Dynamic Algorithm for Path Planning using A-Star with Distance Constraint

Path planning is one of the most well-researched topics in regard of autonomous agents. The task is to determine an optimal path from the source to the destination by avoiding obstacles at the same time. The optimality of the path is evaluated using performance indicators that reward the shortest route that is planned between the source and the destination. The A-star algorithm is popularly used for effective path planning. The current objective of this paper is to augment the A-star algorithm with the constraint of distance or cost that can be found in real-time scenarios where the battery charge of the mobile robot gets depleted over time before the destination is reached. The modified A-star algorithm tackles this problem by allowing the mobile robot to reach a not yet visited checkpoint that is closest to the destination and within the distance limit. This checkpoint is considered as a charging point, and a new path is planned from this checkpoint to the destination after resetting the cost function of the A-star algorithm.