Research On Key Technologies Of Localization Method For Walking Assistant Robot

The walking assistant robot (WAR) is a special kind of service robot which canassist the elderly to walk. The reason behind the development of the WAR is toreplace traditional walking aids such as crutches and the walking frame. Moreover,besides the walking assistant function, it also offers more intelligent functions, such ashealth condition monitoring, voice interaction, navigation, user identification, userprogram reminders, information services, etc. The localization system which is animportant component of WAR acts as a base for many intelligent functions. Thisdissertation covers a study of the localization system and the research contents hereinare as follows.1，The map of the environment is key for a-priori knowledge for the autonomouslocalization and navigation function of the WAR. Although2D maps can meet theneeds of the robot for self-localization, its drawback of uncertainty in the verticaldirection made it unable to meet the demand for autonomous navigation in narrowenvironment such as would be encountered in a typical home setting. Traditional3Dmapping methods need expensive equipment and the operation is complex. In thisdissertation, we studied the3D mapping method based on RGB-D (color-depth)sensor and proposed a map creation method based on improved “KinectFusion”,enabling users to more easily re-create the family environment. This dissertationadvances the KinectFusion algorithm with two improvements. On the one hand use ismade of the environment feature to point out matching edges and consequentlyimprove its positioning robustness, on the other hand ground point cloud is preset inthe point cloud model to reduce the accumulated error and hence improve accuracy. Additionally, a sub-map stitching method is proposed to solve the limitation of thesize of the map built by “KinectFusion”, based on the ground consistency and thecalibration marker.2，The working style of WAR is flexible and there is often the need to switch betweenpassive control and autonomous operation, especially when its operating environmentswitches between indoor and outdoor. In this manner the continuous positioning isfrequently interrupted. This requires the robot to have a strong global positioningfeature and the ability to quickly re-orient itself. In this dissertation, the global searchpositioning dimensionality reduction method is proposed using the rotationalinvariants for the initial search for a viable space robot position, and subsequently inthe direction of the search space to get the orientation of the robot thus greatlyenhancing the efficiency of its global positioning.3，The traditional2D continuous location tracking method is mature, but it requiresthe use of laser sensors on the WAR which is unfavorable for purposes of minimizingcost. This article attempts to employ an RGB-D sensor instead of a2D laser sensor forcontinuous positioning. The main idea is to exclusively use RGB-D information as a3D point cloud for position tracking, making up for its disadvantage by selecting asmall field of view in the horizontal direction. Traditional3D point cloud registrationalgorithm, cannot fulfill the demands of real-time location. This dissertation presentsa study of three-dimensional point cloud registration using RGB-D sensors, andproposes a fast3D point cloud registration method based on3DLUT (Lookup Table)algorithm. This method can not only achieve real-time processing speeds, but also hasa high degree of accuracy.4，The human positioning function is a very important function and plays a great roletowards improving user-friendliness of the WAR. The traditional laser-basedlocalization method lacks the capacity to identify the user hence cannot work well inan environment full of people. Vision-based methods on the other hand are verysensitive to changes in light characteristics hence have low robustness. In thisdissertation, we propose a people positioning based on omni-dimensional visual and infrared markers for identification. The test results proved it to be stable both indoorsand outdoors. For the omni-directional vision system (odvs) calibration, we proposeto use the image of the base circle contour to compute the posture of the mirror anddetermine the internal parameters, and then use the center of the mirror to determinethe true solution from two possibilities. Next, we propose using a special uniquesolution-Non-SVP P3P method–to determine the external parameters. Thecalibration method is simple and fast, and not only places low demand on thecalibration object, but also has high accuracy.5，Using the solutions for these key technologies, the hardware and software systemfor the WalkMate III WAR was designed and built. We proposed to use the modulebased system model to make the development of the software system easier, and makethe structure of the system clearer. Finally two intelligence functions were tested inorder to evaluate the Feasibility of the whole system. These are the users findingfunction (when the robot power is switched on) and user tracking.The domestic research of WAR has just started. Because of its’ special workingmethods and have many differences with general mobile service robots, there aremany issues to be resolved. The purpose of this study is: research on the localizationsystem of WAR, and solve several key issues. The research contained in thisdissertation should be useful towards helping the WAR enter the practical stage assoon as possible, laying the foundation for solving the problem of caring for theelderly caused by aging population problem. Eventually this and has important socialsignificance and results in economic value.