Mobile Robot Autonomous Navigation Based On Cognitive Map

Robots are mending their pace to fuse into daily life of human being recently. Robots are expected to not only have ability of safe navigation but also are more intelligent and friendly to communicate with human being. But the state-of-the-art in mobile robotics is far behind expectation. The greatest challenge at the moment for mobile robotics is how to endow robots with the capacity to exhibit a greater degree of spatial awareness. The root-cause of the problem lies in the deficiency of semantic content in mobile robot representations. These problems form the core motivations of this thesis.The work presented here is an in-depth study of the problems of environment apperception, navigation and environment intercommunion. It studied the relative problems step by step. Inspired by biology cognitive mapping, a mobile robot cognitive mapping algorithm based on multi-sensor and joint-sequent particle filter is proposed by referring the strongpoint of biologic and probabilistic navigation and using the common sensors: odometer, vision and laser range finder. The algorithm can build a global, correlative, active map. Thirdly a navigation framework is presented based on the cognitive map: i.e. solving the problems of global localization, path planning and ending docking based on the cognitive map. Lastly three key technologies for intercommunion between the robot and the environment in the map are discussed which can build a reliable foundation for intercommunion between the robot and the environment.The problems studied in this paper derive from the National Natural Science Foundation of China"Research on Mobile Robot Indoor Navigation Technology Based an Inaccurate Map", and the National 863 High-tech Research and Development Plan of China"Collaboration and Competition Mechanism for Distributed Multi-robots and its Application Techniques". The contributions are discussed in detail as follows:Firstly, the SIFT(Scale Invariant Feature Transform) algorithm which is used to represent environment is discussed, and a DD-BBF(Double-Direction Best-Bin-First) based SIFT feature matching method is presented to solve the data matching problem in 3D reconstruction of space efficiently; A PCSM(Polar Coordinates Scan Matching) method is discussed for the robust laser data matching.Secondly, a mobile robot cognitive mapping algorithm based on multi-sensor and joint-sequent particle filter is studied.As to build the cognitive map, an improved RBPF(Rao-Blackwellized particle filter) and FastSLAM are used to implement a jointSLAM. A more precise vision-laser joint metric map is built by this method. When building the joint metric map, the map is partition into many groups of submaps by a special partition rule. Each submap group is defined as a place, and every place is encoded with semantic conception which comes from a tutor semantic sequence. When the semantic map is built, the cognitive map is founded at the same time.Thirdly, a navigation method based on cognitive map is studied to solve the problem of global localization, HMM based place recognition, path planning, place based navigation and precise docking. The highlight point of the method is that it can well instruct the real robot application, and endow mobile robots with the abilities of flexible and precise navigation in large scale environment. It also provide a new thought of solving the navigation problem.Finally, object surveillance and tracking method based on the cognitive map are discussed, and a vision network with new background subtraction for non-stationary scenes is used to extend the observation range of the mobile robot. A homography matrix is used to settle the calibration relationship between the robot and the vision network; a monocular vision based object following method is presented which uses SIFT to judge the distance and direction of the object; as to human localization and tracking, a heterogeneous sensor sequence filter based on laser-vision is presented to locate and track the people efficiently. These works can build a reliable foundation for intercommunion between the robot and the environment. lastly, the hardware and software of the system are introduced.