Publications of Dieter Fox

Most recent

• GP-BayesFilters: Bayesian Filtering Using Gaussian Process Prediction and Observation Models.
  J. Ko, and D. Fox. IROS-08.
• Learning to Associate Image Features with CRF-Matching.
  F. Ramos, K. Waleed, and D. Fox. ISER-08.
• Laser and Vision Based Outdoor Object Mapping
  B. Douillard, D. Fox, and F. Ramos. RSS-08.
• GP-UKF: Unscented Kalman Filters with Gaussian Process Prediction and Observation Models.
  J. Ko, D. Klein, D. Fox, and D. Hähnel. IROS-07. Best Student Paper Award.

Book

1. Probabilistic Robotics.
   S. Thrun, W. Burgard, D. Fox. MIT Press, September 2005.

Journals and Magazines

1. Learning and Inferring Transportation Routines.
   L. Liao, D.J. Patterson, D. Fox, and H. Kautz. AIJ 07.
2. Extracting Places and Activities from GPS Traces Using Hierarchical Conditional Random Fields.
   L. Liao, D. Fox, and H. Kautz. International Journal of Robotics Research, 2007.
3. Distributed Multi-robot Exploration and Mapping.
   D. Fox, J. Ko, K. Konolige, B. Limketkai, D. Schulz, and B. Stewart. Proc. of the IEEE, 2006.
4. Real-time Particle Filters.
   C. Kwok, D. Fox, and M. Meila. Proceedings of the IEEE, 92(2), 2004.
5. Bayesian filtering for location estimation.
   D. Fox, J. Hightower, L. Liao, D. Schulz, and G. Borriello. IEEE Pervasive Computing, 2003.
6. Adapting the sample size in particle filters through KLD-sampling.
   D. Fox. International Journal of Robotics Research IJRR, 2003.
7. People Tracking with a Mobile Robot Using Sample-based Joint Probabilistic Data Association Filters.
   D. Schulz, W. Burgard, D. Fox, and A. B. Cremers. International Journal of Robotics Research (IJRR), 22(2), 2003.
8. Robust Monte Carlo Localization for Mobile Robots.
   S. Thrun, D. Fox, W. Burgard, and F. Dellaert. Artificial Intelligence (AIJ), 2001.
9. Integrated Plan-based Control of Autonomous Service Robots in Human Environments.
   M. Beetz, T. Arbuckle, T. Belker, M. Bennewitz, W. Burgard, A. Cremers, D. Fox, H. Grosskreutz, D. Haehnel, and D. Schulz. IEEE Intelligent Systems, 16 (5), 2001.
10. Probabilistic algorithms and the interactive museum tour-guide robot minerva.
    S. Thrun, M. Bennewitz, W. Burgard, A.B. Cremers, F. Dellaert, D. Fox, D. Hähnel, C. Rosenberg, N. Roy, J. Schulte, and D. Schulz. International Journal of Robotics Research (IJRR), 19 (11), 2000.
11. A Probabilistic Approach to Collaborative Multi-Robot Localization.
    D. Fox, W. Burgard, H. Kruppa, and S. Thrun. Auonomous Robots, 8 (3), 2000.
12. Web interfaces for mobile robots in public places.
    D. Schulz, W. Burgard, D. Fox, S. Thrun, and A.B. Cremers. IEEE-Magazine on Robotics and Automation, 7 (1), 2000.
13. Markov Localization for Mobile Robots in Dynamic Environments.
    D. Fox, W. Burgard, and S. Thrun. Journal of Artificial Intelligence Research (JAIR), 11, 1999.
    Honorable Mention: 2004 IJCAII-JAIR Best Paper Award.
14. Experiences with an interactive museum tour-guide robot.
    W. Burgard, A.B. Cremers, D. Fox, D. Hähnel, G. Lakemeyer, D. Schulz, W. Steiner, and S. Thrun. Artificial Intelligence (AIJ), 114 (1-2) 1999.
15. Active markov localization for mobile robots.
    D. Fox, W. Burgard, and S. Thrun. Robotics and Autonomous Systems (RAS), 25:195-207, 1998.
16. Integrating active localization into high-level robot control systems.
    M. Beetz, W. Burgard, D. Fox, and A.B. Cremers. Robotics and Autonomous Systems (RAS), 23:205-220, 1998.
17. A probabilistic approach to concurrent mapping and localization for mobile robots.
    S. Thrun, D. Fox, and W. Burgard. Machine Learning and Autonomous Robots (joint issue) (ML), (31), 1998.
18. The dynamic window approach to collision avoidance.
    D. Fox, W. Burgard, and S. Thrun. IEEE Robotics & Automation Magazine, 4(1), March 1997.
19. The mobile robot Rhino.
    J. Buhmann, W. Burgard, A.B. Cremers, D. Fox, T. Hofmann, F. Schneider, J. Strikos, and S. Thrun. AI Magazine, 16(2), Summer 1995

