Automatic Docking Optimization Method of Bed and Chair Based on Multi-sensor Information Fusion

Abstract

Automatic docking is a basic function of intelligent wheel-chair bed system. In order to achieve high-precision docking between intelligent wheelchair and U-shaped bed, this paper proposes an optimization method of automatic docking between bed and chair based on multi-sensor information fusion. By installing a variety of sensors, such as depth vision camera and lidar ranging, there is usually cross sensitivity when multiple sensors work together. Based on real sensing technology, wireless sensor network technology and lidar ranging equipment l, a dynamic Bayesian multi-mode information fusion method with asynchronous constraints is proposed. Wireless sensors are used to collect wheelchair pose information in real time. By analyzing the characteristics of the observation information of various sensors, the complementary and redundant information of various sensors in space and time is combined according to optimization criteria. The data fitting between multi-sensor information is carried out efficiently and quickly by surface fitting method. Based on the extended Kalman filter algorithm, the information fusion of IMU and combined sensing unit is realized, and the analysis model is established. Finally, the feasibility of the method is verified by Matlab simulation and the use of Gazebo in ROS to build a simulation experiment environment for fusion algorithm verification.