End‐Effector Pose Estimation in Complex Environments Using Complementary Enhancement and Adaptive Fusion of Multisensor

Abstract

Redundant manipulators are suitable for working in narrow and complex environments due to their flexibility. However, a large number of joints and long slender links make it hard to obtain the accurate end-effector pose of the redundant manipulator directly through the encoders. In this paper, a pose estimation method is proposed with the fusion of vision sensors, inertial sensors, and encoders. Firstly, according to the complementary characteristics of each measurement unit in the sensors, the original data is corrected and enhanced. Furthermore, an improved Kalman filter (KF) algorithm is adopted for data fusion by establishing the nonlinear motion prediction of the end-effector and the synchronization update model of the multirate sensors. Finally, the radial basis function (RBF) neural network is used to adaptively adjust the fusion parameters. It is verified in experiments that the proposed method achieves better performances on estimation error and update frequency than the original extended Kalman filter (EKF) and unscented Kalman filter (UKF) algorithm, especially in complex environments.

Shape Sensing of Hyper-Redundant Robots Using an AHRS IMU Sensor Network

“…A Root Mean Square Error (RMSE) error between 0.4–0.47 deg and between 1.17–1.22 deg was reported for yaw and pitch angle, respectively, for different elements of the robot. In [ 41 ], Luo et al proposed a fusion pose estimation method (RBF-UKF) for a redundant robot that is based on a multisensory fusion approach that is applied in two phases: a “pre-enhancement” fusion phase where information from a RGB-D camera and a MARG (Magnetic, Angular Rate, and Gravity) sensor are fused with the information from an optical encoder and an adaptive fusion phase where the pose of the robot is predicted and various parameters are adaptively adjusted. Their experimental setup consists of eight modules with 1-DoF serially connected as a redundant manipulator.…”