未知环境中移动机器人导航控制理论与方法（英文版）-JobPlus

[书籍] 未知环境中移动机器人导航控制理论与方法（英文版）

作者: 蔡自兴

出版社: 科学出版社

简介: The issue of the navigation control theory and method for mobile robot in unknown environments is one of the international frontier research topics and is also one of the hot spot issues and the most difficult problems in the development of the intelligent robotics. The intelligent mobile robot is a kind of robotic system that can release autonomous navigation motion towards its object in the environment with obstacles and completes the desired tasks by means of sensing its environment and itself situation through sensors and other advanced techniques. The contents of this book deal with the navigation control theory and method for mobile robot in unknown environments including the architecture， localization and mapping， obstacle detection， navigational strategy and fault diagnosis of mobile robot system etc. The breakthrough of these technologies in the book will produce positive influence in many fields. It will promote the research of many frontier discipline such as cognition science， pattern recognition， nonlinear control. It will drive the development of mobile robot navigation control system for spaceflight， ocean， military， architecture， traffic， industry and service and so on. It will also build theoretical and technical foundation for the application of mobile robot system such as unmanned exploring vehicles， unmanned emission car， unmanned transporter in the field of spaceflight， military， under ocean and nuclear industry. During 2003 to 2008， I presided over the key project of National Natural Science Fund of China（NSFC）， titled as "Navigation Control Theory and Method of Mobile Robot under Unknown Environment"（Grant No. 60234030） and the key project of National Basic Research Fund of China， titled as "Research on Theories and Methods of Synergetic Searching and Reconfiguration for Heterogeneous Multi-mobile Agents"（Grant No. A4120060159）， which have passed the concluding acceptance checks and were comprehensive evaluation of outstanding in January 2007 and May 2009 respectively.

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