Kapoutsis, A.C., Malliou, C.M., Chatzichristofis, S.A. and Kosmatopoulos, E.B., 2017, October. Continuously informed heuristic A∗-optimal path retrieval inside an unknown environment. In 2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR) (pp. 216-222). IEEE.
The developed algorithm ensures the optimal path retrieval between two given locations by exploring the minimum portion of the environment.
The term minimum portion of the environment is defined as the number of cells that have to be visited by the explorer (robot-scouter) to acquire information about the state (obstacle or free space) of their neighbors.
In principle, the optimal path can be guaranteed by a searching agent that adopts an A*-like decision mechanism. The proposed CIA* inherits the A* optimality and efficiency guarantees, while at the same time exploits the learnt formation of the obstacles, to on-line revise the heuristic evaluation of the candidate states. For more information please check this paper.
@article{kapoutsis2017Continuously,
title={Continuously Informed Heuristic A* – Optimal Path Retrieval Inside an Unknown Environment},
author={Kapoutsis, A Ch and Malliou, C M and Chatzichristofis, S A and Kosmatopoulos, E B},
booktitle={2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR)},
pages={216–222},
year={2017},
publisher={IEEE}
}