Path Planning with Hybrid Maps for processing and memory usage optimisation
Luís Santos, Filipe Neves dos Santos, Andrae S. Aguiar, António Valente, Pedro Costa
- 发表年份
- 2022
- 引用次数
- 4
摘要
Robotics will play an essential role in agriculture. Deploying agricultural robots on the farm is still a challenging task due to the terrain’s irregularity and size. Optimal path planning solutions may fail in larger terrains due to memory requirements as the search space increases. This work presents a novel open-source solution called AgRob Topologic Path Planner, which is capable of performing path planning operations using a hybrid map with topological and metric representations. A local A<sup>*</sup> algorithm pre-plans and saves local paths in local metric maps, saving them into the topological structure. Then, a graph-based A<sup>*</sup> performs a global search in the topological map, using the saved local paths to provide the full trajectory. Our results demonstrate that this solution could handle large maps (5 hectares) using just 0.002 % of the search space required by a previous solution.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991