Force-Based Algorithm for Motion Planning of Large Agent
| Autor: | Samaneh Hosseini Semnani, Hugh H. T. Liu, Anton H. J. de Ruiter |
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| Rok vydání: | 2022 |
| Předmět: |
0209 industrial biotechnology
Computer science Autonomous agent Control (management) 02 engineering and technology Computer Science Applications Term (time) Human-Computer Interaction Motion 020901 industrial engineering & automation Control and Systems Engineering Position (vector) 0202 electrical engineering electronic engineering information engineering Benchmark (computing) Computer Simulation 020201 artificial intelligence & image processing Motion planning Electrical and Electronic Engineering Algorithm Algorithms Software Collision avoidance Information Systems |
| Zdroj: | IEEE Transactions on Cybernetics. 52:654-665 |
| ISSN: | 2168-2275 2168-2267 |
| DOI: | 10.1109/tcyb.2020.2994122 |
| Popis: | This article presents a distributed, efficient, scalable, and real-time motion planning algorithm for a large group of agents moving in 2-D or 3-D spaces. This algorithm enables autonomous agents to generate individual trajectories independently with only the relative position information of neighboring agents. Each agent applies a force-based control that contains two main terms: 1) collision avoidance and 2) navigational feedback. The first term keeps two agents separate with a certain distance, while the second term attracts each agent toward its goal location. Compared with existing collision-avoidance algorithms, the proposed force-based motion planning (FMP) algorithm can find collision-free motions with lower transition time, free from velocity state information of neighboring agents. It leads to less computational overhead. The performance of proposed FMP is examined over several dense and complex 2-D and 3-D benchmark simulation scenarios, with results outperforming existing methods. |
| Databáze: | OpenAIRE |
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