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This is a record of a document published elsewhere, first published by the United States Patent and Trademark Office, as US-12583111-B2, on 24 March 2026. OpenTechnical did not first disclose it. The identifier, hashes and timestamps below record what this library served and when, not when the material became public. View the original.

OT-2026-000001560

Eye-on-hand reinforcement learner for dynamic grasping with active pose estimation

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Classification
Robotics & Automation › Robot Architectures
Inventors
HUANG BAICHUAN, JAIN SIDDARTH, YU JINGJIN
Assignee
MITSUBISHI ELECTRIC RES LABORATORIES INC
Original source
US-12583111-B2, the United States Patent and Trademark Office, 24 March 2026
Document SHA-256
378a1cab8b885ba6edb8f5127e881e72f2f835eb8455608b42680565bd6c9aeb

Abstract

A controller is provided for performing dynamic grasping of a target object using visual sensory inputs. The controller includes a robotic interface connected to a robotic arm including links connected by joints having actuators and encoders, and a gripper of the end-effector of the robotic arm configured to grasp the target object in response to robot control signals, and a vision sensor configured to continuously provide visual observations for tracking poses of the target object in a workspace and compute grasp poses, wherein the vision sensor is mounted on a distal end of the robotic arm adjacent to the gripper. The controller trains the Eye-on-Hand reinforcement learner policy, tracks the poses of the target object, and generates robot control signals to follow the target object while keeping it in the field of view of the vision sensor and grasp the target object in the workspace.

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Citation

OpenTechnical Publication OT-2026-000001560, “Eye-on-hand reinforcement learner for dynamic grasping with active pose estimation,” published September 15, 2026 at 19:06:40 UTC, https://opentechnical.org/p/OT-2026-000001560.

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