W. Burgard, D. Fox, H. Jans, C. Matenar, and S. Thrun. Sonar-based mapping with mobile robots using EM. In Proc. of the International Conference on Machine Learning, 1999. Home/Search Document Details and Download
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Simultaneous Localization and Mapping - A Discussion - Frese, Hirzinger (2001) (4 citations) (Correct)
....Identification can be identified. This is a very difficult but highly important problem, since for instance, the event of closing a loop is only evident from the re identification of some landmarks. There are some approaches that take advantage of tightly integrating mapping and identification [1] . Indeed the uncertainty information from the map can be used to support identification [13] However it is often a good idea to separate both, as the SLAM problem can be formulated relatively independently of the sensors used, whereas landmark identification usually depends heavily on them. ....
....instance representing ambiguous identifications. The computational cost however is exponential in the number of dimensions, limiting them to 3 or 4. Representing a joint distribution of all robot poses or even of all map instances as in the covariance based approaches is not feasible. Thrun et al. [1] solve this problem by building the map from possibly overlapping patches each described by an evidence grid and a distribution of the pose of that patch in the map. The distribution of the different patches are assumed to be independent. While the robot moves, the raw sensor data (ultrasonic) ....
W. Burgard, D. Fox, H. Jans, C. Matenar, and S. Thrun. Sonarbased mapping with mobile robots using EM. In Proc. 16th International Conf. on Machine Learning, pages 67--76. Morgan Kaufmann, San Francisco, CA, 1999.
Tele-presence in Populated Exhibitions through.. - Burgard.. (2003) Self-citation (Burgard) (Correct)
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W. Burgard, D. Fox, H. Jans, C. Matenar, and S. Thrun, Sonar-based mapping with mobile robots using EM, Proc. of the International Conference on Machine Learning (ICML), 1999.
Collaborative Multi-Robot Exploration - Burgard, Moors, Fox, Simmons, Thrun (2000) (71 citations) Self-citation (Burgard Fox Thrun) (Correct)
....there are N robots which all have an individual map m i . Furthermore, let P (occ i x;y ) denote the probability that the location hx; yi in the global coordinate frame is occupied in the map of robot i. Then we integrate the maps of the different robots according to the following formula [3, 13, 18]: P (occ x;y ) odds x;y 1 odds x;y (1) where odds x;y = n Y i=1 odds i x;y (2) and odds i x;y = P (occ i x;y ) 1 P (occ i x;y ) 3) As an example consider the maps depicted in Figure 1. Here the two local maps shown on the left are integrated into one global map shown on ....
W. Burgard, D. Fox, H. Jans, C. Matenar, and S. Thrun. Sonar-based mapping with mobile robots using EM. In Proc. of the International Conference on Machine Learning, 1999.
Collaborative Multi-Robot Exploration - Burgard, Fox, Moors, Simmons, Thrun (2000) (71 citations) Self-citation (Burgard Fox Thrun) (Correct)
....there are N robots which all have an individual map m i . Furthermore, let P (occ i x;y ) denote the probability that the location hx; yi in the global coordinate frame is occupied in the map of robot i. Then we integrate the maps of the different robots according to the following formula [11, 15, 3]: P (occ x;y ) odds x;y 1 odds x;y (1) where odds x;y = n Y i=1 odds i x;y (2) and odds i x;y = P (occ i x;y ) 1 P (occ i x;y ) 3) As an example consider the maps depicted in Figure 1. Here the two local maps shown on the left are integrated into one global map shown on ....
W. Burgard, D. Fox, H. Jans, C. Matenar, and S. Thrun. Sonar-based mapping with mobile robots using EM. In Proc. of the International Conference on Machine Learning, 1999.
Hierarchical Linear/Constant Time SLAM - Using Particle Filters (Correct)
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W. Burgard, D. Fox, H. Jans, C. Matenar, and S. Thrun. Sonar-based mapping with mobile robots using EM. In Proc. of the International Conference on Machine Learning, 1999.
Topology Inference for a Vision-Based Sensor Network - Dimitri Marinakis Gregory (Correct)
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W. Burgard, D. Fox, H. Jans, C. Matenar, and S. Thrun. Sonar-based mapping with mobile robots using EM. In Proc. 16th International Conf. on Machine Learning, pages 67-- 76. Morgan Kaufmann, San Francisco, CA, 1999.
Multi-agent Mapping Using Dynamic Allocation - Utilizing Centralized Storage (Correct)
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Wolfram Burgard, Dieter Fox, Hauke Jans, Christian Matenar, and Sebastian Thrun. Sonar-based mapping with mobile robots using EM. In Proc. 16th International Conf. on Machine Learning, pages 67--76. Morgan Kaufmann, San Francisco, CA, 1999.
Mobile Robot Localisation and Mapping in Extensive Outdoor.. - Bailey (2002) (10 citations) (Correct)
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W. Burgard, D. Fox, H. Jans, C. Matenar, and S. Thrun. Sonar-based mapping with mobile robots using EM. In International Conference on Machine Learning, 1999.
DP-SLAM: Fast, Robust Simultaneous Localization and Mapping.. - Eliazar, Parr (2003) (5 citations) (Correct)
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W. Burgard, D. Fox, H. Jans, C. Matenar, and S. Thrun. Sonar-based mapping with mobile robots using EM. In Proc. of the International Conference on Machine Learning, 1999.
Dp-Slam 2.0 - Austin Eliazar And (2004) (1 citation) (Correct)
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W. Burgard, D. Fox, H. Jans, C. Matenar, and S. Thrun, "Sonar-based mapping with mobile robots using EM," in Proc. of the International Conference on Machine Learning, 1999.
Simultaneous Localization and Mapping - - New Algorithm For (Correct)
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W. Burgard, D. Fox, H. Jans, C. Matenar, and S. Thrun. Sonar-based mapping with mobile robots using EM. In Proc. of the International Conference on Machine Learning, 1999.
Some Experiments With Reinforcement Learning on Real World Robots - Vikram (2001) (Correct)
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Wolfram, B., Fox, D., Jans, H., Matenar, C., and Thrun, S. (1999). Sonar-based mapping with mobile robots using em. In Proceedings of the 16th International Conference on Machine Learning. 66
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