TY - GEN
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
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/9/28
Y1 - 2020/9/28
N2 - 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.
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.
UR - http://www.scopus.com/inward/record.url?scp=85099343195&partnerID=8YFLogxK
U2 - 10.1109/RCAR49640.2020.9303303
DO - 10.1109/RCAR49640.2020.9303303
M3 - Conference contribution
AN - SCOPUS:85099343195
T3 - 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020
SP - 515
EP - 520
BT - 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020
Y2 - 28 September 2020 through 29 September 2020
ER -