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Cooperative Aerial-Ground Robotic System Using Genetic Algorithm Auto-Tuned Fractional Order PID Control

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Cooperative Aerial-Ground systems demand robust and efficient control authority to perform precise tracking motion in outdoor exploring, surveillance, and mapping missions. The dynamic characteristics of the swarm system reveal some levels of challenging and model uncertainties. This paper develops a Genetic Algorithm (GA) auto-tuned Fractional Order PID (FOPID) to control the tracking trajectories of a cooperative aerial-ground robotic system. The cooperative team consists of an Unmanned Aerial Vehicle (UAV), aka quadrotor, and an Unmanned Ground Vehicle (UGV). The quadrotor communicates, shares information, and performs a coordinated take-off, tracking, and landing over the UGV. The UGV moves on a predetermined path while the UAV follows it. The mission is called over when the UGV makes a complete stop, and then the UAV safely lands over it. The design onboard controllers minimize the tracking errors. A fractional order PID controller is implemented in a genetic algorithm platform in order to perform online optimization to obtain the best control parameters. The simulation results explain the benefits of the presented approach.
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Aerial Ground Team; Fractional PID Controller; Genetic Algorithm; Trajectory Tracking; Swarm Robotics

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