Cooperative Area Coverage Using Hexagonal Segmentation

Mobile Robotics have generated considerable interest in recent decades, mainly due to the advances that have lead to the development and use of mobile robots to perform tasks in several different areas. The mapping and area coverage problems are major challenges in Robotics that have many applications such as surveillance, detection of unexploded ordnance, and rescue, among others, in which the cooperation of different simultaneous robots can improve the performance of these tasks.

This work presents a complete and cooperative coverage methodology based on a hexagonal tessellation of the environment, on where robot teams will work together to cover a concave or convex, region of interest. The proposed method supports different configurations depending on the mapping being performed. We also implement a simple but efficient approach for resilient task allocation to allow the fulfillment of the coverage, even if there is only one robot left of the team. This methodology was adapted to function with 2D and 3D coverage and was used in a cooperative aerial mapping system to detect magnetic anomalies.