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Papers
Recent Documentation
1. Ma, Jeremy (May 17th, 2006). Documentation on NorthStar (PDF) .
2. Ma, Jeremy (June 7th, 2006). Documentation on NorthStar [revised] (PDF) .
Published Papers
None yet, but soon enough there will be!
Currently Reading
Dynamic SLAM:
1. D. Hahnel, R. Triebel, W. Burgard, and S. Thrun. Map Building with Mobile Robots in Dynamic Environments . In IEEE International Conference on Robotics and Automation (ICRA), Taipei, Taiwan, 2003. ICRA.
2. D. Fox, W. Burgard, S. Thrun, and A. Cremers. Position Estimation for Mobile Robots in Dynamic Environments . In Proceedings of the AAAI Fifteenth National Conference on Artificial Intelligence, 1998.
3. D. Fox, W. Burgard, and S. Thrun. Markov Localization for Mobile Robots in Dynamic Environments . Journal of Artificial Intelligence Research 11 (1999) 391-427.
4. C.-C. Wang, C. Thorpe, and S. Thrun. Online Simultaneous Localization and Mapping with Detection and Tracking of Moving Objects: Thoery and Results from a Ground Vehicle in Crowded Urban Areas . IEEE Int. Conf. on Robotics and Automation, May, 2003.
5. C.-C. Wang, C. Thorpe, and S. Thrun. Simultaneous Localization and Mapping with Detection and Tracking of Moving Objects. IEEE Int. Conf. on Robotics and Automation, May, 2002.
6. C.-C. Wang, C. Thorpe, and A. Suppe. Ladar-Based Detection and Tracking of Moving Objects from a Ground Vehicle at High Speeds. . In IEEE Intelligent Vehicles Symposium (IV2003), June, 2003.
7. K. Kodagoda, C.-C. Wang, and G. Dissanayake. Laser-Based Sensing on Roads . In IEEE Intelligent Vehicles Symposium (IV2003), June, 2003.
8. M. Montemerlo, S. Thrun, and W. Whittaker. Conditional Particle Filters for Simultaneous Mobile Robot Localization and people-Tracking. . In IEEE International Conference on Robotics and Automation (ICRA), Washington, DC, 2002. ICRA.
9. C.-C. Wang. Simultaneous Localization, Mapping and Moving Object Tracking. Doctoral dissertation. . Technical Report CMU-RI-TR-04-23, Robotics Institute, Carnegie Mellon University, 2004.
10. D. Koks and S. Challa. An Introduction to Bayesian and Dempster-Shafer Data Fusion . Australian Government Department of Defence. Defence Science and Technology Organisation.
11. D. Fox, S. Thrun, W. Burgard, and F. Dellaert. Particle Filters for Mobile Robot Localization .
Static SLAM:
1. Lu, Feng and Evangelos Milios. Robot Pose Estimation in Unknown Environments by Matching 2D Range Scans. Depertment of Computer Science, York University, North York, Canada M3J 1P3.
2. Lu, Feng and Evangelos Milios. Globally Consistent Range Scan Alignment for Environment Mapping. Depertment of Computer Science, York University, North York, Canada April 17, 1997.
3. Pfister, Samuel T., Kristo L. Kriechbaum, Stergios I. Roumeliotis, Joel W. Burdick. A Weighted Range Sensor Matching Algorithm for Mobile Robot Displacement Estimation. Division of Engineering and Applied Science, California Institute of Technology.
Attention/Awareness & Saliency Maps:
1. S. Frintrop, E. Rome, A. Nuchter, and H. Surmann. A Bimodal Laser-Based Attention System . Computer Vision and Image Understanding 100 (2005) 124-151.
2. L. Itti and C. Koch. Feature Combination Strategies for Saliency-Based Visual Attention Systems. California Institute of Technology, Computation and Neural Systems Program.
3. L. Itti and C. Koch. A Saliency-Based Search Mechanism for Overt and Covert Shifts of Visual Attention . Vision Research, Vol. 40, No. 10-12, pp. 1489-1506, May 2000.
4. L. Itti, C. Koch, and E. Nieubur. A Model of Saliency-Based Visual Attention for Rapid Scene Analysis . IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20, No. 11, pp. 1254-1259, Nov 1998.
5. S. Frintrop, A. Nuchter, and H. Surmann. Visual Attention for Object Recognition in Spatial 3D Data . In: Proceedings of the 2nd International Workshop on Attention and Performance in Computational Vision (WAPCV 2004), revised post-conference proceedings: Springer LNCS Vol. 3368, Berlin ISBN 3-540-24421-2.
6. S. Frintrop, G. Backer, and E. Rome. Goal-Directed Search with a Top-Down Modulated Computational Attention System . Proceedings of the Annual Meeting of the German Association for Pattern Recognition (DAGM '05), Wien, Austria, Aug/Sept. 2005.
7. S. Frintrop, G. Backer, and E. Rome. Selecting What Is Important: Training Visual Attention . Proceedings of the 28th German Conference on Artificial Intelligence (KI '05), Koblenz, Germany, Sept. 2005.
8. J. Tsotsos, et. al. Modeling Visual Attention via Selective Tuning . Artificial Intelligence 78 (1995) 507-545.
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