A Dual-six-dimensional Force Sensors Calibration Method for pHRI based on Ridge Regression

Huanyu Tian; Xingguang Duan; Tengfei Cui; Jin Wang; Qingxin Shi; Junjie Dong

doi:10.1109/RCAR49640.2020.9303303

A Dual-six-dimensional Force Sensors Calibration Method for pHRI based on Ridge Regression

Huanyu Tian, Xingguang Duan^*, Tengfei Cui, Jin Wang, Qingxin Shi, Junjie Dong

^*Corresponding author for this work

School of Mechatronical Engineering

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

During robot teaching and physical human-robot interaction (pHRI), external forces and torques are required to be measured. However, the gravity acted on collaborative tools is a known-structure but unknown parameters input for pHRI systems. It is an essential process that gravity parameters need to be estimated and compensated using six-dimension force sensor calibration in a pHRI linear system based on Newton-Euler (NE) equation. In the previous work, the collaborative robot (cbot) system interacting with human and environment has 2 orthogonal installation six-dimension force sensors, where sensors' biasing and static wrenches exist. To solve this problem for both six-dimension force sensors in the same time, a regression algorithm in 3 steps is proposed using ridge regression and least square regression.

Original language	English
Title of host publication	2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	515-520
Number of pages	6
ISBN (Electronic)	9781728172927
DOIs	https://doi.org/10.1109/RCAR49640.2020.9303303
Publication status	Published - 28 Sept 2020
Event	2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020 - Virtual, Asahikawa, Hokkaido, Japan Duration: 28 Sept 2020 → 29 Sept 2020

Publication series

Name	2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020

Conference

Conference	2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020
Country/Territory	Japan
City	Virtual, Asahikawa, Hokkaido
Period	28/09/20 → 29/09/20

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10.1109/RCAR49640.2020.9303303

Cite this

Tian, H., Duan, X., Cui, T., Wang, J., Shi, Q., & Dong, J. (2020). A Dual-six-dimensional Force Sensors Calibration Method for pHRI based on Ridge Regression. In 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020 (pp. 515-520). Article 9303303 (2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RCAR49640.2020.9303303

Tian, Huanyu ; Duan, Xingguang ; Cui, Tengfei et al. / A Dual-six-dimensional Force Sensors Calibration Method for pHRI based on Ridge Regression. 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 515-520 (2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020).

@inproceedings{fcff77c378044396be5aa0d4c0cee379,

title = "A Dual-six-dimensional Force Sensors Calibration Method for pHRI based on Ridge Regression",

abstract = "During robot teaching and physical human-robot interaction (pHRI), external forces and torques are required to be measured. However, the gravity acted on collaborative tools is a known-structure but unknown parameters input for pHRI systems. It is an essential process that gravity parameters need to be estimated and compensated using six-dimension force sensor calibration in a pHRI linear system based on Newton-Euler (NE) equation. In the previous work, the collaborative robot (cbot) system interacting with human and environment has 2 orthogonal installation six-dimension force sensors, where sensors' biasing and static wrenches exist. To solve this problem for both six-dimension force sensors in the same time, a regression algorithm in 3 steps is proposed using ridge regression and least square regression.",

author = "Huanyu Tian and Xingguang Duan and Tengfei Cui and Jin Wang and Qingxin Shi and Junjie Dong",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020 ; Conference date: 28-09-2020 Through 29-09-2020",

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doi = "10.1109/RCAR49640.2020.9303303",

language = "English",

series = "2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Tian, H, Duan, X, Cui, T, Wang, J, Shi, Q & Dong, J 2020, A Dual-six-dimensional Force Sensors Calibration Method for pHRI based on Ridge Regression. in 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020., 9303303, 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020, Institute of Electrical and Electronics Engineers Inc., pp. 515-520, 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020, Virtual, Asahikawa, Hokkaido, Japan, 28/09/20. https://doi.org/10.1109/RCAR49640.2020.9303303

A Dual-six-dimensional Force Sensors Calibration Method for pHRI based on Ridge Regression. / Tian, Huanyu; Duan, Xingguang; Cui, Tengfei et al.
2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020. Institute of Electrical and Electronics Engineers Inc., 2020. p. 515-520 9303303 (2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - A Dual-six-dimensional Force Sensors Calibration Method for pHRI based on Ridge Regression

AU - Tian, Huanyu

AU - Duan, Xingguang

AU - Cui, Tengfei

AU - Wang, Jin

AU - Shi, Qingxin

AU - Dong, Junjie

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AB - During robot teaching and physical human-robot interaction (pHRI), external forces and torques are required to be measured. However, the gravity acted on collaborative tools is a known-structure but unknown parameters input for pHRI systems. It is an essential process that gravity parameters need to be estimated and compensated using six-dimension force sensor calibration in a pHRI linear system based on Newton-Euler (NE) equation. In the previous work, the collaborative robot (cbot) system interacting with human and environment has 2 orthogonal installation six-dimension force sensors, where sensors' biasing and static wrenches exist. To solve this problem for both six-dimension force sensors in the same time, a regression algorithm in 3 steps is proposed using ridge regression and least square regression.

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Tian H, Duan X, Cui T, Wang J, Shi Q, Dong J. A Dual-six-dimensional Force Sensors Calibration Method for pHRI based on Ridge Regression. In 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 515-520. 9303303. (2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020). doi: 10.1109/RCAR49640.2020.9303303

A Dual-six-dimensional Force Sensors Calibration Method for pHRI based on Ridge Regression

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