1. GP-BayesFilters: Bayesian Filtering Using Gaussian Process Prediction and Observation Models.
   J. Ko, and D. Fox. IROS-08.
2. Laser and Vision Based Outdoor Object Mapping
   B. Douillard, D. Fox, and F. Ramos. RSS-08.
3. GP-UKF: Unscented Kalman Filters with Gaussian Process Prediction and Observation Models.
   J. Ko, D. Klein, D. Fox, and D. Hähnel. IROS-07. Best Student Paper Award.
4. A Spatio-Temporal Probabilistic Model for Multi-Sensor Object Recognition.
   B. Douillard, D. Fox, and F. Ramos. IROS-07.
5. CRF-Matching: Conditional Random Fields for Feature-Based Scan Matching.
   F. Ramos, D. Fox, and H. Durrant-Whyte. RSS-07.
6. Gaussian Processes and Reinforcement Learning for Identification and Control of an Autonomous Blimp.
   J. Ko, D. Klein, D. Fox, and D. Hähnel. ICRA-07.
7. CRF-filters: Conditional Particle Filters for Sequential State Estimation .
   B. Limketkai, D. Fox, and L. Liao. ICRA-07.
8. Voronoi Random Fields: Extracting the Topological Structure of Indoor Environments via Place Labeling.
   S. Friedman, H. Pasula, and D. Fox. IJCAI-07.
9. Training Conditional Random Fields using Virtual Evidence Boosting.
   L. Liao, T. Choudhury, D. Fox, and H. Kautz. IJCAI-07.
10. WiFi-SLAM Using Gaussian Process Latent Variable Models.
    B. Ferris, D. Fox, and N. Lawrence. IJCAI-07.
11. Efficient Failure Detection on Mobile Robots Using Particle Filters with Gaussian Process Proposals.
    C. Plagemann, D. Fox, and W. Burgard. IJCAI-07.
12. Recognizing Activities and Spatial Context Using Wearable Sensors.
    A. Subramanya, A. Raj, J. Bilmes, and D. Fox. UAI-06.
13. Gaussian Processes for Signal Strength-Based Location Estimation.
    B. Ferris, D. Haehnel, and D. Fox. RSS-06.
14. Location-Based Activity Recognition.
    L. Liao, D. Fox, and H. Kautz. NIPS-05.
15. Large-Scale Localization from Wireless Signal Strength.
    J. Letchner, D. Fox, and A. LaMarca. AAAI-05.
16. Relational Object Maps for Mobile Robots.
    B. Limketkai, L. Liao, and D. Fox. IJCAI-05.
17. Location-Based Activity Recognition using Relational Markov Networks.
    L. Liao, D. Fox, and H. Kautz. IJCAI-05.
18. Autonomous Terrain Mapping and Classification Using Hidden Markov Models.
    J. Wolf, G. Sukhatme, D. Fox, and W. Burgard. ICRA-05.
19. Bayesian Color Estimation for Adaptive Vision-based Robot Localization.
    D. Schulz and D. Fox. IROS-04.
20. Reinforcement Learning for Sensing Strategies.
    C. Kwok and D. Fox. IROS-04.
21. Mapping and Localization with RFID Technology.
    D. Hähnel, W. Burgard, D. Fox, K. Fishkin, and M. Philipose. ICRA-04.
22. Opportunity Knocks: a System to Provide Cognitive Assistance with Transportation Services.
    D. J. Patterson, L. Liao, K. Gajos, M. Collier, N. Livic, K. Olson, S. Wang, D. Fox, and H. Kautz. UBICOMP-04.
23. Learning and Inferring Transportation Routines.
    L. Liao, D. Fox, and H. Kautz. AAAI-04. Outstanding Paper Award.
24. The Revisiting Problem in Mobile Robot Map Building: A Hierarchical Bayesian Approach.
    B. Stewart, J. Ko, D. Fox, and K. Konolige. UAI-03.
25. People Tracking with Anonymous and ID-sensors Using Rao-Blackwellised Particle Filters.
    D. Schulz, D. Fox, and J. Hightower. IJCAI-03.
26. Inferring High-Level Behavior from Low-Level Sensors.
    D.J. Patterson, L. Liao, D. Fox, and H. Kautz. UBICOMP-03.
27. A Practical, Decision-theoretic Approach to Multi-robot Mapping and Exploration.
    J. Ko, B. Stewart, D. Fox, K. Konolige, and B. Limketkai. IROS-03
28. Voronoi Tracking: Location Estimation Using Sparse and Noisy Sensor Data.
    L. Liao, D. Fox, J. Hightower, H. Kautz, and D. Schulz. IROS-03.
29. Map merging for distributed robot navigation.
    K. Konolige, D. Fox, J. Ko, B. Limketkai, and B. Stewart. IROS-03.
30. An Efficient FastSLAM Algorithm for Generating Maps of Large-scale Cyclic Environments From Raw Laser Range Measurements.
    D. Haehnel, W. Burgard, D. Fox, and S. Thrun. IROS-03.
31. Adaptive Real-time Particle Filters.
    C. Kwok, D. Fox, and M. Meila. ICRA-03.
32. Real-time Particle Filters.
    C. Kwok, D. Fox, and M. Meila. NIPS-02.
33. PlantCare: An Investigation in Practical Ubiquitous Systems
    A. LaMarca, W. Brunette, D. Koizumi, M. Lease, S.B. Sigurdsson, K. Sikorski, D. Fox, G. Borriello. UBICOMP-02.
34. An experimental comparison of localization methods continued.
