Abstract
Navigation is necessary for autonomous mobile robots that need to track the roads in outdoor environments. These functions could be achieved by fusing data from costly sensors, such as GPS/IMU, lasers and cameras. In this paper, we propose a novel method for road detection and road following without prior knowledge, which is more suitable with small single lane roads. The proposed system consists of a road detection system and road tracking system. A color-based road detector and a texture line detector are designed separately and fused to track the target in the road detection system. The top middle area of the road detection result is regarded as the road-following target and is delivered to the road tracking system for the robot. The road tracking system maps the tracking position in camera coordinates to position in world coordinates, which is used to calculate the control commands by the traditional tracking controllers. The robustness of the system is enhanced with the development of an Unscented Kalman Filter (UKF). The UKF estimates the best road borders from the measurement and presents a smooth road transition between frame to frame, especially in situations such as occlusion or discontinuous roads. The system is tested to achieve a recognition rate of about 98.7% under regular illumination conditions and with minimal road-following error within a variety of environments under various lighting conditions.
Highlights
In recent years, autonomous mobile robots have been an active research field
This paper presents a low-cost road-following system for mobile robots based on a monocular camera
The system is composed of a road detection system and road tracking system
Summary
Autonomous mobile robots have been an active research field. Navigation is one of the significant problems that need to be addressed by robots, which work in outdoor environments [1]. A low-cost, vision-based road-following system is proposed for autonomous mobile robots working in outdoor environments. The proposed system could be integrated with a local controller, such as pure pursuit, model predictive control (MPC) or Douglas-Peucker (DP) This will improve the navigation ability of robots in single lane road scenarios. The UKF is used to fuse the detection results by the color-based and texture line detector and to track the target.
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