Work

Is the Leader Robot an Adequate Sensor for Posture Estimation and Ergonomic Assessment of A Human Teleoperator?

Year: 2021

Type: conference-paper

Abstract: Ergonomic assessment of human posture plays a vital role in understanding work-related safety and health. Current posture estimation approaches face occlusion challenges in teleoperation and physical human-robot interaction. We investigate if the leader robot is an adequate sensor for posture estimation in teleoperation and we introduce a new probabilistic approach that relies solely on the trajectory of the leader robot for generating observations. We model the human using a redundant, partially-observable dynamical system and we infer the posture using a standard particle filter. We compare our approach with postures from a commercial motion capture system and also two least-squares optimization approaches for human inverse kinematics. The results reveal that the proposed approach successfully estimates human postures and ergonomic risk scores comparable to those estimates from gold-standard motion capture.

Source: IEEE International Conference on Automation Science and Engineering (CASE)

DOI: 10.1109/case49439.2021.9551471

Authors: Amir Yazdani, Roya Sabbagh Novin, Andrew Merryweather, Tucker Hermans

Institutions: University of Utah, Nvidia (United States)

Language: English

Topic: Ergonomics and Musculoskeletal Disorders

Subfield: Social Psychology

Field: Psychology

Domain: Social Sciences

Open Access status: green

Funder: Defense Advanced Research Projects Agency

Award: G1723748841