Promoting Cooperative Behavior Between Cost-Based Planners
نویسندگان
چکیده
Robots performing delivery tasks use cost-based planning in order to move from a starting point to a destination point. This can ensure obstacle-free and distance-optimal trajectories for individual robots. However, when many robots share the same space, their shortest routes may overlap, causing traffic. This is particularly relevant when managing unmanned aerial vehicles (UAV) in the airspace, where low-level conflict-avoidance maneuvers can cause potentially hazardous situations when the density of traffic becomes too high. We propose a multiagent approach to traffic management, such that agents manipulate the sector-level cost space of UAVs traveling through an obstacle-filled environment. Results from testing on a simulated urban environment show that given only local UAV information, the team of sector agents was able to learn appropriate costing strategies to reduce the number of conflicts experienced in the entire airspace. Comparison to a uniform costing strategy showed on average a 16.4% reduction of conflicts in the airspace after 100 learning epochs.
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تاریخ انتشار 2015