A 2-Dimensional ACO-Based Path Planner for Off-Line Robot Path Planning

Wireless sensor networks are usually deployed in scenarios that are too hostile for human personnel to perform maintenance tasks. Wireless sensor nodes usually exchange information in a multi-hop manner. Connectivity is crucial to the performance of a wireless sensor network. In case a network is partitioned due to node failures, it is possible to re-connect the fragments by setting up bridges using mobile platforms. Given the landscape of a terrain, the mobile platforms should be able reach the target position using a desirable path. In this paper, an off-line robot path planner is proposed to find desirable paths between arbitrary points in a given terrain. The proposed path planner is based on ACO algorithms. Unlike ordinary ACO algorithms, the proposed path planner provides its artificial ants with extra flexibility in making routing decisions. Simulation results show that such enhancement can greatly improve the qualities of the paths obtained. Performances of the proposed path planner can be further optimized by fine-tuning its parameters.