The problem of robotic area coverage is applicable to many domains, such as search, agriculture, cleaning, and machine tooling. The robotic area coverage task is concerned with moving a vehicle with an effector, or sensor, through the task space such that the sensor passes over every point in the space. For covering complex areas, back and forth paths are inadequate. This paper presents a real-time path planning architecture consisting of layers of a clustering method to divide and conquer the problem combined with a two layered, global and local optimization method. This architecture is able to optimize the execution of a series of waypoints for a restricted mobility vehicle, a fixed wing airplane.
R. J. Meuth and D. C. Wunsch, "Divide and Conquer Evolutionary TSP Solution for Vehicle Path Planning," Proceedings of the IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence), 2008, Institute of Electrical and Electronics Engineers (IEEE), Jun 2008.
The definitive version is available at https://doi.org/10.1109/CEC.2008.4630868
IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence), 2008
Electrical and Computer Engineering
Keywords and Phrases
Divide and Conquer Methods; Evolutionary Computation; Path Planning; Robots; Travelling Salesman Problems; Vehicles
Article - Conference proceedings
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