Deere & Company

Irobot Corporation

William Robert Norris

James Raymond Allard

John Franklin Reid

Bernard Edwin Romig

Mikhail Filippov

Christopher David Glenn Turner

Andrew Julian Norby

Kathleen Wienhold

Anthony Francis Catalfano

Brian Joseph Gilmore

Mark D Schmaltz

Scott Keller

Robert Dale Haun

Osa Fitch

Kevin B Larsen

Nadim El Fata

Arlen Eugene Meuchel

Chris A De Roo

John O'Connor

Seth Gilbertson

David S Zendzian

Jeffery Scott Puhalla

Bernard Edwin Rornig

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.

Versatile robotic control module

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.

Systems and methods for switching between autonomous and manual operation of a vehicle

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.

Systems and methods for obstacle avoidance

A method of controlling a vehicle suspension system including the steps of detecting, computing and altering the center of gravity of the vehicle. The detecting step includes the detecting of a center of gravity of the vehicle thereby defining a detected center of gravity. The computing step includes computing what alteration of a plurality of actuators is needed to substantially reduce a value of a difference between the detected center of gravity and a preferred center of gravity using a fuzzy relations control strategy. The computing step is carried out in a controller. The altering step includes altering the center of gravity of the vehicle by way of the controller actuating at least one of the actuators connected to suspension elements of the vehicle dependent upon the alteration arrived at in the computing step.

Vehicle center of gravity active suspension control system

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.

Perception model for trajectory following autonomous and human augmented steering control

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.

Perception model for trajectory following autonomous and human augmented speed control

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.

Networked multi-role robotic vehicle

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.

Human perception model for speed control performance

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.

Vehicle steering control method and performance

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.

Growing community of inventors

Rock Hill, SC, United States of America

William Robert Norris