Disney Enterprises, Inc.

Tanner J Rinke

Alfredo Medina Ayala

Moritz Niklaus Bächer

Lars Espen Knoop

Christian Gabriel Schumacher

Sungjoon Choi

Venkata Krishna Tamminana

A robot control method, and associated robot controllers and robots operating with such methods and controllers, providing real-time vibration suppression. The control method involves learning to support real-time, vibration-suppressing control. The method uses state-of-the-art machine learning techniques in conjunction with a differentiable dynamics simulator to yield fast and accurate vibration suppression. Vibration suppression using offline simulation approaches that can be computationally expensive may be used to create training data for the controller, which may be provide by a variety of neural network configurations. In other cases, sensory feedback from sensors onboard the robot being controlled can be used to provide training data to account for wear of the robot's components.

Robotic systems using learning to provide real-time vibration-suppressing control

A rotating joint assembly such as an interface device in a master device or remote manipulator for a puppeteering device or other mechanical system operating in response to operator input and requiring more than 360 degrees of rotation. The rotating joint assembly includes a hard stop assembly that limits the rotation of its rotating component(s) to a predefined maximum amount of rotation such as to less than two full revolutions, e.g., some rotation amount between 360 and 720 degrees. The hard stop assembly includes a Geneva drive body or driven wheel with a hard stop body rigidly coupled with the Geneva drive body to rotate it between a disengaged position (during the first revolution) and one of two engaged positions by rotation of an inner ring (at some point during the second revolution in either direction).

Hard stop assembly for a joint adapted for more than a single revolution

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Sherman Oaks, CA, United States of America

Tanner J Rinke