Position estimation for mobile robot using sensor fusion

Proposes a position estimation method and a path generation between current position and goal point for mobile robots. Dead reckoning has been commonly used for position estimation. However this method has inherent problems because it also accumulates estimation errors. In this paper, the authors propose a new method to increase the accuracy of estimated positions using a matching method which is applied with a least squared scheme. This approach uses features, such as corner points and edges of the object in the task environment instead of land-marks. Also, the authors discuss how to establish an environment database and propose a genetic algorithm in order to find an optimal path. It is shown that: it is possible to estimate the position of mobile robot precisely, errors are not cumulated, and the path generation method is very fast