Probabilistic robotics

Sebastian Thrun · CACM · 2002

Summary

This research presents a novel approach to planning and navigation algorithms that exploit statistics gleaned from uncertain, imperfect real-world environments to guide robots toward their goals and around obstacles.

Type: article
Published: 2002-03-01
Cited by: 7,657
References: 11
DOI: https://doi.org/10.1145/504729.504754
OpenAlex: https://openalex.org/W2336416123
Semantic Scholar: https://api.semanticscholar.org/CorpusID:14552983

Keywords

Artificial intelligence, Robotics, Computer science, Probabilistic logic, Robot

References

Sequential Monte Carlo Methods in PracticeArnaud Doucet — 2001
The optimal control of par-tially observable Markov processesEdward J. Sondik — 1971
Coordination for Multi-Robot Exploration and MappingReid Simmons, David Apfelbaum, Wolfram Burgard — 2000
An Affective Mobile Robot Educator with a Full-Time JobIllah Nourbakhsh, Judith Bobenage, S. Grange — 1999
Coastal Navigation with Mobile RobotsNicholas Roy, Sebastian Thrun — 1999
Towards terrain-aided navigation for underwater roboticsStefan B. Williams, Gamini Dissanayake, Hugh Durrant‐Whyte — 2001
An Autonomous Guided Vehicle for Cargo Handling ApplicationsHugh Durrant‐Whyte — 1995
Probabilistic Algorithms and the Interactive Museum Tour-Guide Robot MinervaSebastian Thrun, Michael Beetz, Maren Bennewitz — 2000
Using EM to Learn 3D Models of Indoor Environments with Mobile RobotsYufeng Liu, Rosemary Emery, Deepayan Chakrabarti — 2001
The EM algorithm and extensionsJames E. Gentle, Geoffrey J. McLachlan, T. Krishnan — 1996
Proceedings of the international conference « Territorial Intelligence, Socioecological Transition ans resiliency of the territories »Jean-Jacques Girardot — 2013
The EM Algorithm and ExtensionsDebashis Kushary, Geoffrey J. McLachlan, Thriyambakam Krishnan — 1998

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Probabilistic robotics

Summary

Keywords

References

Cited by

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