Force/Torque Sensor Measurements for Estimating the Mass Center of an Unknown Robot End Effector

Introduction

This dataset was created as part of a study on a novel geometric method to estimate the mass center of an unknown robot end effector. A conference paper from this study was accepted for the 2024 IEEE International Conference on Real-time Computing and Robotics (RCAR 2024) [1]. 

A force/torque sensor (FTS) was attached to the flange of a serial robot, and an unknown end effector was attached to the FTS. Vougioukas [2] described a method to calculate the FTS bias, as well as the mass and mass center using Least Squares Estimation (LSE). His method requires FTS samples from 24 specific orientations of the sensor. See his paper for a description of this calibration method. This dataset was used to evaluate and compare the estimates from the proposed geometric technique to the estimates from Vougioukas' method. 

The hardware used to generate this dataset were:

KUKA Agilus KR6 R900 sixx (KUKA AG, Germany)

ATI Gamma FTS (ATI Industrial Automation, Inc., USA)

ATI Netbox (ATI Industrial Automation, Inc., USA)

Dataset

The robot was used to move the FTS with high precision and accuracy as required by the calibration method from Vougioukas. Each line in the dataset is the measured force and torque, the direction of gravity in the FTS frame, and the orientation of the FTS expressed in the world frame. The lines are ordered and correspond to the orientations described by Vougioukas in his paper. 

fx, fy, fz - The force components as measured by the FTS.tx, ty, tz - The torque components as measured by the FTS.gx,gy,gz - The direction of the gravitational vector in the FTS frame.r11, r12, r13, r21, r22, r23, r31, r32, r33 - The components of the rotation matrix that represents the FTS orientation in the world frame.

References

[1] A. Skrede, "A Geometric Perspective on Moment Arm Estimation Using Force/Torque Sensors", Accepted for the 2024 IEEE International Conference on Real-time Computing and Robotics (RCAR), Ålesund, Norway, June 2024 

[2] S. Vougioukas, “Bias Estimation and Gravity Compen- sation For Force-Torque Sensors,” in Recent Advances in Simulation, Computational Methods and Soft Computing. WSEAS Press, 2001, pp. 82–85.