Abstract
Path optimization is a vital aspect in the design of Mobile Robot, which saves precious time and energy. In this paper, Autonomous Mobile Robot (AMR) is imitated the Grey Wolf searching possessions and navigated to reach the target, beneath collision free, in various environments with different shaped obstacles. Grey wolves succeed in hunting through packs. These wolves glue together forever and follow the leader of the pack with communicating among them through howl. GWO algorithm has a capability to flee from local optima and facilitates to reach towards global maxima. The simulation and experiment results are compared against Probabilistic Road Map method, and proved that Navigation of AMR with GWO algorithms is robust to overcome sharp edged obstacles. The Integration of Safe Boundary Algorithm with GWO algorithm yielded better results.
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