Probabilistic Robotics is a formal framework within robotics that employs probability theory as the foundational calculus for representing uncertainty and making decisions, distinguishing itself from deterministic approaches by explicitly modeling sensor noise, actuation errors, and environmental unpredictability through probabilistic state estimation and control.
218
Publications
17.6K
Citations
523
Authors
202
Institutions
Publications per year
2017–2026
37
Parents
Publications
218
1–5 of 218
Authors
523
- ST
9
h-index
- CB
5
h-index
- WB
5
h-index
- FD
3
h-index
- JP
3
h-index
1–5 of 523
Institutions
202
Carnegie Mellon University
Pittsburgh, United States
15 h-index
32 publications
12.5K citations
Massachusetts Institute of Technology
Cambridge, United States
10 h-index
17 publications
386 citations
University of California, Berkeley
Berkeley, United States
8 h-index
17 publications
756 citations
University of Illinois Urbana-Champaign
Urbana, United States
8 h-index
19 publications
398 citations
University of Maryland, College Park
College Park, United States
6 h-index
10 publications
180 citations
University of Freiburg
Freiburg im Breisgau, Germany
6 h-index
14 publications
1.9K citations
École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland
5 h-index
13 publications
289 citations
Georgia Institute of Technology
Atlanta, United States
5 h-index
17 publications
312 citations
1–8 of 202
Venues
- The International Journal of Robotics Research
IJRR · 8 publications · 1.1K citations
8
h-index
- 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems
Conference · 4 publications · 59 citations
4
h-index
- Autonomous Robots
4 publications · 319 citations
4
h-index
- IEEE Transactions on Robotics and Automation
3 publications · 108 citations
3
h-index
- IEEE Robotics and Automation Letters
3 publications · 209 citations
3
h-index
1–5