Motion Planning through Demonstration to Deal with Complex Motions in Assembly Process
This addresses the problem of enabling robots to perform complex assembly tasks for industrial applications, but it is incremental as it builds on existing demonstration-based planning approaches.
The paper tackles the challenge of robots generating complex and skillful motions in assembly processes by developing a motion planning method that uses demonstrations, specifically tracking object poses with AR markers to capture key poses from human assembly. The method's effectiveness is verified through numerical examples and actual robot experiments.
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 planning. The effectiveness of the presented method is verified through some numerical examples and actual robot experiments.