle, inputting a measure of operator aggressiveness and defuzzifying an output. The applying step includes applying the steering angle, the velocity error and the distance error to fuzzy logic membership functions to produce an output that is applied to a velocity rule base. The inputting step inputs a measure of operator aggressiveness to the velocity rule base. The defuzzifying step defuzzifies an output from the velocity rule base to produce a speed signal.