Haptic shared control enables a human operator and an autonomous controller to share the control of a robotic system using haptic active constraints. It has been used in robotic teleoperation for different purposes, such as navigating along paths minimizing the torques requested to the manipulator or avoiding possibly dangerous areas of the workspace. However, few works have focused on using these ideas to account for the user’s comfort. In this work, we present an innovative haptic-enabled shared control approach aimed at minimizing the user’s workload during a teleoperated manipulation task. Using an inverse kinematic model of the human arm and the Rapid Upper Limb Assessment (RULA) metric, the proposed approach estimates the current user’s comfort online. From this measure and an a priori knowledge of the task, we then generate dynamic active constraints guiding the users towards a successful completion of the task, along directions that improve their posture and increase their comfort. Studies with human subjects show the effectiveness of the proposed approach, yielding a 30% perceived reduction of workload with respect to using standard guided human-in-the-loop teleoperation.

Caring about the human operator: haptic shared control for enhanced user comfort in robotic telemanipulation

Gabiccini, Marco
Membro del Collaboration Group
;
Artoni, Alessio
Membro del Collaboration Group
;
2020-01-01

Abstract

Haptic shared control enables a human operator and an autonomous controller to share the control of a robotic system using haptic active constraints. It has been used in robotic teleoperation for different purposes, such as navigating along paths minimizing the torques requested to the manipulator or avoiding possibly dangerous areas of the workspace. However, few works have focused on using these ideas to account for the user’s comfort. In this work, we present an innovative haptic-enabled shared control approach aimed at minimizing the user’s workload during a teleoperated manipulation task. Using an inverse kinematic model of the human arm and the Rapid Upper Limb Assessment (RULA) metric, the proposed approach estimates the current user’s comfort online. From this measure and an a priori knowledge of the task, we then generate dynamic active constraints guiding the users towards a successful completion of the task, along directions that improve their posture and increase their comfort. Studies with human subjects show the effectiveness of the proposed approach, yielding a 30% perceived reduction of workload with respect to using standard guided human-in-the-loop teleoperation.
2020
Rahal, Rahaf; Matarese, Giulia; Gabiccini, Marco; Artoni, Alessio; Prattichizzo, Domenico; Robuffo Giordano, Paolo; Pacchierotti, Claudio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1025853
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