Motion Planning through Demonstration to Deal with Complex Motions in Assembly Process
Yan Wang, Kensuke Harada, Weiwei Wan

TL;DR
This paper introduces a motion planning approach that leverages demonstration of skillful human assembly motions, using AR markers to capture key poses, enabling robots to perform complex assembly tasks more effectively.
Contribution
It presents a novel motion planning method that incorporates demonstration and AR marker tracking to handle complex, skillful motions in robotic assembly.
Findings
Method successfully captures key poses via AR markers.
Robot experiments validate the effectiveness of the approach.
Accelerates planning by prioritizing key poses based on derivatives.
Abstract
Complex and skillful motions in actual assembly process are challenging for the robot to generate with existing motion planning approaches, because some key poses during the human assembly can be too skillful for the robot to realize automatically. In order to deal with this problem, this paper develops a motion planning method using skillful motions from demonstration, which can be applied to complete robotic assembly process including complex and skillful motions. In order to demonstrate conveniently without redundant third-party devices, we attach augmented reality (AR) markers to the manipulated object to track and capture poses of the object during the human assembly process, which are employed as key poses to execute motion planning by the planner. Derivative of every key pose serves as criterion to determine the priority of use of key poses in order to accelerate the motion…
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Taxonomy
TopicsRobotic Path Planning Algorithms · Robot Manipulation and Learning · Robotics and Sensor-Based Localization
