Obstacle

About: Obstacle is a research topic. Over the lifetime, 9517 publications have been published within this topic receiving 94760 citations. The topic is also known as: impediment & barrier.

Robust Obstacle Detection in General Road Environment Based on Road Extraction and Pose Estimation

Abstract: Understanding the general road environment is a vital task for obstacle detection in complicated situations. That task is easier to perform for highway environments than for general roads because road environments are well-established in highways and obstacle classes are limited. On the other hand, general roads are not always well-established and various small obstacles, as well as larger ones, must be detected. For the purpose of discerning obstacles and road patterns, it is important to determine the relative positions of the camera and the road surface. This paper presents an efficient solution using a stereo-vision-based obstacle detection method for general roads. The relative position is estimated dynamically even without any clear lane markings. Additionally, obstacles are detected without applying explicit models. We present experimental results to demonstrate the effectiveness of our proposed method under various conditions.

Stereo obstacle detection in challenging environments: The VIAC experience

Abstract: Obstacle detection by means of stereo-vision is a fundamental task in computer vision, which has spurred a lot of research over the years, especially in the field of vehicular robotics. The information provided by this class of algorithms is used both in driving assistance systems and in autonomous vehicles, so the quality of the results and the processing times become critical, as detection failures or delays can have serious consequences. The obstacle detection system presented in this paper has been extensively tested during VIAC, the VisLab Intercontinental Autonomous Challenge [1], [2], which has offered a unique chance to face a number of different scenarios along the roads of two continents, in a variety of conditions; data collected during the expedition has also become a reference benchmark for further algorithm improvements.

Application of A* algorithm for real-time path re-planning of an unmanned surface vehicle avoiding underwater obstacles

Abstract: This paper describes path re-planning techniques and underwater obstacle avoidance for unmanned surface vehicle (USV) based on multi-beam forward looking sonar (FLS). Near-optimal paths in static and dynamic environments with underwater obstacles are computed using a numerical solution procedure based on an A* algorithm. The USV is modeled with a circular shape in 2 degrees of freedom (surge and yaw). In this paper, two-dimensional (2-D) underwater obstacle avoidance and the robust real-time path re-planning technique for actual USV using multi-beam FLS are developed. Our real-time path re-planning algorithm has been tested to regenerate the optimal path for several updated frames in the field of view of the sonar with a proper update frequency of the FLS. The performance of the proposed method was verified through simulations, and sea experiments. For simulations, the USV model can avoid both a single stationary obstacle, multiple stationary obstacles and moving obstacles with the near-optimal trajectory that are performed both in the vehicle and the world reference frame. For sea experiments, the proposed method for an underwater obstacle avoidance system is implemented with a USV test platform. The actual USV is automatically controlled and succeeded in its real-time avoidance against the stationary undersea obstacle in the field of view of the FLS together with the Global Positioning System (GPS) of the USV.