Robot Programming by Demonstration: Trajectory Learning Enhanced by sEMG-Based User Hand Stiffness Estimation

Trajectory learning is one of the key components of robot Programming by Demonstration approaches, which in many cases, especially in industrial practice, aim at defining complex manipulation patterns. In order to enhance these methods, which are generally based on a physical interaction between the...

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Bibliographic Details
Published in:IEEE transactions on robotics Vol. 39; no. 4; pp. 3259 - 3278
Main Authors: Biagiotti, Luigi, Meattini, Roberto, Chiaravalli, Davide, Palli, Gianluca, Melchiorri, Claudio
Format: Journal Article
Language:English
Published: New York IEEE 01.08.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Constrained smoothing B-splines
Education
human–robot interaction
Learning
Muscles
Optimization
Programming
programming by demonstration (PbD)
Robots
Splines (mathematics)
Stiffness
surface electromyography (sEMG) signals
Task analysis
Trajectory
Trajectory analysis
ISSN:1552-3098, 1941-0468
Online Access:Get full text
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Summary:Trajectory learning is one of the key components of robot Programming by Demonstration approaches, which in many cases, especially in industrial practice, aim at defining complex manipulation patterns. In order to enhance these methods, which are generally based on a physical interaction between the user and the robot, guided along the desired path, an additional input channel is considered in this article. The hand stiffness, that the operator continuously modulates during the demonstration, is estimated from the forearm surface electromyography and translated into a request for a higher or lower accuracy level. Then, a constrained optimization problem is built (and solved) in the framework of smoothing B-splines to obtain a minimum curvature trajectory approximating, in this manner, the taught path within the precision imposed by the user. Experimental tests in different applicative scenarios, involving both position and orientation, prove the benefits of the proposed approach in terms of the intuitiveness of the programming procedure for the human operator and characteristics of the final motion.
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ISSN:1552-3098
1941-0468
DOI:10.1109/TRO.2023.3258669