Efficient Goal Seeking for Robots in Unknown Environments with Wall like Obstacles
V. R. Jisha, Debasish Ghose · Proceedings of International Conference on Intelligent Unmanned Systems · 2010
In this paper, we consider the problem of frontier based goal seeking by robots in unknown environments but with the location of the goal known approximately. The environment is assumed to be cluttered with wall like obstacles whose locations are not known a priori. Frontier cells, which are on the boundary between explored space and unexplored space, are considered to be the best candidate positions to move to, for efficiently navigating in unknown environments. Our algorithm efficiently chooses the best candidate frontier cell, having maximum “goal seeking index”, and it is capable of escaping from “trap” present in environments with wall like obstacles, with reduced repeated coverage through already explored region, unlike other reactive goal seeking algorithms. Simulations show that the algorithm can find a route, with the minimal number of moves, to a goal in a fully unknown environment. In this paper, we also demonstrate the performance of the proposed algorithm by actual robots in a laboratory environment.