System modeling and simulation are widely used in robotic vehicle engineering to reduce development time, improve the vehicle design, and miniaturize complex systems. This paper focuses on the steering control of a four-wheel steering vehicle. Optimally-tuned PID controllers are designed for autonomous ground vehicles. The required mission path and stability of steering are achieved by reducing the error between the vehicle heading and the target point. Predefined waypoints are set for the trajectory tracking system. An optimal genetic algorithm (GA) is proposed to tune the vehicle controllers. The proposed GA-tuned PID controller exhibits satisfactory simulation results and promising experimental results. This paper reports the current status of an ongoing research project for a fully autonomous unmanned ground vehicle (UGV).
Unmanned vehicles have been an active area of research and development over the past three decades. Unmanned Ground Vehicles (UGVs) are used in both civilian and military applications all over the world. The design of the ground control station hardware and software can become very complicated depending on the UGV mission and the autonomous guidance required. This paper introduces an autonomous system capable of guiding a small UGV via GPS. Different control methods are used including radio control (RC), joystick, and autonomous control. The GPS navigation loop provides continuous and reliable navigation data to the waypoint guidance algorithm and its control loop which is responsible for autonomous navigation. This control loop computes the guidance commands to follow the waypoint scenarios encountered and generates actuator signals for steering and speed control. The guidance, navigation, and control (GNC) algorithm was implemented within an embedded processor which communicates with the ground control station (GCS) over a wireless channel. The real-time test results indicate that the vehicle can reliably perform autonomous guidance in different scenarios.
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