HRWP: A hierarchical randomwalk path planner for post-disaster Mobile Ad-hoc Rescue Network

Path planning is a critical task for search and rescue mission in Mobile Ad-hoc Rescue Network in natural or unnatural catastrophes. However, most existing path planning schemes fail to cope with the challenges in post-disaster map environment due to its increased complexity and uncertainty. To address these issues, we propose a Hierarchical Random Walk based path Planner (HRWP). In HRWP, Regular Grid and Voronoi Diagram are used to model the map, and uncertain map segments are assigned uncertain cost using random variables. The hierarchical random walk is then designed to generate the optimal path using probabilistic accept-reject. In this way, results of HRWP can significantly reduce the risk of uncertainty and converge to the optimal path. Using a combination of analytical modeling and extensive simulations we show that HRWP outperforms existing path planer and mobility schemes, and performs well in complicated environments.