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.

Toward stochastic modeling of obstacle detectability in passive stereo range imagery

Abstract: To design high-performance obstacle detection systems for semi-autonomous navigation, it will be necessary to characterize the performance of obstacle detection sensors in quantitative, statistical terms and to develop design methodologies that relate task requirements (e.g., vehicle speed) to sensor system parameters (e.g., image resolution). Steps to be taken to realize such a methodology are outlined. For the specific case of obstacle detection with passive stereo range imagery, the development of the statistical models needed for the methodology is begun, and experimental results for outdoor images of a gravel road, which test the models empirically, are presented. The experimental results show sample error distributions for estimates of disparity and range, illustrate systematic errors caused by partial occlusion, and demonstrate that effective obstacle detection is achievable. >

Obstacle detection apparatus and obstacle detection program

Abstract: An obstacle detection apparatus includes a transmission antenna transmitting radio waves, a reception antenna receiving radio waves transmitted to and reflected by an obstacle, an obstacle detection unit configured to detect the obstacle based on the received radio waves, a false detection determination unit configured to determine presence or absence of a false detection characteristic, which is set in advance, with regard to the detected obstacle, a camera capturing an image, and an obstacle existence determination unit configured to determine, based on the image captured by the camera, presence or absence of the obstacle on which it is determined that the false detection characteristic is present.

Higher integrability in parabolic obstacle problems

Abstract: Abstract. In this paper we establish the self-improving property of integrability for parabolic variational inequalities satisfying an obstacle constraint and involving possibly degenerate respectively singular operators in divergence form. In particular, our results apply to the model case of the variational inequality associated to the parabolic p-Laplacean operator. Thereby we do not impose any monotonicity assumption in time on the obstacle function.

Mobile robot obstacle avoidance method based on Kinect

Abstract: The invention discloses a mobile robot obstacle avoidance method based on Kinect. In the indoor environment, environment information is obtained through a Kinect sensor, obstacle characteristics are recognized by processing depth information, different obstacles are separated out, the sizes of the obstacles can be estimated and the special obstacles are recognized; according to information of the obstacles, corresponding obstacle scenes are determined, so that corresponding obstacle avoidance strategies are determined, and on the basis of an artificial potential field method, the solution with the high adaptability, good real-time performance and smooth path is provided for real-time obstacle avoidance of an intelligent mobile robot in the unknown indoor environment. The environment information can be better mastered, so that the method is applicable to more indoor scenes, meanwhile, obstacle avoidance is performed on the basis of the artificial potential field method, and the defects existing in some artificial potential field methods are overcome through the environment information by means of advantages of the artificial potential field method.

Obstacle detection in single images with deep neural networks

Abstract: Obstacle detection in single images is a challenging problem in autonomous navigation on low-cost condition. In this paper, we introduce an approach for obstacle detection in single images with deep neural networks. We propose the followings: (1) a deep model combined with other deep neural network for obstacle detection; (2) a method to segment obstacles and infer their depths. Among others, both local and global information are generated in our method for better classification and portability. Experiments are performed on the open datasets and images captured by our autonomous vehicle. The results show that our method is effective in both obstacle detection and depth inference.