The co-presence of a robot and a human sharing some activities in an industrial setting constitutes a challenging scenario for control solutions, requiring highly flexible controllers to preserve productivity and enforce human safety. Standard methods are not suitable given the lack of methodologies able to evaluate robot execution time variability, caused by the necessity to continuously modify/adapt robot motions to grant human safety. This paper presents a novel dynamic planning system for Human-Robot Collaboration (HRC) which leverages an offline motion planning technique and deploys planning and execution features dealing with temporal uncertainty and kinematics both at planning and execution time. The proposed system is deployed in a manufacturing case study for controlling a working cell in which a robot and a human collaborate to achieve a shared production goal. The approach has been shown to be feasible and effective in a real case study.

Planning and execution with robot trajectory generation in industrial human-robot collaboration

Molinari Tosatti, Lorenzo;Pellegrinelli, Stefania;Tolio, Tullio;
2018

Abstract

The co-presence of a robot and a human sharing some activities in an industrial setting constitutes a challenging scenario for control solutions, requiring highly flexible controllers to preserve productivity and enforce human safety. Standard methods are not suitable given the lack of methodologies able to evaluate robot execution time variability, caused by the necessity to continuously modify/adapt robot motions to grant human safety. This paper presents a novel dynamic planning system for Human-Robot Collaboration (HRC) which leverages an offline motion planning technique and deploys planning and execution features dealing with temporal uncertainty and kinematics both at planning and execution time. The proposed system is deployed in a manufacturing case study for controlling a working cell in which a robot and a human collaborate to achieve a shared production goal. The approach has been shown to be feasible and effective in a real case study.
4th Italian Workshop on Artificial Intelligence and Robotics, AIRO 2017
Computer Science (all)
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1064685
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