Potential fields have been widely used for mobile robot navigation and obstacle avoidance. Their success is due to two main reasons: the simplicity with which a path planning problem can be represented and solved and, most of all, the computational efficiency that allows its real-time applicability. In this paper we analyze the complexity of calculating the artificial potential field and propose a novel algorithm that statistically reduces it
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Titolo: | AI-CART: An Algorithm to Incrementally Calculate Artificial potential fields in Real-Time |
Autori: | |
Data di pubblicazione: | 1999 |
Abstract: | Potential fields have been widely used for mobile robot navigation and obstacle avoidance. Their success is due to two main reasons: the simplicity with which a path planning problem can be represented and solved and, most of all, the computational efficiency that allows its real-time applicability. In this paper we analyze the complexity of calculating the artificial potential field and propose a novel algorithm that statistically reduces it |
Handle: | http://hdl.handle.net/11567/529329 |
Appare nelle tipologie: | 04.01 - Contributo in atti di convegno |
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