For obstacle datasets, the segmentation precision and the average distance estimation error of the proposed method are 81.4% and 1.6 cm, respectively, whereas those for a conventional method are 57.5% and 9.9 cm, respectively. The obstacle segmentation accuracies and the distance estimation error are quantitatively analyzed. ![]() ![]() The algorithm is tested by applying it to 70 datasets, 20 of which include nonobstacle images where considerable changes in floor appearance occur. ![]() Next, the shortest distance between the robot and the obstacle is calculated. Markov random field-based obstacle segmentation is then performed using the IPM results and a floor appearance model. This method is much more advantageous when the camera is not high off the floor, which makes point tracking near the floor difficult. While conventional methods depend on point tracking for geometric cues for obstacle detection, the proposed algorithm uses the inverse perspective mapping (IPM) method. Each individual image pixel at the bottom region of interest is labeled as belonging either to an obstacle or the floor. This paper presents a monocular vision sensor-based obstacle detection algorithm for autonomous robots. Lee, Tae-Jae Yi, Dong-Hoon Cho, Dong-Il Dan It was observed that the algorithm performs well, provided that the wires are not too thin (or distant) and that some post processing is performed to remove false alarms due to clutter.Ī Monocular Vision Sensor-Based Obstacle Detection Algorithm for Autonomous Robots. The performance of the algorithm was evaluated both, at the pixel and the wire levels. The algorithm was tested using a set of images synthetically generated by combining real outdoor images with computer generated wire images. After reviewing the line detection literature, an algorithm for sub-pixel edge detection proposed by Steger was identified as having good potential to solve the considered task. Since they are very thin, their detection early enough so that the pilot has enough time to take evasive action is difficult, as their images can be less than one or two pixels wide. Wires present a serious hazard to rotorcrafts. In particular, the problem of detecting thin wires in the presence of image clutter and noise was studied. In this research we addressed the problem of obstacle detection for low altitude rotorcraft flight. Huang, Ying Narasimhamurthy, Anand Pande, Nitin Ahumada, Albert (Technical Monitor) Obstacle Detection Algorithms for Rotorcraft Navigation A list of publications resulting from this grant as well as a list of relevant publications resulting from prior NASA grants on this topic are presented. Real time implementation of obstacle detection algorithms on the Datacube MaxPCI architecture. Algorithms for detecting airborne obstacles and Part III. Data modeling and camera characterization Part II. This report describes the results of our research in realizing such a design. Design of such a module includes the selection and characterization of robust, reliable, and fast techniques and their implementation for execution in real-time. ![]() One of the components of the SVS is a module for detection of potential obstacles in the aircraft's flight path by analyzing the images captured by an on-board camera in real-time. The research reported here is a part of NASA's Synthetic Vision System (SVS) project for the development of a High Speed Civil Transport Aircraft (HSCT). Kasturi, Rangachar Camps, Octavia Coraor, Lee Obstacle Detection Algorithms for Aircraft Navigation: Performance Characterization of Obstacle Detection Algorithms for Aircraft Navigation
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