Estimation of Payload Inertial Parameters from Human Demonstrations by Hand Guiding

TL;DR

This paper presents a method for estimating a robot's payload inertial parameters during hand guiding demonstrations, enabling easier programming of in-contact motions without dedicated calibration, thus improving flexibility and user-friendliness.

Contribution

It introduces a novel approach to estimate payload inertial parameters from human demonstrations, reducing calibration requirements for non-expert users.

Findings

Payload mass estimation is accurate.

Center of mass and inertia tensor estimates are affected by noise.

Sufficient payload accelerations are necessary for accurate estimation.

Abstract

As the availability of cobots increases, it is essential to address the needs of users with little to no programming knowledge to operate such systems efficiently. Programming concepts often use intuitive interaction modalities, such as hand guiding, to address this. When programming in-contact motions, such frameworks require knowledge of the robot tool's payload inertial parameters (PIP) in addition to the demonstrated velocities and forces to ensure effective hybrid motion-force control. This paper aims to enable non-expert users to program in-contact motions more efficiently by eliminating the need for a dedicated PIP calibration, thereby enabling flexible robot tool changes. Since demonstrated tasks generally also contain motions with non-contact, our approach uses these parts to estimate the robot's PIP using established estimation techniques. The results show that the estimation of the payload's mass is accurate, whereas the center of mass and the inertia tensor are affected by noise and a lack of excitation. Overall, these findings show the feasibility of PIP estimation during hand guiding but also highlight the need for sufficient payload accelerations for an accurate estimation.