Shortest Path Planning with an Energy-Constrained Robot

In this paper, we study the problem of shortest path planning for a mobile robot that does not possess unlimited energy for traveling. The robot can travel at most B distance with its battery fully charged. The objective of this energy-constrained robot is to travel from location S to location G in the presence of k charging stations while minimizing the incurred travel cost. As the robot is constrained by its energy, it needs to stop at one or more charging stations in order to recharge its battery. To solve the stated problem, we have proposed a variant of the classical A
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search algorithm that plans the path of the robot in such a way that it moves as much distance as possible with a full recharge (the maximum being B). Furthermore, it chooses the one to be the next charging station that minimizes the extra distance that needs to be covered to reach it on top of the shortest distance from S to G. We have designed novel heuristic functions that guide the search towards such charging stations where the deviation from the shortest path without the constraint is the minimum. We prove that the proposed approach is complete. Results show that our proposed algorithm finds an optimal solution while taking a negligible time to execute.