RAPID DESIGN AND ANIMATION OF FREELY-WALKING ROBOTIC DEVICES

Number: 20250108505
Published: 2025-04-03
Filed: 2024-05-08
Assignee: DISNEY ENTERPRISES, INC.
Inventors: Bächer; Moritz Niklaus et al.
CPC: B25J9/0081; B25J9/1653; B25J9/163
Verdict: High Hardware
Source: Google Patents · FreePatentsOnline

The keeper's note

Freely-walking robotic-device rapid design/animation technique (Bächer).

Abstract

A method of training a robotic device includes: parameterizing, via a processing element, an input to the robotic device. The parameterizing comprises defining a range of values of the input. The method further includes generating, via the processing element, a plurality of samples of the parameterized input from within the range of values; training a control policy, via the processing element. The training includes: providing the plurality of samples to the control policy, wherein the control policy is adapted to operate an actuator of the robotic device, and generating, via the processing element, a policy action using the control policy; transmitting the policy action to a robotic model, wherein the robotic model includes a physical model of the robotic device. The method further includes deploying the one or more trained control policies to an on-board controller for the robotic device.

Background

FIELD

The present application relates to systems and methods for controlling and generating effects with robotic characters. BACKGROUND

Creating and training robotic characters, such as free moving robots, can be time intensive and processing intensive. Previous model-based processes for creating free moving robots often are too-closely tied to the physical hardware, making changes and improvements to the processes or hardware difficult, i.e., new hardware requires entirely new control processes to enable accurate control and balance for the robotic device. Therefore, there exists a need for improved processes that can enable quick design of stable and creative robotic systems. BRIEF SUMMARY

In one embodiment, a method of training a robotic device includes: parameterizing, via a processing element, an input to the robotic device, wherein the parameterizing includes defining a range of values of the input; generating, via the processing element, a plurality of samples of the parameterized input from within the range of values; training a control policy, via the processing element, wherein the training includes: providing the plurality of samples to the control policy, wherein the control policy is adapted to operate an actuator of the robotic device, and generating, via the processing element, a policy action using the control policy; transmitting the policy action to a robotic model, wherein the robotic model includes a physical model of the robotic devic

Claims

1. A method of training a robotic device comprising: parameterizing, via a processing element, an input to the robotic device, wherein the parameterizing comprises defining a range of values of the input; generating, via the processing element, a plurality of samples of the parameterized input from within the range of values; training a control policy, via the processing element, wherein the training comprises: providing the plurality of samples to the control policy, wherein the control policy is adapted to operate an actuator of the robotic device, and generating, via the processing element, a policy action using the control policy; transmitting the policy action to a robotic model, wherein the robotic model includes a physical model of the robotic device; and deploying the trained control policy to an on-board controller for the robotic device. || 5. A method of operating a robotic device comprising: receiving, at a processing element, a user input, wherein the processing element is in communication with one or more actuators of the robotic device; comparing, via the processing element, the user input to an animation database; selecting, via the processing element, an animation from the animation database based on the comparison; activating, via the processing element, a control policy for the selected animation, wherein the control policy has been trained by a reinforcement learning method; generating, via the processing element, a low-level control adapted to control a robotic device actuator; controlling, via the low-level control, the robotic device actuator. || 14. A robotic device comprising: a plurality of modular hardware components; a processing element in communication with the plurality of modular hardware components; a plurality of control policies trained by a reinforcement learning method to control the plurality of modular hardware components. || 22. A method of controlling a robotic device comprising: generating, via a first trained control policy executed by a processing element, a first policy action adapted to perform a perpetual motion; generating, via a second trained control policy executed by the processing element, a second policy action adapted to perform a periodic motion; generating, via a third trained control policy executed by the processing element, a third policy action adapted to perform an episodic motion; and deploying, via the processing element, the first, second, and third policy actions to a plurality of actuators of the robotic device, wherein the plurality of actuators are adapted to perform the perpetual motion, the periodic motion, and the episodic motion.