Abstract
This work presents a vision-based obstacle avoidance algorithm for autonomous mobile robots. It provides an efficient solution that uses a minimum of sensors and avoids, as much as possible, computationally complex processes. The only sensor required is a stereo camera. The proposed algorithm consists of two building blocks. The first one is a stereo algorithm, able to provide reliable depth maps of the scenery in frame rates suitable for a robot to move autonomously. The second building block is a decision making algorithm that analyzes the depth maps and deduces the most appropriate direction for the robot to avoid any existing obstacles. The proposed methodology has been tested on sequences of self-captured outdoor images and its results have been evaluated. The performance of the algorithm is presented and discussed.
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References
Iocchi, L., Konolige, K.: A multiresolution stereo vision system for mobile robots. In: Italian AI Association Workshop on New Trends in Robotics Research (1998)
Siegwart, R., Nourbakhsh, I.R.: Introduction to Autonomous Mobile Robots. MIT Press, Massachusetts (2004)
Schreer, O.: Stereo vision-based navigation in unknown indoor environment. In: 5th European Conference on Computer Vision, vol. 1, pp. 203–217 (1998)
Scharstein, D., Szeliski, R.: A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. International Journal of Computer Vision 47(1-3), 7–42 (2002)
Torra, P.H.S., Criminisi, A.: Dense stereo using pivoted dynamic programming. Image and Vision Computing 22(10), 795–806 (2004)
Muhlmann, K., Maier, D., Hesser, J., Manner, R.: Calculating dense disparity maps from color stereo images, an efficient implementation. International Journal of Computer Vision 47(1-3), 79–88 (2002)
Di Stefano, L., Marchionni, M., Mattoccia, S.: A fast area-based stereo matching algorithm. Image and Vision Computing 22(12), 983–1005 (2004)
Yoon, S., Park, S.K., Kang, S., Kwak, Y.K.: Fast correlation-based stereo matching with the reduction of systematic errors. Pattern Recognition Letters 26(14), 2221–2231 (2005)
Zach, C., Karner, K., Bischof, H.: Hierarchical disparity estimation with programmable 3d hardware. In: International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, pp. 275–282 (2004)
Yoon, K.J., Kweon, I.S.: Adaptive support-weight approach for correspondence search. IEEE Transactions on Pattern Analysis and Machine Intelligence 28(4), 650–656 (2006)
Nalpantidis, L., Sirakoulis, G.C., Gasteratos, A.: Review of stereo vision algorithms: from software to hardware. International Journal of Optomechatronics 2(4), 435–462 (2008)
Borenstein, J., Koren, Y.: Real-time obstacle avoidance for fast mobile robots in cluttered environments. IEEE Transactions on Systems, Man, and Cybernetics 19(5), 1179–1187 (1990)
Ohya, A., Kosaka, A., Kak, A.: Vision-based navigation of mobile robot with obstacle avoidance by single camera vision and ultrasonic sensing. IEEE Transactions on Robotics and Automation 14(6), 969–978 (1998)
Vandorpe, J., Van Brussel, H., Xu, H.: Exact dynamic map building for a mobile robot using geometrical primitives produced by a 2d range finder. In: IEEE International Conference on Robotics and Automation, Minneapolis, USA, pp. 901–908 (1996)
Labayrade, R., Aubert, D., Tarel, J.P.: Real time obstacle detection in stereovision on non flat road geometry through ”v-disparity” representation. In: IEEE Intelligent Vehicle Symposium, Versailles, France, vol. 2, pp. 646–651 (2002)
Zhao, J., Katupitiya, J., Ward, J.: Global correlation based ground plane estimation using v-disparity image. In: IEEE International Conference on Robotics and Automation, Rome, Italy, pp. 529–534 (2007)
Soquet, N., Aubert, D., Hautiere, N.: Road segmentation supervised by an extended v-disparity algorithm for autonomous navigation. In: IEEE Intelligent Vehicles Symposium, Istanbul, Turkey, pp. 160–165 (2007)
Nalpantidis, L., Kostavelis, I.: Group of Robotics and Cognitive Systems (2009), http://robotics.pme.duth.gr/reposit/stereoroutes.zip
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Nalpantidis, L., Kostavelis, I., Gasteratos, A. (2009). Stereovision-Based Algorithm for Obstacle Avoidance. In: Xie, M., Xiong, Y., Xiong, C., Liu, H., Hu, Z. (eds) Intelligent Robotics and Applications. ICIRA 2009. Lecture Notes in Computer Science(), vol 5928. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10817-4_19
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DOI: https://doi.org/10.1007/978-3-642-10817-4_19
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