Obstacle Avoidance System using 2D Lidar for Autonomous Vehicle

This paper aims to develop autonomous driving vehicle based on robot operating system (ROS). ROS nodes are defined relative to model-based control and each node computes as the same period. For control system based on ROS, the structure of the feedback loop is designed based on the block diagram, which is not convenient for the complex system. The conceptual design of SysML may be more useful than block diagram. The feedback control with obstacle avoidance system is extracted to subsystems such as obstacle avoidance system, trajectory tracking, and motion control system. The communication between the subsystem is defined as subscription and publication in ROS. MATLAB/Simulink and Arduino IDE are used to develop ROS code. The obstacle avoidance node and trajectory tracking nodes subscribed the necessary data and they publish the desired velocity and the desired steering angle. The motion control node consists of velocity control and steering control, which are programmed to Arduino board and communicate with other nodes through UART communication. Gaussian potential function is applied to detect the obstacle and define the direction to avoid the obstacle. The prototype vehicle is developed as small vehicle and it is used to perform by the algorithms. The experiment result presents that the vehicle can detect the obstacle and avoid the obstacle successfully. The maximum of detection range is varied to observe the behavior and the steering angle is bounded +/- 20 degrees. As summary, the avoidance performance depends on the radius of detection, steering mechanisms, and communication speed between the nodes, which effects to sampling rate of control system.

This paper aims to develop autonomous driving vehicle based on robot operating system (ROS). ROS nodes are defined relative to model-based control and each node computes as the same period. For control system based on ROS, the structure of the feedback loop is designed based on the block diagram, which is not convenient for the complex system. The conceptual design of SysML may be more useful than block diagram. The feedback control with obstacle avoidance system is extracted to subsystems such as obstacle avoidance system, trajectory tracking, and motion control system. The communication between the subsystem is defined as subscription and publication in ROS. MATLAB/Simulink and Arduino IDE are used to develop ROS code. The obstacle avoidance node and trajectory tracking nodes subscribed the necessary data and they publish the desired velocity and the desired steering angle. The motion control node consists of velocity control and steering control, which are programmed to Arduino board and communicate with other nodes through UART communication. Gaussian potential function is applied to detect the obstacle and define the direction to avoid the obstacle. The prototype vehicle is developed as small vehicle and it is used to perform by the algorithms. The experiment result presents that the vehicle can detect the obstacle and avoid the obstacle successfully. The maximum of detection range is varied to observe the behavior and the steering angle is bounded +/- 20 degrees. As summary, the avoidance performance depends on the radius of detection, steering mechanisms, and communication speed between the nodes, which effects to sampling rate of control system.