Tomahawk Robotics

Harris Corporation

Daniel R Hedman

Matthew D Summer

William S Bowman

Andrew D Falendysz

Kevin Makovy

Michael E Bowman

Bradley D Truesdell

Paul Michael Bosscher

Brad Truesdell

Sean Wagoner

Michael W Holt

Jeffrey S Cooper

Kevin M Makovy

Methods and systems are described herein for generating composite data streams. A data stream processing system may receive multiple data streams from, for example, multiple unmanned vehicles and determine, based on the type of data within each data stream, a machine learning model for each data stream for processing the type of data. Each machine learning model may receive the frames of a corresponding data stream and output indications and locations of objects within those data streams. The data stream processing system may then generate a composite data stream with indications of the detected objects.

Architecture for distributed artificial intelligence augmentation with objects detected using artificial intelligence models from data received from multiple sources

Systems and methods of manipulating/controlling robots. In many scenarios, data collected by a sensor (connected to a robot) may not have very high precision (e.g., a regular commercial/inexpensive sensor) or may be subjected to dynamic environmental changes. Thus, the data collected by the sensor may not indicate the parameter captured by the sensor with high accuracy. The present robotic control system is directed at such scenarios. In some embodiments, the disclosed embodiments can be used for computing a sliding velocity limit boundary for a spatial controller. In some embodiments, the disclosed embodiments can be used for teleoperation of a vehicle located in the field of view of a camera.

Spatial teleoperation of legged vehicles

Methods and systems are described herein for detecting motion-induced errors received from inertial-type input devices and for generating accurate vehicle control commands that account for operator movement. These methods and systems may determine, using motion data from inertial sensors, whether the hand/arm of the operator is moving in the same motion as the body of the operator, and if both are moving in the same way, these systems and methods may determine that the motion is not intended to be a motion-induced command. However, if the hand/arm of the operator is moving in a different motion from the body of the operator, these methods and systems may determine that the operator intended the motion to be a motion-induced command to a vehicle.

Inertially isolated spatial control

Methods and systems are described herein for determining three-dimensional locations of objects within identified portions of images. An image processing system may receive an image and an identification of location within an image. The image may be input into a machine learning model to detect one or more objects within the identified location. Multiple images may then be used to generate location estimations of those objects. Based on the location estimations, an accurate three-dimensional location may be calculated.

Point of interest tracking and estimation

Systems and methods of detecting intent of spatial control

Systems and methods of remote teleoperation of robotic vehicles

A common command and control architecture (alternatively termed herein as a 'universal control architecture') is disclosed that allows different unmanned systems, including different types of unmanned systems (e.g., air, ground, and/or maritime unmanned systems), to be controlled simultaneously through a common control device (e.g., a controller that can be an input and/or output device). The universal control architecture brings significant efficiency gains in engineering, deployment, training, maintenance, and future upgrades of unmanned systems. In addition, the disclosed common command and control architecture breaks the traditional stovepipe development involving deployment models and thus reducing hardware and software maintenance, creating a streamlined training/proficiency initiative, reducing physical space requirements for transport, and creating a scalable, more connected interoperable approach to control of unmanned systems over existing unmanned systems technology.

Universal control architecture for control of unmanned systems

A robotic system implements a collision avoidance scheme and includes a first robotic manipulator and a first controller configured to control the first robotic manipulator for movement along a first pre-planned actual path. A second controller is configured to control movement of a second robotic manipulator for movement along a second pre-planned intended path and deviating therefrom to move in a dodging path away from the first pre-planned actual path based upon determining a potential collision with the first robotic manipulator without prior knowledge of the first pre-planned actual path.

Growing community of inventors

Palm Bay, FL, United States of America

Daniel R Hedman