By Rudiger Dillmann, Jurgen Beyerer, Christoph Stiller, Marius Zollner, Tobias Gindele
ISBN-10: 3642102832
ISBN-13: 9783642102837
Das 21. Fachgespr?ch Autonome cellular Systeme (AMS 2009) ist ein discussion board, das Wissenschaftlerinnen und Wissenschaftlern aus Forschung und Industrie, die auf dem Gebiet der autonomen mobilen Systeme arbeiten, eine foundation f?r den Gedankenaustausch bietet und wissenschaftliche Diskussionen sowie Kooperationen auf diesem Forschungsgebiet f?rdert bzw. initiiert. Inhaltlich finden sich ausgew?hlte Beitr?ge zu den Themen Humanoide Roboter und Flugmaschinen, Perzeption und Sensorik, Kartierung und Lokalisation, Regelung, Navigation, Lernverfahren, Systemarchitekturen sowie der Anwendung von autonomen mobilen Systemen.
Read or Download Autonome Mobile Systeme 2009 (21. Fachgesprach Karlsruhe, 3. 4. Dezember 2009) (Reihe: Informatik aktuell) PDF
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Extra info for Autonome Mobile Systeme 2009 (21. Fachgesprach Karlsruhe, 3. 4. Dezember 2009) (Reihe: Informatik aktuell)
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A Theory of Visual Control of Braking Based on Information about Timeto-Collision. : A combined corner and edge detector. : Good features to track. : Calculating Time-to-Contact Using Real-Time Quantized Optical Flow. : An affine invariant interest point detector. : Multiple View Geometry in Computer Vision. Cambridge University Press, 2003 [7] Lowe D. : Distinctive image features from scale-invariant keypoints. : Optical Flow based robot obstacle avoidance. : Robust Time-to-Contact Calculation for Real Time Applications.
Each graphic shows calculated TTC values for one respective feature. values. The curve, marked with (×) shows the TTC values which have been computed using the original approach presented by Lee. The curve, marked with (∗) shows TTC values which were calculated using the proposed approach. The same noisy data were used as an input to both methods. In contrast to the (×)-curve the (∗)- curve is more smooth and avoids sudden jumps. Moreover it approximates the true values up to a variance from 5 to 7 sec.
3. P. M. Jolion, A. Limongiello, and M. Vento. Stereo Vision for Obstacle Detection: A Grap-Based Approach. LNCS GbRPR, 4538:37–48, 2007. 4. A. Wedel, U. Franke, J. Klappstein, T. Brox, and D. Cremers. Realtime Depth Estimation and Obstacle Detection from Monocular Video. DAGM, pages 475–484, 2006. 5. E. Einhorn, Ch. -J. -M. Gross. A Hybrid Kalman Filter Based Algorithm for Real-time Visual Obstacle Detection. In ECMR, pages 156–161, 2007. 6. J. D. D. Molton, and O. Stasse. MonoSLAM: Real-Time Single Camera SLAM.
Autonome Mobile Systeme 2009 (21. Fachgesprach Karlsruhe, 3. 4. Dezember 2009) (Reihe: Informatik aktuell) by Rudiger Dillmann, Jurgen Beyerer, Christoph Stiller, Marius Zollner, Tobias Gindele
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