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A Multirobot Path-Planning Strategy for Autonomous Wilderness Search and Rescue.

Ashish Macwan, Julio Vilela, Goldie Nejat

    IEEE Transactions on Cybernetics
    |November 7, 2014
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    This study introduces a new on-line path planning strategy for autonomous ground robots in wilderness search and rescue (WiSAR). It ensures optimal robot deployment by dynamically replanning paths for efficient and timely missions.

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    Area of Science:

    • Robotics
    • Artificial Intelligence
    • Search and Rescue Operations

    Background:

    • Wilderness Search and Rescue (WiSAR) presents dynamic challenges for autonomous robot deployment.
    • Effective multi-robot coordination (MRC) is crucial for maximizing search efficiency and success rates.

    Purpose of the Study:

    • To propose a novel on-line motion-path planning strategy for autonomous ground robots in WiSAR.
    • To ensure optimal robot deployment and path feasibility throughout dynamic search operations.

    Main Methods:

    • Developed a multi-robot coordination (MRC) methodology incorporating on-line path planning.
    • Robots plan initial time-optimal, piecewise polynomial paths.
    • Paths are continuously evaluated for feasibility and replanned on-line as needed.

    Main Results:

    • The proposed strategy enables dynamic path adjustments for optimal robot deployment.
    • Simulated realistic WiSAR scenarios demonstrate the effectiveness of the on-line replanning approach.
    • The strategy was compared against a non-probabilistic alternative, highlighting its advantages.

    Conclusions:

    • The novel on-line path planning strategy enhances the efficiency and adaptability of robots in WiSAR.
    • Continuous evaluation and on-line replanning are key to maintaining optimal robot deployment in dynamic environments.
    • This approach offers a robust solution for complex multi-robot search and rescue missions.