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 Marco
Primo
Membro del Collaboration Group
;
Beschi Manuel
Co-ultimo
Membro del Collaboration Group
;
Pedrocchi Nicola
Co-ultimo
Membro del Collaboration Group
2019

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
Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato - STIIMA (ex ITIA)
978-1-7281-0303-7
robotics
MPC
motion planning
optimization
huma.robot collaboration
cobots
industrial application
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/372515
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