Performance Analysis of Different Optimal Path Planning Bug Algorithms on a Client Server Based Mobile Surveillance UGV

Abstract

Path planning algorithms have drawn attention of researches in the last few years. Mobile path planning robots are considered to be very useful for surveillance and military use. Efficiency parameters include distance and time taken by the UGVs to reach the target destination in both known (global) environment and real time unknown (local) environment. Pre-planned trajectories need complete static information of the respective environment for a successful implementation. Runtime dynamic obstructions are handled using different sensing devices. This paper explains the implementation of various bug algorithms of which point bug is considered to be the most efficient and effective with respect to the time and cost on a mobile UGV. The UGV is controlled through Client Server modeling and input from ultrasonic sensors which have played a vital role in surveillance. Navigation criterion has been accomplished using Global positioning module and digital compass. A complete system is capable of reaching destination point given by a client user with an efficient path planning algorithm. We have compared the performance of different bug algorithms in static and dynamic local environments in terms of the shortest collision free distance traversed towards a given target location. The experimental results are compared with simulations and previous research along with discussion on the strengths and weaknesses of these algorithms under complex environments.