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Traditional sensor network and robot navigation are based on the map of detecting the fields available in advance.The optimal algorithms are developed to solve the energy saving,the shortest path problems,etc.However,in the practical environment,there are many fields,whose map is difficult to get,and needs to be detected.In this paper a kind of ad-hoc navigation algorithm is explored,which is based on the hybrid sensor network without the prior map in advance.The navigation system is composed of static nodes and dynamic nodes.The static nodes monitor the occurrances of the events and broadcast them.In the system,a kind of algorithm is to locate the robot,which is based on cluster broadcasting.The dynamic nodes detect the adversary or dangerous fields and broadcast warning messages.The robot gets the message and follows ad-hoc routine to arrive where the events occur.In the whole process,energy saving has been taken into account.The algorithms,which are based on the hybrid sensor network,are given in this paper.The simulation and practical results are also available.
Traditional sensor network and robot navigation are based on the map of detecting the fields available in advance. The optimal algorithms are developed to solve the energy saving, the shortest path problems, etc. However, in the practical environment, there are many fields, whose map is difficult to get, and needs to be detected. This paper a kind of ad-hoc navigation algorithm is explored, which is based on the hybrid sensor network without the prior map in advance. navigation system is composed of static nodes and dynamic nodes. The static nodes monitor the occurrances of the events and broadcast them.In the system, a kind of algorithm is to locate the robot, which is based on cluster broadcasting. The dynamic nodes detect the adversary or dangerous fields and broadcast warning messages The robot gets the message and follows ad-hoc routine to arrive where the events occur. In the whole process, energy saving has been taken into account.The algorithms, which are based on the hybrid sensor networ k, are given in this paper. The simulation and practical results are also available.