A Methodology for Autonomous Radio Repeating Based on the A* Algorithm

In the event of a disaster, rst responders must rapidly gain situational awareness about the environment in order to plan e ective response operations. Unmanned ground vehicles are well suited for this task but often require a strong communication link to a remote ground station to e ectively relay information. When considering an obstacle-rich environment, non-line-of-sight conditions and na ve navigation strategies can cause substantial degradations in radio link quality. Therefore, this paper incorporates an unmanned aerial vehicle as a radio repeating node and presents a path planning strategy to cooperatively navigate the vehicle team so that radio link health is maintained. This navigation technique is formulated as an A*-based search and this paper presents the formulation of this path planner as well as an investigation into strategies that provide computational e ciency to the search process. The path planner uses predictions of radio signal health at di erent vehicle con gurations to e ectively navigate the vehicles and simulations have shown that the path planner produces favorable results in comparison to several conceivable na ve radio repeating variants. The results also show that the radio repeating path planner has outperformed the na ve variants in both simulated environments and in eld testing where a Yamaha RMAX unmanned helicopter and a ground vehicle were used as the vehicle team.