The mobile robot path planning depends on sensing the data, map building and planning the path according to the prescribed environment. Many researchers have followed different techniques to get the optimal path. In the Earlier days Mathematical model has been developed to get the optimal path but the result obtained was very poor. After that, so many Soft computing techniques have been developed, but the major drawback is that they are more time to find the optimal path. Sometimes these algorithms fall in local optima during execution. This paper Deals with mobile robot path planning using two nature inspired meta-heuristic algorithms namely cuckoo-search and bat algorithm in the unknown or partially known environment. Cuckoo search is based on the parasitic behaviour of the cuckoo, and the bat algorithm is based on the Echolocation behaviour of the bats. The best qualities in the cuckoo-search and the bat algorithm are combined to obtain the optimal path. Proposed method takes less time to reach the target as compared to individual algorithms. The efficiency of this work has been tested in Matlab environment.
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