Visual Robot Guidance In Dynamic Environment Using Quadtree Data Structure And Parallel Processing

Abstract

To guide a robot in a time varying environment, the initially planned path must be updated as the contents of the scene change. This research addresses the problem of planning a collosion free path for efficient visual guidance in scenes involving moving obstacles. Here we present a time efficient path planing based on quadtree data structure and parallel processing techniques, which is applied to the top view of a dynamic environment. Motion analysis is performed on a sequence of images taken from the top view of the scene in certain time intervals. The extracted motion information is then used for selecting the best path as the shortest distance nearer to the obstacle which is moving away from a reference point (e.g., camera, robot or a segment of initially planed path).