Grid roadmap based ANN corridor search for collision free, path planning

The probabilistic roadmap (prm) is a force for path planning in static environments. altogether,a small change in obstacle position may lead to the regeneration of a new road map, invalidating collidingnodes and edges, and then causing a search for a new collision free path. these steps take a considerableamount of time for processing. in this article, a new method, based on the grid roadmap (grm), is proposedto mitigate the desired time of path planning. by the suggested roadmap and implementation of anartificial neural network (ann) for a corridor search, a fast path planning method is achieved, whichoperates on static, dynamic and unseen environments.