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Real-Time Path Planning Algorithm for Autonomous Border Patrol: Design, Simulation, and Experimentation

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Abstract

This paper presents an online path planning algorithm for unmanned vehicles in charge of autonomous border patrol. In this Pursuit-Evasion game, the unmanned vehicle, acting as the pursuer, is required to capture multiple trespassers on its own before any of them reach a target safe house where they are safe from capture. The problem formulation is based on Isaacs’ Target Guarding problem, but extended to the case of multiple evaders. The proposed path planning method is based on Rapidly-exploring random trees (RRT) and is capable of producing trajectories within seconds to capture 2 or 3 evaders. Simulations are carried out to demonstrate that the resulting trajectories approach the optimal solution produced by a nonlinear programming-based numerical optimal control solver. Experiments are also conducted on unmanned ground vehicles to show the feasibility of implementing the proposed online path planning algorithm on physical applications.

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  1. University of Toronto Institute for Aerospace Studies, 4925 Dufferin Street, Toronto, ON, Canada, M3H 5T6

    George Lau & Hugh H. T. Liu

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  1. George Lau
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  2. Hugh H. T. Liu
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Correspondence to Hugh H. T. Liu.

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Lau, G., Liu, H.H.T. Real-Time Path Planning Algorithm for Autonomous Border Patrol: Design, Simulation, and Experimentation. J Intell Robot Syst 75, 517–539 (2014). https://doi.org/10.1007/s10846-013-9841-7

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  • DOI: https://doi.org/10.1007/s10846-013-9841-7

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