J.-S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. Proceedings of the 1998 IEEE/RSJ Intl. Conference on Intelligent Robots and Systems (IROS'98), 1998. Home/Search Document Details and Download
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Developing Comprehensive State Estimators for Robot Soccer - Schmitt, Hanek, Beetz (2003) (Correct)
....tour guide projects, some of the most successful applications of state estimation in autonomous robotics, the robot mainly estimated its own position. Therefore, the performance factors are simply whether or not the robot was lost and the average accuracy over the episodes in which it was not lost [4, 5]. In a nutshell, the cost of game state estimation in a soccer situation could be stated as cost(belief state,situation) w 1 hallucinations w 2 overlooked objects w 3 avg accuracy, where w 1 , w 2 , and w 3 are weights that assess the relative importance of hallucinating and ....
J.-S. Gutmann and D. Fox. An experimental comparison of localization methods continued. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2002.
Developing Comprehensive State Estimators for Robot Soccer - Schmitt, Hanek, Beetz (2003) (Correct)
....tour guide projects, some of the most successful applications of state estimation in autonomous robotics, the robot mainly estimated its own position. Therefore, the performance factors are simply whether or not the robot was lost and the average accuracy over the episodes in which it was not lost [4, 5]. In a nutshell, the cost of game state estimation in a soccer situation could be stated as cost(belief state,situation) w 1 hallucinations w 2 overlooked objects w 3 avg accuracy, where w 1 , w 2 , and w 3 are weights that assess the relative importance of hallucinating and ....
J.-S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In Proc. of the IEEE/RSJ IROS, 1998.
Particle Filters in Robotics - Thrun (2002) (4 citations) (Correct)
....popularity in computer vision applications. In most variants of the mobile localization problem, particle filters have been consistently found to outperform alternative techniques, including parametric probabilistic techniques such as the Kalman filter and more traditional techniques (see e.g. [18, 51]) MCL has been implemented with as few as 50 samples [26] on robots with extremely limited processing and highly inaccurate actuation, such as the soccerplaying AIBO robotic shown in Figure 2. Recent research has led to a range of adaptations of the basic particle filter. Generating particles ....
J.-S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In IROS-98.
Evidence Accumulation Method for Mobile Robot Localization - Restelli, Sorrenti, Marchese (2002) (Correct)
....without the need for extracting landmark features. These methods allow to obtain a robust localization even with quite noisy perceptions. Recently, several techniques for dense sensor matching have been developed, most of which base on probabilistic approaches. Techniques like scan matching [14] uses the Kalman Filter and assumes that both movements and measurements are affected by White Gaussian Noise. These techniques can localize a robot precisely and efciently, but, since they are local methods, they cannot recover from bad matches and or errors in the model. Markov Localization uses ....
Gutmann, J., Burgard, W., Fox, D., Konolige, K.: An experimental comparison of localization methods. In: proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS98). (1998)
People Tracking with a Mobile Robot Using Sample-based .. - Schulz, Burgard, Fox, .. (2003) (7 citations) Self-citation (Burgard Fox) (Correct)
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J.-S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1998.
Efficient Failure Detection for Mobile Robots Using.. - Plagemann, Stachniss, .. (2006) Self-citation (Burgard) (Correct)
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J.-S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In Proc. of the IEEE/RSJ InternationalConference on Intelligent Robots and Systems, 1998.
Adapting the Sample Size in Particle Filters Through KLD-Sampling - Fox (2003) (1 citation) Self-citation (Fox) (Correct)
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J.S. Gutmann and D. Fox. An experimental comparison of localization methods continued. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2002.
Adapting the Sample Size in Particle Filters Through KLD-Sampling - Fox (2003) (1 citation) Self-citation (Fox) (Correct)
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J.S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 1998.
People Tracking with a Mobile Robot Using Sample-Based .. - Schulz, Burgard, Fox, .. (2003) (3 citations) Self-citation (Burgard Fox) (Correct)
No context found.
J.-S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1998.
Tracking Multiple Moving Objects with a Mobile Robot - Dirk Schulz Wolfram (2001) (9 citations) Self-citation (Burgard Fox) (Correct)
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J.-S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1998.
