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

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.