Abstract
In this paper a method has been proposed to identify the lowest cost path to reach a destination point from a source point. However, unlike most of the colloquial graph traversal problems, here the destination point is dynamic— not fixed, i.e. changes its position with time. This causes the chaser to update its path planning accordingly, by constantly sensing the position of the destination. During the progression, the chaser may has to side-track many obstacles, for which, in addition to the algorithm for reaching dynamic target through optimal path, two techniques have also been proposed for avoiding obstacles. The proposed method has been compared with the existing techniques for reaching dynamic target such as D*, D* Lite etc. and also with the existing obstacle avoidance techniques such as Bug, NHNA etc., mainly used in Robotics.
Highlights
In GIS finding shortest [3] path between two points plays a very important role
There exists a number of graph search techniques for finding optimal path to reach a dynamic target
The main motto of the proposed technique is to achieve a dynamic target i.e. a target which changes its position over time, by traversing as shortest distance as possible
Summary
In GIS finding shortest (or least cost on the basis of influencing criteria) [3] path between two points plays a very important role. In addition to path planning, the robot has to side-track the existing obstacles [1][2][4][5]. The target point may be dynamic (e.g. to track a pirate ship, to chase a wounded animal adorned with radio collaretc.). During planning for shortest path, existing obstacles should be avoided. In this proposed method, two obstacle avoidance techniques, namely — Iterative Recovery Method and Shortest Leap Method; have been proposed. A number of existing algorithms both for dynamic target search and obstacle avoidance are been studied along with their demerits and the proposed technique tries to overcome them
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