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A Multirobot Path-Planning Strategy for Autonomous Wilderness Search and Rescue
IEEE Transactions on Cybernetics
|November 7, 2014
Summary
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.
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.
