Human-based framework for the assembly of elastic objects by a dual-arm robot

Human-based framework for the assembly of elastic objects by a dual-arm robot This paper proposes a new framework for planning assembly tasks involving elastic parts. As an example of these kind of assembly tasks, we deal with the insertion of ring-shaped objects into a cylinder by a dual-arm robot. The proposed framework is a combination of human movements to determine the overall assembly strategy and an optimization-based motion planner to generate the robot trajectories. The motion of the human’s hands, more specifically, the motion of the fingers gripping the object is captured by a Leap Motion Controller. Then, key points in the recorded trajectory of the position and orientation of the human’s fingers are extracted. These points are used as partial goals in the optimization-based motion planner that generates the robot arms’ trajectories which minimize the object’s deformation. Through experimental results it was verified the validity of the extracted key points from the human’s movements that enable the robot to successfully assemble ring-shaped elastic objects. We compared these results with the assembly done by purely repeating all of the human’s hands movements. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ROBOMECH Journal Springer Journals

Human-based framework for the assembly of elastic objects by a dual-arm robot

Human-based framework for the assembly of elastic objects by a dual-arm robot

This paper proposes a new framework for planning assembly tasks involving elastic parts. As an example of these kind of assembly tasks, we deal with the insertion of ring‑ shaped objects into a cylinder by a dual‑ arm robot. The proposed framework is a combination of human movements to determine the overall assembly strategy and an optimization‑ based motion planner to generate the robot trajectories. The motion of the human’s hands, more specifically, the motion of the fingers gripping the object is captured by a Leap Motion Controller. Then, key points in the recorded trajectory of the position and orientation of the human’s fingers are extracted. These points are used as partial goals in the optimization‑ based motion planner that generates the robot arms’ trajectories which minimize the object’s deformation. Through experimental results it was verified the validity of the extracted key points from the human’s movements that enable the robot to successfully assemble ring‑ shaped elastic objects. We compared these results with the assembly done by purely repeating all of the human’s hands movements. Keywords: Assembly, Deformable object, Human demonstration tasks, knowledge of all the parts to be assembled is indis- Introduction pensable. Since most of the assembly tasks have a very As stated by Napier [1]: “the hand of man is, the most small margin of error (in the order of mm), vision sensors perfect and complete mechanical organ that nature and force sensors are frequently needed for a robot to has yet produced” and it also comprises a very fine tac - successfully complete the assembly. In our previous work tile (somatic) sense. Indeed most of the tasks that only [4], we developed an assembly planner able to insert an humans are able to accomplish are due to the skillfulness elastic o-ring into a cylinder. Our planner first computes of our hands. Furthermore, if we add up that we humans a key position...
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Publisher
Springer International Publishing
Copyright
Copyright © 2017 by The Author(s)
Subject
Engineering; Robotics and Automation; Mechatronics; Artificial Intelligence (incl. Robotics); Control; Computational Intelligence
eISSN
2197-4225
D.O.I.
10.1186/s40648-017-0088-0
Publisher site
See Article on Publisher Site

Abstract

This paper proposes a new framework for planning assembly tasks involving elastic parts. As an example of these kind of assembly tasks, we deal with the insertion of ring-shaped objects into a cylinder by a dual-arm robot. The proposed framework is a combination of human movements to determine the overall assembly strategy and an optimization-based motion planner to generate the robot trajectories. The motion of the human’s hands, more specifically, the motion of the fingers gripping the object is captured by a Leap Motion Controller. Then, key points in the recorded trajectory of the position and orientation of the human’s fingers are extracted. These points are used as partial goals in the optimization-based motion planner that generates the robot arms’ trajectories which minimize the object’s deformation. Through experimental results it was verified the validity of the extracted key points from the human’s movements that enable the robot to successfully assemble ring-shaped elastic objects. We compared these results with the assembly done by purely repeating all of the human’s hands movements.

Journal

ROBOMECH JournalSpringer Journals

Published: Aug 14, 2017

References

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