Human-robot collaboration is becoming increasingly popular in the manufacturing industry, opening the door to a large range of applications by combining the complementary skills of the human worker and the robot. Collaborative robots are also a solution to decrease the operator workload and indirectly reduce the risk of occupational injuries such as musculoskeletal disorders (MSDs). The latter represents one of the major causes of absenteeism at work. Thanks to the development of human tracking devices, it is possible to monitor the operator, analyze the postures, and assess the associated MSD risk. In this paper, we present a novel ergonomics optimization framework that performs postural optimization based on the virtual element method. A feedback interface is developed whereby the user is informed about non-ergonomic postures and an improved body pose is proposed. The workpiece position controller module acts on the cobot end-effector and indirectly on the co-manipulated part in such a way that the operator’s posture is improved. The framework was validated by a user study performed on a human-robot collaboration task whereby the subject polishes a part hold by the robot. The conducted study of the user’s perception and REBA scores showed promising results. Note to Practitioners —This paper is motivated by the problem of non-ergonomic posture of workers in hybrid workcells. The proposed approach makes use of virtual elements (springs and dampers) to build a mechanical model of the human body posture and perform postural optimization. The obtained body joint angles are fed into two modules of the framework. First, a graphical interface displays the current pose of the user and proposes to him the improved posture. Second, a controller adapts the pose of the workpiece hold by the collaborative robot. This is realized by computing a displacement vector between the wrist current and optimized positions. The use of such a framework was demonstrated on a collaborative polishing task whereby the robot adjusts the position of the workpiece. After a user study test with 10 participants, joint data were collected and the REBA scores of different subtasks were measured and compared. The results from these preliminary experiments showed that the proposed approach improves the human body postures and offers a promising solution to enhance ergonomics by the robot assistance in case of robotic workcells. The conducted survey also shows an overall positive subject’s perception of the system.
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