Markov Localization: A Probabilistic Framework for Mobile Robot.. - Fox (1998) (15 citations) Self-citation (Burgard Fox) (Correct)
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Jens-Steffen Gutmann, Wolfram Burgard, Dieter Fox, and Kurt Konolige. An experimental comparison of localization methods. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'98), 1998.
Tracking Multiple Moving Targets with a Mobile Robot.. - Schulz, Burgard, Fox, .. (2001) (37 citations) Self-citation (Burgard Fox) (Correct)
No context found.
J.-S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1998.
Foundations of Assisted Cognition Systems - Kautz, Etzioni, Fox, Weld (2003) (8 citations) Self-citation (Fox) (Correct)
.... several variants of dynamic Bayes filters in the context of robot localization and people tracking [21, 20, 49, 47, 51, 137] In various experiments we demonstrated the advantages of rich, non parametric representations over more restricted representations such as Gaussians used in Kalman filters [58, 59, 98]. As a consequence of this research, we introduced particle filters [41] as a powerful tool for state estimation in robotics [47, 48, 51] The idea of particle filters is to represent probability densities by sets of samples. This representation allows particle filters to efficiently represent ....
J.S. Gutmann and D. Fox. An experimental comparison of localization methods continued. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2002.
Foundations of Assisted Cognition Systems - Kautz, Etzioni, Fox, Weld (2003) (8 citations) Self-citation (Fox) (Correct)
.... several variants of dynamic Bayes filters in the context of robot localization and people tracking [21, 20, 49, 47, 51, 137] In various experiments we demonstrated the advantages of rich, non parametric representations over more restricted representations such as Gaussians used in Kalman filters [58, 59, 98]. As a consequence of this research, we introduced particle filters [41] as a powerful tool for state estimation in robotics [47, 48, 51] The idea of particle filters is to represent probability densities by sets of samples. This representation allows particle filters to efficiently represent ....
J.S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 1998.
Environment Identification by Comparing Maps of Landmarks - Jens-Steffen Gutmann Masaki Self-citation (Gutmann) (Correct)
....by the sensors on the robot. The latter initially starts with an empty map in an unknown environment and builds a representation of the environment from the actions carried out by the robot and the measurements of its sensors. For both problems, many solutions have been presented in the past [1, 4, 5, 8, 10, 13, 14]. In general, map building is the harder of the two problems since it requires to not only estimate the position of the robot but also the position of landmarks (walls, corners, etc. in the environment. In many cases special conditions might be needed when building a map such as having the ....
J.-S. Gutmann and D. Fox. An experimental comparison of localization methods continued. In IROS, 2002.
CS Freiburg: Coordinating Robots for Successful Soccer .. - Weigel, Gutmann.. (2002) (3 citations) Self-citation (Gutmann) (Correct)
....is employed which is described in the next section. E. Markov Localization as Observation Filter In localization experiments carried out on the mobile robot Rhino [33] it became evident that Markov localization is more robust, while Kalman filtering is more accurate when compared to each other [14]. A combination of both methods is likely to provide a maximum robust and accurate system. For ball localization, this result is utilized by employing a Markov process as an observation filter for the Kalman filter. A grid based approach with a 2 dimensional (x; y) grid is used where each cell z ....
J.S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In Proc. Int. Conf. on Intelligent Robots and Systems (IROS), pages 736 -- 743, Victoria, Canada, October 1998.
RG Mapping: Learning Compact and Structured 2D Line Maps .. - Schröter, Beetz, Gutmann (2002) Self-citation (Gutmann) (Correct)
....position to be known. The localization matches the original range data with a scan calculated from the map at the same position. As a result we get an estimate for the current position, which we compare with the according aligned scan, that was actually part of the map building process before. In [7] it has been shown that the localization based on laser scans is very accurate precise. Therefore we take it as ground truth. The results are summarized in table II. We have also determined the accuracy by comparing how well the line segments match the scans they have been produced from The ....
J.-S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1998.
