Trajectory learning is a fundamental component in a robot Programming by Demonstration (PbD) system, where often the very purpose of the demonstration is to teach complex manipulation patterns. However, human demonstrations are inevitably noisy and inconsistent. This paper highlights the trajectory learning component of a PbD system for manipulation tasks encompassing the ability to cluster, select, and approximate human demonstrated trajectories. The proposed technique provides some advantages with respect to alternative approaches and is suitable for learning from both individual and multiple user demonstrations.

Robust Trajectory Learning and Approximation for Robot Programming by Demonstration / Aleotti, Jacopo; Caselli, Stefano. - In: ROBOTICS AND AUTONOMOUS SYSTEMS. - ISSN 0921-8890. - 54:(2006), pp. 409-413. [10.1016/j.robot.2006.01.003]

Robust Trajectory Learning and Approximation for Robot Programming by Demonstration

ALEOTTI, Jacopo;CASELLI, Stefano
2006-01-01

Abstract

Trajectory learning is a fundamental component in a robot Programming by Demonstration (PbD) system, where often the very purpose of the demonstration is to teach complex manipulation patterns. However, human demonstrations are inevitably noisy and inconsistent. This paper highlights the trajectory learning component of a PbD system for manipulation tasks encompassing the ability to cluster, select, and approximate human demonstrated trajectories. The proposed technique provides some advantages with respect to alternative approaches and is suitable for learning from both individual and multiple user demonstrations.
2006
Robust Trajectory Learning and Approximation for Robot Programming by Demonstration / Aleotti, Jacopo; Caselli, Stefano. - In: ROBOTICS AND AUTONOMOUS SYSTEMS. - ISSN 0921-8890. - 54:(2006), pp. 409-413. [10.1016/j.robot.2006.01.003]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/1512368
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