Abstract
The problem of planning a set of paths for the coalition of robots (agents) with different capabilities is considered in the paper. Some agents can modify the environment by destructing the obstacles thus allowing the other ones to shorten their paths to the goal. As a result the mutual solution of lower cost, e.g. time to completion, may be acquired. We suggest an original procedure to identify the obstacles for further removal that can be embedded into almost any heuristic search planner (we use Theta*) and evaluate it empirically. Results of the evaluation show that time-to-complete the mission can be decreased up to 9–12 % by utilizing the proposed technique.
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Notes
- 1.
The path itself can be reconstructed by iteratively tracing backpointers from goal vertex until start is reached.
- 2.
Source code is available at https://github.com/PathPlanning/AStar-JPS-ThetaStar/tree/destroy_obs_and_replan
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Acknowledgments
This work was supported by the “RUDN University Program 5–100” (extracting data from OpenStreetMaps to conduct the experiments) and by the RSF project #16-11-00048 (developing path planning methods and evaluating them).
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Andreychuk, A., Yakovlev, K. (2018). Path Finding for the Coalition of Co-operative Agents Acting in the Environment with Destructible Obstacles. In: Ronzhin, A., Rigoll, G., Meshcheryakov, R. (eds) Interactive Collaborative Robotics. ICR 2018. Lecture Notes in Computer Science(), vol 11097. Springer, Cham. https://doi.org/10.1007/978-3-319-99582-3_2
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