Learning Compact 3D Models of Indoor and Outdoor.. - Hähnel, Burgard, Thrun Self-citation (Burgard) (Correct)
....mobile robotics is a 2D pose alignment procedure. The problem is as follows: Robot odometry is erroneous. Small error in odometry, caused by effects such as drift and slippage, multiply over time. Such effects are relatively easy to compensate if a model of the environment is readily available [9] . However, in the absence of such a model, the robot faces a chicken andegg problem in that it has to simultaneously estimate both the model and its path. In the robot mapping literature, this problem is known as the simultaneously localization and mapping problem Figure 3: Occupancy grid map ....
J.-S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1998.
Robust Monte Carlo Localization for Mobile Robots - Thrun, Fox, Burgard, Dellaert (2001) (77 citations) Self-citation (Burgard Fox) (Correct)
.... The vast majority of existing algorithms address only the position tracking problem (see e.g. the review [4] The nature of small, incremental errors makes algorithms such as Kalman filters [28,37,47,68] applicable, which have been successfully applied in a range of fielded systems (e.g. [27,42,44,63]) Kalman filters estimate posterior distributions of robot poses conditioned on sensor data. Exploiting a range of restrictive assumptions such as Gaussian noise and Gaussian distributed initial uncertainty they represent posteriors by Gaussians. Kalman filters offer an elegant and efficient ....
J.-S. Gutmann, W. Burgard, D. Fox, K. Konolige, An experimental comparison of localization methods, in: Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-98), Victoria, BC, 1998.
Sensor-Actuator-Comparison as a Basis for - Collision Detection For (2004) (Correct)
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J.-S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. Proceedings of the 1998 IEEE/RSJ Intl. Conference on Intelligent Robots and Systems (IROS'98), 1998.
Topological Mapping of Ambiguous Space: Combining Qualitative . . . - Savelli (2005) (Correct)
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J. S. Gutmann and D. Fox. An experimental comparison of localization methods continued. In Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, Lusanne, Switzerland, 2002.
Topological Mapping of Ambiguous Space: Combining Qualitative . . . - Savelli (2005) (Correct)
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J. S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, Victoria, Canada, 1998.
Cars Perception, State Of The Art - Benenson (Correct)
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J. Gutmann and D. S. Fox. An experimental comparison of localization methods continued. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2002. Available from: http://www.informatik.uni-freiburg.de/~gutmann/.
Cars Perception, State Of The Art - Benenson (Correct)
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J. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1998. Available from: http://citeseer.ist.psu.edu/ article/gutmann98experimental.html.
Jolly Pochie 2004 in the Four Legged Robot League - Jun Inoue Hajime (2004) (Correct)
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Jens-Ste#en Gutmann and Dieter Fox. An experimental comparison of localization methods continued. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2002.
Hough Localization for Mobile Robots in Polygonal Environments - Iocchi, Nardi (2002) (2 citations) (Correct)
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J. S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 1998.
Predictive Autonomous Robot Navigation - Foka (2005) (1 citation) (Correct)
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J.-S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots & Systems (IROS), pages 736-743, 1998.
Predictive Autonomous Robot Navigation - Foka (2005) (1 citation) (Correct)
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Self-Localization in the RoboCup Environment - Luca Iocchi And (1999) (15 citations) (Correct)
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J. S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In International Conference on Intelligent Robots and Systems, 1998.
Laser-Based Localization with Sparse - Landmarks Andreas Strack (2005) (Correct)
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J.-S. Gutmann and D. Fox. An Experimental Comparison of Localization Methods Continued. In Proc. of the Int. Conf. on Intelligent Robots and Systems, 2002.
The Normal Distributions Transform: . . . - Biber (2003) (Correct)
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J. Gutmann, W. Burghard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In ##### ############# ############ ########### ###### ### ######, 1998.
Robot Homing by Exploiting Panoramic Vision - Argyros, Bekris, Al. (2005) (Correct)
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Gutmann, J.S., Burgard, W., Fox, D., and Konolige, K. 1998. An experimental comparison of localization methods. In the Proceedings of the 1998IEEE/RSJ, International Conference on Intelligent Robots and Systems,Victoria, B.C., Canada.