    J.-S. Gutmann and D. Fox. IROS-02.
35. Making Sensor Networks Practical with Robots
    A. LaMarca, W. Brunette, D. Koizumi, M. Lease, S.B. Sigurdsson, K. Sikorski, D. Fox, G. Borriello. PERVASIVE-02.
36. Tracking Multiple Moving Objects with a Mobile Robot.
    D. Schulz, W. Burgard, D. Fox, and A. B. Cremers. CVPR-01.
37. KLD-Sampling: Adaptive Particle Filters.
    D. Fox. NIPS-01.
38. Tracking Multiple Moving Targets with a Mobile Robot using Particle Filters and Statistical Data Association.
    D. Schulz, W. Burgard, D. Fox, and A. B. Cremers. ICRA-01. Best Vision Paper Award Finalist.
39. Soccer-Robot Locatization Using Sporadic Visual Features.
    S. Enderle, M. Ritter, D. Fox, S. Sablatnög, G. Kraetzschmar and G. Palm. IAS-00.
40. Coordinated Deployment of Multiple, Heterogeneous Robots.
    R. Simmons, D. Apfelbaum, D. Fox, R. P. Goldman, K. Zita Haigh, D. J. Musliner, M. Pelican, and S. Thrun. IROS-00.
41. Monte carlo localization with mixture proposal distribution.
    S. Thrun, D. Fox, and W. Burgard. AAAI-00.
42. Coordination for multi-robot exploration and mapping.
    R. Simmons, D. Apfelbaum, W. Burgard, D. Fox, M. Moors, S. Thrun, and H. Younes. AAAI-00.
43. A real-time algorithm for mobile robot mapping with applications to multi-robot and 3d mapping.
    S. Thrun, W. Burgard, and D. Fox. ICRA-00. Best paper award
44. Collaborative Multi-Robot Exploration.
    W. Burgard, M. Moors, D. Fox, R. Simmons, and S. Thrun. ICRA-00.
45. Monte carlo localization: Efficient position estimation for mobile robots.
    D. Fox, W. Burgard, F. Dellaert, and S. Thrun. AAAI-99.
46. Collaborative Multi-Robot Localization.
    D. Fox, W. Burgard, H. Kruppa, and S. Thrun. KI-99. DAGM outstanding paper award.
47. Experiences with two deployed interactive tour-guide robots.
    S. Thrun, M. Bennewitz, W. Burgard, A.B. Cremers, F. Dellaert, D. Fox, D. Hähnel, C. Rosenberg, N. Roy, J. Schulte, D. Schulz, and W. Steiner. FSR-99.
48. Using the condensation algorithm for robust, vision-based mobile robot localization.
    F. Dellaert, W. Burgard, D. Fox, and S. Thrun. CVPR-99.
49. Monte Carlo hidden Markov models: Learning non-parametric models of partially observable stochastic processes.
    S. Thrun, J. Langford, and D. Fox. ICML-99.
50. Sonar-based mapping of large-scale mobile robot environments using EM.
    W. Burgard, D. Fox, H. Jans, C. Matenar, and S. Thrun. ICML-99.
51. MINERVA: A second generation mobile tour-guide robot.
    S. Thrun, M. Bennewitz, W. Burgard, A.B. Cremers, F. Dellaert, D. Fox, D. Hähnel, C. Rosenberg, N. Roy, J. Schulte, and D. Schulz. ICRA-99.
52. Monte carlo localization for mobile robots.
    F. Dellaert, D. Fox, W. Burgard, and S. Thrun. ICRA-99.
53. Coastal navigation: Mobile robot navigation with uncertainty in dynamic environments.
    N. Roy, W. Burgard, D. Fox, and S. Thrun. ICRA-99.
54. Position estimation for mobile robots in dynamic environments.
    D. Fox, W. Burgard, S. Thrun, and A.B. Cremers. AAAI-98.
55. Integrating topological and metric maps for mobile robot navigation: A statistical approach
    S. Thrun, J.-S. Gutmann, D. Fox, W. Burgard, and B. Kuipers. AAAI-98.
56. The interactive museum tour-guide robot.
    W. Burgard, A.B. Cremers, D. Fox, D. Hähnel, G. Lakemeyer, D. Schulz, W. Steiner, and S. Thrun. AAAI-98. Outstanding paper award.
57. An experimental comparison of localization methods.
    J.-S. Gutmann, W. Burgard, D. Fox, and K. Konolige. IROS-98. Best paper award.
58. Integrating global position estimation and position tracking for mobile robots: the Dynamic Markov Localization approach.
    W. Burgard, A. Derr, D. Fox, and A.B. Cremers. IROS-98.
59. A hybrid collision avoidance method for mobile robots.
    D. Fox, W. Burgard, S. Thrun, and A.B. Cremers. ICRA-98.
60. Probabilistic mapping of an environment by a mobile robot.
    S. Thrun, D. Fox, and W. Burgard. ICRA-98.
61. Active mobile robot localization.
    W. Burgard, D. Fox, and S. Thrun. IJCAI-97.
62. Fast grid-based position tracking for mobile robots.
    W. Burgard, D. Fox, and D. Hennig. KI-97.
63. Estimating the Absolute Position of a Mobile Robot Using Position Probability Grids.
    W. Burgard, D. Fox, D. Hennig, and T. Schmidt. AAAI-96.
64. Controlling synchro-drive robots with the dynamic window approach to collision avoidance.
    D. Fox, W. Burgard, and S. Thrun. IROS-96.

