Vision-Based Robust Path Reconstruction for Robot Control

被引:12
作者
Fontanelli, Daniele [1 ]
Moro, Federico [1 ]
Rizano, Tizar [1 ]
Palopoli, Luigi [1 ]
机构
[1] Univ Trento, Dept Informat Engn & Comp Sci, I-38123 Trento, Italy
关键词
Camera localization; inverse perspective mapping; path reconstruction; vision-based estimation; LANE DETECTION; LINE DETECTION; HOUGH TRANSFORM; SYSTEM; ROAD; TRACKING; RECOGNITION; OBSTACLE; MODEL;
D O I
10.1109/TIM.2013.2289091
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Many applications in mobile robotics require the localization of the robot with respect to the boundary of a path (e. g., a lane marker) and the reconstruction of the path in front of the robot. The former can be used as a basis for a reactive control scheme that drives the robot along the specified path and the latter is used to plan its future motion. Our solution to these problems relies on a camera mounted on the chassis and pointing headway. The relevant elements of the image grabbed from the camera (i.e., the lines delimiting the path) are robustly extracted and projected into the field-of-view of a virtual camera looking over the scene from above. This way, we obtain a top plan view that allows us to reconstruct position and bearing of the vehicle irrespective of mechanical vibrations or imperfect plane of motion. What is more, by pushing forward the virtual camera, we are able to reconstruct the path in front of the robot for some distance ahead. In this paper, we describe the main ideas underlying the approach and its implementation. The accuracy of the technique and the computational workload is evaluated through a large set of experiments.
引用
收藏
页码:826 / 837
页数:12
相关论文
共 54 条
[1]  
Aggarwal N, 2006, IEEE T IMAGE PROCESS, V15, P582, DOI 10.1109/TIP.2005.863021
[2]   Trajectory-tracking and path-following of underactuated autonomous vehicles with parametric modeling uncertainty [J].
Aguiar, A. Pedro ;
Hespanha, Joao P. .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2007, 52 (08) :1362-1379
[3]   Real time Detection of Lane Markers in Urban Streets [J].
Aly, Mohamed .
2008 IEEE INTELLIGENT VEHICLES SYMPOSIUM, VOLS 1-3, 2008, :165-170
[4]  
[Anonymous], 1998, LECT NOTES CONTROL I
[5]   GOLD: A parallel real-time stereo vision system for generic obstacle and lane detection [J].
Bertozzi, M ;
Broggi, A .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 1998, 7 (01) :62-81
[6]  
Borkar A, 2010, LECT NOTES COMPUT SC, V6475, P179, DOI 10.1007/978-3-642-17691-3_17
[7]   ROBUST LANE DETECTION AND TRACKING WITH RANSAC AND KALMAN FILTER [J].
Borkar, Amol ;
Hayes, Monson ;
Smith, Mark T. .
2009 16TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-6, 2009, :3261-+
[8]   A Hybrid Particle Approach for GNSS Applications With Partial GPS Outages [J].
Boucher, Christophe ;
Noyer, Jean-Charles .
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2010, 59 (03) :498-505
[9]   Image processing and behavior planning for intelligent vehicles [J].
Bücher, T ;
Curio, C ;
Edelbrunner, J ;
Igel, C ;
Kastrup, D ;
Leefken, I ;
Lorenz, G ;
Steinhage, A ;
von Seelen, W .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2003, 50 (01) :62-75
[10]  
Buehler Martin, 2007, The 2005 DARPA grand challenge: the great robot race, V36