Abstract
Abstract Robot Motion Planning (RMP) has been a thrust area of research in computing due to its complexity, since RMP in dynamic environments for a point robot with bounded velocity is an NP-hard problem. This paper is a critical review of the major contributions to RMP in dynamic environments. Between 1985 and 2015 the focus has changed from the classical approach to a heuristic approach. For velocity based motion planning in dynamic environments, ICS — AVOID (Fraichard and Asama, 2004, also see Section 2.4.4) is the safest approach which means that this method have the capability of for an autonomous robotic system to avoid collision with the obstacles in the environment. Other important approaches include artificial potential field based, artificial intelligence based, probabilistic based RMP and applications in areas of Agent systems and computer geometry. Classification of the RMP literature on the basis of the techniques and their performance has been attempted.
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