Research On Mapping And Automated Navigation In Indoor Environment For Intelligent Wheelchair

With the increasing pressure of the aging population and the increasing number of the disabled population,it has become an urgent social problem to improve the mobility of the elderly and the disabled.Intelligent wheelchair as an important branch of helping the old disabled products by domestic and foreign researchers attention.Indoor building and autonomous navigation as the basic function of intelligent wheelchair,which involves the key technologies are SLAM(Simultaneous Localization And Mapping),global localization and path planning.This paper focuses on the key technologies involved in the indoor mapping and autonomous navigation of the intelligent wheelchair,the main work is as follows:First of all,the mathematical model of SLAM is studied.For the mapping algorithm based on filter can't build a global consistent map in large environment,a mapping algorithm based on graph optimization is proposed.The algorithm uses correlative scan matching to achieve frame matching and uses the local map matching method to complete the loop-closure detection,and uses the pose optimization to eliminate the accumulated error.By simulation,the algorithm can build a global consistent map in a large indoor environment.Secondly,the basic Monte Carlo localization algorithm is studied.For the basic Monte Carlo localization algorithm which is applied to global positioning has some problems,such as the slow convergence of particles,the degradation of particles and the lack of particles,an improved Monte Carlo localization algorithm is proposed.The extended Kalman filter is used to estimate the pose of the motion prediction process,and the adaptive mechanism is introduced into the resampling process to adaptively resample and adjust the number of particles.By simulation,the algorithm improves the convergence speed of particles and the reliability of localization.Thirdly,the A* algorithm is studied.For the A* algorithm wh ich is applied to global path planning has some peoblems,such as low planning efficiency and there are many turning points in the planning path,a double smoothing A* algorithm for global path planning is proposed.The efficiency of global path planning i s improved,and a smooth global path is obtained.DWA algorithm is also studied for local path planning,and based on the combination of global path planning and local path planning,a hybrid path planning method based on improved A* algorithm and DWA algorithm is proposed.By simulation,the proposed method can obtain a better and smoother global path in the known environment,and can also avoid obstacles in the local changing environment.Finally,the experiment platform of intelligent wheelchair is buil t,including the intelligent wheelchair hardware platform and the ROS based autonomous navigation system.The indoor mapping,localization and autonomous navigation experiments of the intelligent wheelchair were conducted in indoor complex environments and simple environment,the experimental results show that the proposed method has some effects and the intelligent wheelchair can realize the mapping,positioning and autonomous navigation function in different indoor environments.