Human grasp position estimation for human-robot cooperative object manipulation

摘要

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. (C) 2020 Elsevier B.V. All rights reserved.