Vision-based Robot Localization Using Sporadic Features - Enderle, Folkerts.. (Correct)
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J.-S. Gutmann, W. Burgard, D. Fox, , and K. Konolige. An experimental comparison of localization methods. In Proceedings of the International Conference on Intelligent Robots and Systems (IROS'98), Victoria, Canada, October 1998.
Concurrent Object Identification and Localization.. - Kestler.. (2000) (Correct)
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J.-S. Gutmann, W. Burgard, D. Fox, , and K. Konolige. An experimental comparison of localization methods. In Proceedings of the International Conference on Intelligent Robots and Systems (IROS'98), Victoria, Canada, October 1998.
Improving Vision-Based Self-localization - Utz, Neubeck, Mayer, Kraetzschmar (2002) (1 citation) (Correct)
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J.-S. Gutmann, W. Burgard, D. Fox, , and K. Konolige. An experimental comparison of localization methods. In Proceedings of the International Conference on Intelligent Robots and Systems (IROS'98), Victoria, Canada, October 1998.
Fast and Robust Edge-Based Localization in the Sony.. - Röfer, Jungel (Correct)
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D. Gutmann, J.-S. Fox. An experimental comparison of localization methods continued. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Lausanne, Switzerland, 2002. EPFL.
Testing Omnidirectional Vision-Based - Monte-Carlo Localization Under (Correct)
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J.-S. Gutmann and D. Fox. An Experimental Comparison of Localization Methods Continued. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2002.
Wireless LAN Location-Sensing for Security Applications - Tao, Rudys, Ladd, Wallach (2003) (1 citation) (Correct)
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Designing Probabilistic State Estimators for Autonomous Robot.. - Schmitt, Beetz (2003) (Correct)
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J.-S. Gutmann and D. Fox. An experimental comparison of localization methods continued. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2002.
Designing Probabilistic State Estimators for Autonomous Robot.. - Schmitt, Beetz (2003) (Correct)
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J.-S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 1998.
Image-Based Monte-Carlo Localisation without a Map - Menegatti, Zoccarato.. (Correct)
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J.-S. Gutmann and D. Fox. An Experimental Comparison of Localization Methods Continued. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), da pubblicare, 2002.
Image-Based Monte-Carlo Localisation without a Map - Menegatti, Zoccarato.. (Correct)
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J.-S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An Experimental Comparison of Localization Methods. In Proceedings of the International Conference on Intelligent Robots and Systems (IROS), October 1998.
Fast and Robust Edge-Based Localization in the Sony.. - Röfer, Jüngel (Correct)
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D. Gutmann, J.-S. Fox. An experimental comparison of localization methods continued. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Lausanne, Switzerland, 2002. EPFL.
An Introduction to Robot Distributed Sensors Part I - Aboshosha (2003) (Correct)
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J-S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An Experimental Comparison of Localization Methods. In proceedings of the International Conference on Intel ligent Robots and Systems, Victoria, Canada, October 1998.
Mobile Robot Localization with Sparse Landmarks - Fairfield, Maxwell (2001) (2 citations) (Correct)
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J. Gutmann, W. Burgard, D. Fox, and K. Konolige, "An experimental comparison of localization methods," in Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'98), 1998.
Experiments in Free-Space Triangulation Using.. - Rekleitis, Dudek, Milios (Correct)
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J.-S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In IEEE/RSJ Int. Conference on Intelligent Robots and Systems, 1998.
The Normal Distribution Transform: A New Approach to Laser Scan.. - Biber (2003) (12 citations) (Correct)
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J. Gutmann, W. Burghard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In ##### ############# ############ ########### ###### ### ######, 1998.
An Experimental Comparison of Localisation Methods, - The Mhl Sessions (Correct)
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Jens-Steffen Gutmann and Dieter Fox. An experimental comparison of localization methods continued. In Proc. of the 2002.
An Experimental Comparison of Localisation Methods, - The Mhl Sessions (Correct)
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J.-S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In Proc. of the 1998.
A Hybrid Approach to Solve the Global Localization.. - Romero, Morales, Sucar (Correct)
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J.-S. Gutmann, W. Burgard, D. Fox, and K. Konolige. An experimental comparison of localization methods. In Proc. International Conference on Intelligent Robots and Systems (IROS'98), 1998.
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