WACO: Web3D mountain path planning algorithm

Multi-agent path planning spends much time and computer resource in the calculation process. Especially in mountain terrain, it is difficult to make real time and accurate path planning for multi-agent. This paper proposes a novel algorithm named WACO (Web3D Ant Colony Optimization) to reduce calculation costs. The WACO algorithm commits to solving the mountain terrain scene in real-time path planning. Firstly, a three-dimensional mountainous terrain is constructed, followed by reading the position data of various obstacles on the mountain and mapping the mountainous terrain into a two-dimensional terrain while simultaneously mapping the obstacle data. In the second step, based on the two-dimensional terrain and obstacle locations, WACO ant colony algorithm modeling is conducted, utilizing pheromone updates to continuously search for the optimal path planning. Finally, the proposed WACO ant colony path planning is compared with the latest path planning and classic path planning methods. The experimental results demonstrate that the WACO algorithm can make accurate path planning than other excellent ACO algorithm (pgACO: planar grid ACO) or the classic A* algorithm