An Approximation Algorithm for a Shortest Dubins Path Problem
This provides a better approximation algorithm for unmanned aerial vehicle path planning in monitoring and surveillance applications, though it is incremental.
The paper tackles the problem of finding the shortest path for a vehicle with motion constraints visiting a sequence of points, improving the approximation guarantee from 3.04 to 2.04.
The problem of finding the shortest path for a vehicle visiting a given sequence of target points subject to the motion constraints of the vehicle is an important problem that arises in several monitoring and surveillance applications involving unmanned aerial vehicles. There is currently no algorithm that can find an optimal solution to this problem. Therefore, heuristics that can find approximate solutions with guarantees on the quality of the solutions are useful. The best approximation algorithm currently available for the case when the distance between any two adjacent target points in the sequence is at least equal to twice the minimum radius of the vehicle has a guarantee of 3.04. This article provides a new approximation algorithm which improves this guarantee to 2.04. The developed algorithm is also implemented for hundreds of typical instances involving at most 30 points to corroborate the performance of the proposed approach.