Research On Key Technology Of Autonomous Movement In Complex Environment For Wheeled Mobile Robots

With the rapid development of Intelligent Mobile Robot Technology, the wheeled mobile robots are handling many tasks instead of person, for satisfying the demand in scientific expedition, Removal of Dangerous, relief, Battle, and Intelligent traffic areas.Mostly of working range for wheeled mobile robots are outdoor environments. The localization and tele-operation become very hard because of the complex environ-ments. Therefore, It's very urgent and important for mobile robots to improve the ability of self-localization and motion control in uncertain environments.All the works in the dissertation are sponsored by project fund from National Natural Science Foundation of China. In this paper, the movement principles, method of self localization and motion control were studied.The dissertation is mainly consists of two components. In the first part, researches are focused on the generally complex environments. such as uneven terrain or narrow spaces. Wheeled Skid-Steer Mobile Robots (WSMR) can fit situations in these environments well. WSMRs have simply mechanism, robust reliability,good driving and passing ability. the movement performance of autonomous mobile robots can be improved based on the research of WSMR's theorem. In the second part, facing at mountain roads which are the classic outdoor environments, a Digital Elevation Model aided self-location method is presented. the self-navigation ability for mobile robot without GPS signals can be improved using this method.Wheeled Skid-Steer Mobile Robots are driven by four fixed wheels. They are nonlinear, time-varying, Multi-variable and strong-coupling systems. The model of WSMR by simple kinematics and dynamics models can not be expressed easily. In this dissertation, a slippage model was built for WSMR robots,the effects of slippage are considered fully in analyzing the kinematics features. Effects are also discussed for stationarity in dynamic analysis caused by slippage factors. the paper present and derive the stationarity criterion, and obtained the boundary conditions for robots to keep stationarity when moving and turning in high speed.Estimation poses by fusing information from multi-sensors mounted on the robots are general method for mobile robots self-localization. Although Global Positioning System (GPS) are used widely in mobile robots outdoor localization, the technology of localization without GPS are still very crucial. this paper compose information from Encoders, Digital Compasses, Inertial Measurement Units and Attitude and Heading Reference Systems to localization using Extended Kalman Filter Based method. Slippage model and measurement error models are introduced into EKF to correcting estimation errors in real-time. The experimental results imply that this combined method can improve precision of localization on uneven terrain effectively.Challenges to Motion Control are posed Owing to the uncertainty of WSMR model. This paper design an adaptive control method in this dissertation to simultaneously estimate the wheel/ground contact friction information and control the robot to follow a desired trajectory. A Lyapunov based convergence analysis of controller and the estimation of the friction model parameter is presented. Paper also discuss how to control a WSMR robot to turning accurately in high speed by stunt movement in this section.The dissertation present a Digital Elevation Model aided self-location method in this dissertation. when robots are running on mountain roads. The regular method for self-localization works hardly without GPS signals. 3D network of roads are obtained from DEM models and remote sensing images stored in the robot memory. The global position can be localized in real-time by matching the geometry curvature features of movement trajectories and road network.In order to support above researches, this paper build two WSMR platforms, named TamuBot and NKRover,respectively. The self-localization experiments on terrain surface are implemented based on TamuBot Robots, and the stunt control experiments are implemented based on NKRover robot. A Trajectory Tracking system based on global vision was built for testing the precision of localization. this dissertation also implement some experiment to validate localization method based on geometry feature matching for mobile robot in mountain roads environments.