This thesis describes the development of a speed and steering control system for an autonomous amphibious vehicle use under extreme conditions for tactical distributed surveillance and autonomous motion on ground and water. It has been a research project of the Institute for Real-Time Learning Systems of Siegen University. The primary aim of the project is to design and develop speed and steering control systems for the DORIS Robot. The research is focused on controlling speed, steering, and obstacle avoidance using PID, Dead-Beat, and intelligent fuzzy logic control methods. For controlling the steering of DORIS on ground, two DC motors were used, which act on two variable displacement hydraulic pumps that set the swashplate angles in the hydrostatic transmission system. The PID, Dead-Beat, and P-Dead-Beat controllers were each designed to control the DC motor’s angular position, which in turn, controls the swashplate angle. Throughout the project, these types of controllers were tested on a separate hardware using PWM (Pulse-Width Modulation) for controlling the DC motor’s angular position. A comparison identified the PID control method as the optimal one. The speed of the DC motor is an important factor for controlling the swashplate torque. It was analyzed and studied with respect to the impact of different surfaces during skidding and rolling. To control the steering of the vehicle optimally, an intelligent fuzzy logic controller was developed for producing the independent angular positions of the two DC motors, which control the different speeds of the left and right wheels of the vehicle. These different speeds cause the vehicle to skid-steer right or left per the fuzzy logic rules.
The speed of the vehicle is a function of the engine speed. A servo motor control system controls the engine speed, whereby a coupling between the servo-control loop and the engine control loop is achieved. To drive DORIS semi-autonomously, a tele-operating system was added to the whole design, using a PC and/or Joystick and the Robot Operating System (ROS). During the motion of the vehicle in an unknown and changing environment, the vehicle must be able to navigate successfully without colliding with obstacles in the surroundings. For this purpose, a fuzzy logic strategy was also developed to guide the Autonomous Amphibious Vehicle (AAV).
For driving the vehicle on water, a water-jet system is used. The steering control system was implemented based on a PID control approach.
All hardware systems, control architecture, sensor suite, current capabilities, future research, and applications of the AAV are described in this project.