Human grasp position estimation for human–robot cooperative object manipulation
Artikel i vetenskaplig tidskrift, 2020

This paper addresses the problem of human grasp position estimation in a physical human–robot object handling scenario. The problem is formulated as a linear regression by considering the human grasp position and their exerted torque as unknown parameters. We propose a modified least-squares algorithm to estimate the parameters by evaluating the quality of the estimates based on the assumption that the parameters should remain constant for a period of time. The solution is model-agnostic in terms of the human force/torque model – requiring only force/torque measurements on the robot side and proprioception – and is model-based in terms of the object model. The proposed grasp position estimation method is compared statistically with a conventional contact point estimation method using the collected experimental data. Moreover, the performance of the developed method is evaluated through various scenarios of physical human–robot interaction.

Estimation

Physical human–robot interaction

Object manipulation

Collaborative robots

Författare

Ramin Jaberzadeh Ansari

Chalmers, Elektroteknik, System- och reglerteknik, Mekatronik

Giuseppe Giordano

Zenuity AB

Jonas Sjöberg

Chalmers, Elektroteknik, System- och reglerteknik, Mekatronik

Yiannis Karayiannidis

Chalmers, Elektroteknik, System- och reglerteknik, Mekatronik

Robotics and Autonomous Systems

0921-8890 (ISSN)

Vol. 131 103600

Ämneskategorier

Biomedicinsk laboratorievetenskap/teknologi

Reglerteknik

Signalbehandling

DOI

10.1016/j.robot.2020.103600

Mer information

Senast uppdaterat

2020-08-06