1. Distributed multi-robot mapping.
   D. Fox, J. Ko, B. Stewart, K. Konolige, and B. Limketkai. Multi-Robot Systems: From Swarms to Intelligent Automata, volume II. Kluwer, 2003.
2. CentiBOTS: Large-scale robot teams.
   K. Konolige, C. Ortiz, R. Vincent, A. Agno, M. Eriksen, B. Limketkai, M. Lewis, L. Briesemeister, E. Ruspini, D. Fox, J. Ko, B. Stewart, and L. Guibas. Multi-Robot Systems: From Swarms to Intelligent Automata, volume II. Kluwer, 2003.
3. A Probabilistic Approach to Collaborative Multi-Robot Localization.
   D. Fox, W. Burgard, H. Kruppa, and S. Thrun. Robot Teams: From Diversity to Polymorphism, AK Peters, 2002.
4. Particle filters for mobile robot localization.
   D. Fox, S. Thrun, F. Dellaert, and W. Burgard. Sequential Monte Carlo Methods in Practice. Springer Verlag, New York, 2000.
5. Map learning and high-speed navigation in RHINO.
   S. Thrun, A. Bücken, W. Burgard, D. Fox, T. Fröhlinghaus, D. Hennig, T. Hofmann, M. Krell, and T. Schimdt. Artificial Intelligence and Mobile Robots. MIT/AAAI Press, Cambridge, MA, 1998

