Obstacle Avoidance Algorithms: A Review

Abstract

Abstract It is only with time that the efficiency or the effectiveness of the algorithms for obstacle avoidance gets better, and experiences of any kind can be inferred for the betterment of the knowledge on this domain. For a mobile robot navigating its way from starting point to an ending point while traversing through deterrents, needs to divide the problem into sub problems. It fundamentally involves, sensory data interpretation, choosing apt algorithm based on the objective function, and configuring the mobile robot accordingly to attain desired output. In this paper, few essential classifications for obstacle avoidance and robot navigation algorithms are discussed. Importance of the hardware aspect of the robot is undeniable. A set of algorithms were classified into 2 main classifications which are further divided into sub classifications in an arranged and concise manner. This information can be used to develop a suitable model for the given problem. Understanding fundamental ideas or strategies would allow in developing a novel extended strategy, although few specialized strategies are saturated, nevertheless can still be used as valuable alternatives. These alternatives may involve algorithms which have paramount potential, per se which are interestingly similar to the functioning of a brain, nature-inspired, etc.