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Section: New Results

Securing industrial operators with collaborative robots: simulation and experimental validation for a carpentry task

In this work, a robotic assistance strategy is developed to improve the safety in an artisanal task that involves a strong interaction between a machine-tool and an operator. Wood milling is chosen as a pilot task due to its importance in carpentry and its accidentogenic aspect.

In order to analyze the wood milling task, a wood shaping training was conducted in collaboration with a carpentry learning institute which allowed to collect information related to the task (perceived effort, position of the operator, accident circumstances).

To analyze the human-machine interaction, a formalization of the problem as a dynamic exchange of spatial forces inspired by the grasping theory has been performed. This theory presents structural similarities with the studied task. Based on this formalization, a behavior simulator of the system “wood + human + tool” has been developed.

To propose a credible and a realistic assistance solution, accidentogenic situations are simulated (see Woobotsim). Based on the observation made with these simulations, the use of a collaborative robot to secure wood instability cases has been explored and validated by an experiment. An operational space damping behaviour appears to be the most appropriate solution to improve safety in the studied cases.

The experiment was designed to reproduce two cases of instability during a carpentry milling task based on the entry and exit of the tool into and out of a wood node. For safety reasons, the experiment is performed on a safe but tangible simulation of the task. We then show how a robot ((Franka Emika's Panda, 7-DOF)) controlled in torque can instantly stabilize the wood to avoid an accident without modifying the carpenter's sensations.

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