1. Learning to Associate Image Features with CRF-Matching.
   F. Ramos, K. Waleed, and D. Fox. ISER-08.
2. A Spatio-Temporal Probabilistic Model for Multi-Sensor Multi-Class Ob ject Recognition.
   B. Douillard, D. Fox, and F. Ramos. ISRR-07.
3. Rao-Blackwellized Particle Filters for Recognizing Activities and Spatial Context From Wearable Sensors.
   A. Raj, A. Subramanya, D. Fox, and J. Bilmes. ISER-06.
4. Hierarchical Conditional Random Fields for GPS-based Activity Recognition.
   L. Liao, D. Fox, and H. Kautz. ISRR-05. Springer STAR Series
5. Fine-Grained Activity Recognition by Aggregating Abstract Object Usage.
   D. Patterson, D. Fox, H. Kautz, and M. Philipose. ISWC-05. Best Paper Award.
6. Map-based Multiple Model Tracking of a Moving Object.
   C. Kwok and D. Fox. Robocup Symposium 2004. RoboCup Scientific Challenge Award.
7. Centibots: Very large scale distributed robotic teams.
   K. Konolige, D. Fox, C. Ortiz, A. Agno, M. Eriksen, B. Limketkai, J. Ko, B. Morisset, D. Schulz, B. Stewart, R. Vincent. ISER-04. Springer STAR Series
8. A Hierarchical Bayesian Approach to the Revisiting Problem in Mobile Robot Map Building.
   D. Fox, J. Ko, K. Konolige, and B. Stewart. ISRR-03. Springer STAR Series
9. Research on statistical relational learning at the University of Washington.
   P. Domingos, Y. Abe, C. Anderson, A. Doan, D. Fox, A. Halevy, G. Hulten, H. Kautz, T. Lau, L. Liao, J. Madhavan, D. Mausam, Patterson, M. Richardson, S. Sanghai, D. Weld, and S. Wolfman. IJCAI-2003 Workshop on Learning Statistical Models from Relational Data, 2003.
10. Bayesian Techniques for Location Estimation.
    D. Fox, J. Hightower, H. Kautz, L. Liao, and D.J. Patterson. UbiComp Workshop on Location Estimation (invited), 2003.
11. Learning Occupancy Grid Maps of Non-Stationary Objects with Mobile Robots in Indoor Environments.
    B. Limketkai, R. Biswas, and S. Thrun. ISER-02.
12. Intelligent ubiquitous computing to support Alzheimer's patients: Enabling the cognitively disabled.
    D. Patterson, O. Etzioni, D. Fox, and H. Kautz. UbiCog'02: First International Workshop on Ubiquitous Computing for Cognitive Aids, 2002.
13. An overview of the assisted cognition project.
    H Kautz, L. Arnstein, G. Borriello, O. Etzioni, and D. Fox. AAAI Workshop on Automation as Caregiver: The Role of Intelligent Technology in Elder Care, 2002.
14. Real-time Particle Filters Using Mixtures of Samples Sets.
    C.T. Kwok, D. Fox and M. Meila AAAI/KDD/UAI-2002 Joint Workshop on Real-Time Decision Support and Diagnosis Systems, 2002.
15. Efficient Multi-Robot Localization Based on Monte Carlo Approximation.
    D. Fox, W. Burgard, H. Kruppa, and S. Thrun. ISRR-99, Springer Verlag, 2000.
16. Probabilistic Methods for Mobile Robot Mapping.
    D. Fox, W. Burgard, and S. Thrun. Proc. of the IJCAI-99 Workshop on Adaptive Spatial Representations of Dynamic Environments (invited presentation), 1999.
17. Markov localization for reliable robot navigation and people detection.
    D. Fox, W. Burgard, and S. Thrun. Modelling and Planning for Sensor-Based Intelligent Robot Systems, LNCS. Springer Verlag, 1999.
18. Coastal navigation: Robot motion with uncertainty.
    N. Roy, W. Burgard, D. Fox, and S. Thrun. AAAI Fall Symposium, 1998.
19. The museum tour-guide robot RHINO.
    W. Burgard, A.B. Cremers, D. Fox, D. Hähnel, G. Lakemeyer, D. Schulz, W. Steiner, and S. Thrun. Proc. of Fachgespräch Autonome Mobile Systeme (AMS), Germany, 1998.
20. Real robots for the real world - the RHINO museum tour-guide project.
    W. Burgard, D. Fox, D. Hähnel, G. Lakemeyer, D. Schulz, W. Steiner, S. Thrun, and A.B. Cremers. AAAI Spring Symposium on Integrating Robotics Research: Taking the Next Leap, 1998.
21. Active localization for service robot applications.
    M. Beetz, W. Burgard, A.B. Cremers, and D. Fox. Proc. of the 5th Symposium for Intelligent Robotics Systems (SIRS), Stockholm, Sweden, 1997.
22. Active mobile robot localization by entropy minimization.
    W. Burgard, D. Fox, and S. Thrun. Proc. of the Second Euromicro Workshop on Advanced Mobile Robots (Eurobot). IEEE Computer Society Press, 1997
23. Probabilistic state estimation in robotics.
    S. Thrun, D. Fox, and W. Burgard. Proc. of the Workshop on Self-Organization of Adaptive Behavior, Ilmenau, Germany (invited presentation). VDI-Verlag, 1997.
24. Position tracking with position probability grids.
    W. Burgard, D. Fox, D. Hennig, and Timo Schmidt. Proc. of the First Euromicro Workshop on Advanced Mobile Robots (Eurobot). IEEE Computer Society Press, 1996.