Sikorsky Aircraft Corporation

Uatc, LLC

Uber Technologies, Inc.

Aurora Operations, Inc.

Aaron L Greenfield

Diana Yanakiev

Frederic Tschanz

Vineet Sahasrabudhe

Kenneth Stephen Wittmer

Charles J Tytler

Derek H Geiger

Ole Wulff

John Knag

David McAllister Bradley

Scott C Poeppel

Erez Eller

Matthew A White

Robert Zlot

Mark Sibenac

Cody Fegely

James Rigsby

Maitreya Jayesh Naik

Marc Leach

Matthew T Luszcz

Stephen T Kubik

Alex Faynberg

Dillon Collins

John Rucci

Glen A Knaust

Sean McNeil

Sunny K Siu

Jonathan Aaron Litwin

Jennifer D Goss

Derek Geiger

In one example embodiment, a computer-implemented method includes receiving data representing a motion plan of the autonomous vehicle via a plurality of control lanes configured to implement the motion plan to control a motion of the autonomous vehicle, the plurality of control lanes including at least a first control lane and a second control lane, and controlling the first control lane to implement the motion plan. The method includes detecting one or more faults associated with implementation of the motion plan by the first control lane or the second control lane, or in generation of the motion plan, and in response to one or more faults, controlling the first control lane or the second control lane to adjust the motion of the autonomous vehicle based at least in part on one or more fault reaction parameters associated with the one or more faults.

Fault-tolerant control of an autonomous vehicle with multiple control lanes

The present disclosure is directed to controlling state transitions in an autonomous vehicle. In particular, a computing system can initiate the autonomous vehicle into a no-authorization state upon startup. The computing system can receive an authorization request. The computing system determines whether the authorization request includes a request to enter the first or second mode of operations, wherein the first mode of operations is associated with the autonomous vehicle being operated without a human operator and the second mode of operations is associated with the autonomous vehicle being operable by a human operator. The computing system can transition the autonomous vehicle from the no-authorization state into a standby state in response to determining the authorization request includes a request to enter the first mode of operations or into a manual-controlled state in response to determining the authorization request is a request to enter the second mode of operations.

System and methods for controlling state transitions using a vehicle controller

A sensor data processing system for an autonomous vehicle receives inertial measurement unit (IMU) data from one or more IMUs of the autonomous vehicle. Based at least in part on the IMU data, the system identifies an IMU data offset from a deficient IMU of the one or more IMUs, and generates an offset compensation transform to compensate for the IMU data offset from the deficient IMU. The system dynamically executes the offset compensation transform on the IMU data from the deficient IMU to dynamically compensate for the IMU data offset.

IMU data offset compensation for an autonomous vehicle

Systems and methods are directed to motion planning for an autonomous vehicle. In one example, a computer-implemented method for road surface dependent motion planning includes obtaining, by a computing system comprising one or more computing devices, surface friction data. The method further includes determining, by the computing system, one or more constraints for motion planning based at least in part on the surface friction data. The method further includes generating, by the computing system, a motion plan for an autonomous vehicle based at least in part on the one or more constraints.

Systems and methods for road surface dependent motion planning

A sensor data processing system of an autonomous vehicle can receive inertial measurement unit (IMU) data from one or more IMUs of the autonomous vehicle. Based at least in part on the IMU data, the system can identify an IMU data offset from a deficient IMU of the one or more IMUs, and generate an offset compensation transform to compensate for the IMU data offset from the deficient IMU. The system may then dynamically execute the offset compensation transform on the IMU data from the deficient IMU to dynamically compensate for the IMU data offset.

The present disclosure is directed to a vehicle dynamics monitor for an autonomous vehicle. In particular, the systems and methods of the present disclosure can determine, based on data received from one or more sensors of an autonomous vehicle, that an anomaly exists in an interface between at least one tire of the autonomous vehicle and a road surface. Responsive to determining that the anomaly exists: a motion plan for the autonomous vehicle that takes into account the anomaly can be determined; and one or more controls of the autonomous vehicle can be interfaced with to implement the motion plan.

Vehicle dynamics monitor for autonomous vehicle

A system and method of controlling flight of an aircraft is disclosed. The system includes a first inceptor that provides a direct mode command for controlling a control axis of the aircraft according to a direct mode and a second inceptor that provides a stable mode command for controlling the control axis of the aircraft according to a stable mode. A processor receives the direct mode command and the stable mode command, forms a combined command for controlling the control axis of the aircraft based on a combination of the direct mode command and the stable mode command, and controls the control axis of the aircraft according to the combined command.

Simultaneous flight path control and attitude control with control axis splitting

The present disclosure provides a vehicle interface for an autonomous vehicle. In particular, the systems and methods of the present disclosure can, responsive to receiving, from an autonomy computing system of an autonomous vehicle, a time-based trajectory for the autonomous vehicle, verify that execution of the time-based trajectory is within parameters of the autonomous vehicle. Responsive to verifying that execution of the time-based trajectory is within the parameters of the autonomous vehicle, the time-based trajectory can be converted into a spatial path for the autonomous vehicle, and one or more controls of the autonomous vehicle can be interfaced with such that the autonomous vehicle tracks the spatial path.

Vehicle interface for autonomous vehicle

The present disclosure provides systems and methods that employ tolerance values defining a level of vehicle control precision for motion control of an autonomous vehicle. More particularly, a vehicle controller can obtain a trajectory that describes a proposed motion path for the autonomous vehicle. A constraint set of one or more tolerance values (e.g., a longitudinal tolerance value and/or lateral tolerance value) defining a level of vehicle control precision can be determined or otherwise obtained. Motion of the autonomous vehicle can be controlled to follow the trajectory within the one or more tolerance values (e.g., longitudinal tolerance value(s) and/or a lateral tolerance value(s)) identified by the constraint set. By creating a motion control framework for autonomous vehicles that includes an adjustable constraint set of tolerance values, autonomous vehicles can more effectively implement different precision requirements for different driving situations.

Context-specific tolerance for motion control in autonomous vehicles

One aspect is a flight control system for a coaxial rotary wing aircraft including a main rotor system and an active elevator. The flight control system includes a flight control computer with processing circuitry that executes control logic. The control logic includes a gust detector that produces a gust error indicative of a wind gust encountered by the coaxial rotary wing aircraft. The control logic also includes a gust alleviation control that reduces lift on the main rotor system with collective, based on the gust error, and mixes a collective command to a main rotor cyclic and a differential cyclic to reduce an aircraft pitch response and a lift-offset change. The gust alleviation control also reduces a main rotor pitching moment with the main rotor cyclic, based on the gust error, and mixes a main rotor cyclic command to the active elevator to reduce the aircraft pitch response.

Gust alleviating control for a coaxial rotary wing aircraft

Growing community of inventors

Pittsburgh, PA, United States of America

Aaron L Greenfield