Controlling robotic swarm behavior utilizing real-time kinematics and artificial physics
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Recent commercial developments in small, low cost real-time kinematic GPS sensors enable position realization for light, mobile platforms with centimeter-level accuracy. With a high degree of positional confidence, we explore the feasibility of close-proximity operations of cooperative autonomous agents in an outdoor, GPS-enabled environment. A computer-simulated hookian spring force is used to control a swarm of robotic agents, a technique called artificial physics. The computer model applies a proportional spring constant based o position information, and the resultant force is applied to each agent respectively. We validate the model by comparing it to analytic solutions, then further refine the model by comparing it to field testing data. With an accurate model of the system, user-defined tasks are tested in simulations and the same algorithm then controls the behavior of the robotic swarm in an outdoor environment.
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