Journal ArticleDOI
Velocity potential approach to path planning for avoiding moving obstacles
TLDR
This paper describes the theory and an experiment of a velocity potential approach to path planning and avoiding moving obstacles for an autonomous mobile robot by use of the Laplace potential and verifies the effectiveness of the navigation function for obstacle avoidance in a real world.Abstract:
This paper describes the theory and an experiment of a velocity potential approach to path planning and avoiding moving obstacles for an autonomous mobile robot by use of the Laplace potential. This new navigation function for path planning is feasible for guiding a mobile robot avoiding arbitrarily moving obstacles and reaching the goal in real time. The essential feature of the navigation function comes from the introduction of fluid flow dynamics into the path planning. The experiment is conducted to verify the effectiveness of the navigation function for obstacle avoidance in a real world. Two examples of the experiment are presented; first, the avoidance of a moving obstacle in parallel line-bounded space, and second, the avoidance of one moving obstacle and another standing obstacle. The robot can reach the goal after successfully avoiding the obstacles in these cases.read more
Citations
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Proceedings ArticleDOI
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Real-time obstacle avoidance for multiple mobile robots
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Motion planning in the presence of directional and regional avoidance constraints using nonlinear, anisotropic, harmonic potential fields: a physical metaphor
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Proceedings ArticleDOI
Motion planning in the presence of directional and obstacle avoidance constraints using nonlinear, anisotropic, harmonic potential fields
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TL;DR: In this paper, an evolutionary, hybrid PDE-ODE controller is proposed to jointly condition a motion trajectory with both directional and region avoidance constraints, and mathematical proofs of both convergence and the ability to enforce directional and Region avoidance constraints are provided.
References
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TL;DR: A path-planning algorithm for the classical mover's problem in three dimensions using a potential field representation of obstacles is presented and solves a much wider class of problems than other heuristic algorithms and at the same time runs much faster than exact algorithms.
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