Human robot collaboration requires new planning strategies to guarantee an efficient and safe coexistence of robots and humans in the workspace. We propose a framework based on a model predictive control approach to trajectory scaling and inverse kinematics. The online modification of the velocity override slows down the task to ensure safety and the redundancy of the system is exploited to maximize the distance from the operator. Experimental results on a 7-degree-of-freedom robotic system prove the effectiveness of the method.

An MPC Framework for Online Motion Planning in Human-Robot Collaborative Tasks

Faroni M.;Beschi M.;
2019-01-01

Abstract

Human robot collaboration requires new planning strategies to guarantee an efficient and safe coexistence of robots and humans in the workspace. We propose a framework based on a model predictive control approach to trajectory scaling and inverse kinematics. The online modification of the velocity override slows down the task to ensure safety and the redundancy of the system is exploited to maximize the distance from the operator. Experimental results on a 7-degree-of-freedom robotic system prove the effectiveness of the method.
2019
IEEE International Conference on Emerging Technologies and Factory Automation, ETFA
Enti pubb. di ricerca ital.
Inglese
24th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2019
2019
esp
2019-
1555
1558
4
978-1-7281-0303-7
Institute of Electrical and Electronics Engineers Inc.
no
none
Faroni, M.; Beschi, M.; Pedrocchi, N.
273
info:eu-repo/semantics/conferenceObject
3
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/528740
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