Detecting and modeling doors with mobile robots

@article{Anguelov2004DetectingAM,
  title={Detecting and modeling doors with mobile robots},
  author={Dragomir Anguelov and Daphne Koller and Evan Parker and Sebastian Thrun},
  journal={IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004},
  year={2004},
  volume={4},
  pages={3777-3784 Vol.4}
}
  • Dragomir Anguelov, D. Koller, +1 author S. Thrun
  • Published 2004
  • Engineering, Computer Science
  • IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004
We describe a probabilistic framework for detection and modeling of doors from sensor data acquired in corridor environments with mobile robots. The framework captures shape, color, and motion properties of door and wall objects. The probabilistic model is optimized with a version of the expectation maximization algorithm, which segments the environment into door and wall objects and learns their properties. The framework allows the robot to generalize the properties of detected object… Expand
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References

SHOWING 1-10 OF 39 REFERENCES
Learning Hierarchical Object Maps of Non-Stationary Environments with Mobile Robots
TLDR
This paper presents an algorithm for learning object models of non-stationary objects found in office-type environments through a two-level hierarchical representation that outperforms a previously developed non-hierarchical algorithm that models objects but lacks class templates. Expand
Map building with mobile robots in populated environments
TLDR
This paper uses a probabilistic method to track multiple people and to incorporate the results of the tracking technique into the mapping process, which results in more accurate maps. Expand
A Distributed Model for Mobile Robot Environment-Learning and Navigation
TLDR
A distributed method for mobile robot navigation, spatial learning, and path planning is presented and the main issues addressed are: distributed, procedural, and qualitative representation and computation, emergent behaviors, dynamic landmarks, minimized communication. Expand
Using EM to Learn 3D Models of Indoor Environments with Mobile Robots
TLDR
An algorithm for generating compact 3D models of indoor environments with mobile robots using the expectation maximization algorithm to fit a lowcomplexity planar model to 3D data collected by range finders and a panoramic camera is described. Expand
Position referencing and consistent world modeling for mobile robots
  • R. Chatila, J. Laumond
  • Engineering, Computer Science
  • Proceedings. 1985 IEEE International Conference on Robotics and Automation
  • 1985
TLDR
The approach proposed in this paper relies on the use of a multisensory system, favo ring of the data collected by the more accurate sensor in a given situation, averaging of different but consistent measurements of the same entity weighted with their associated uncertainties. Expand
A robot exploration and mapping strategy based on a semantic hierarchy of spatial representations
TLDR
A robust qualitative method is developed that can build an accurate map of a previously unkown environment in spite of substantial random and systematic sensorimotor error and successful navigation is not critically dependent on the accuracy, or even the existence, of the geometrical description. Expand
MAGELLAN: An Integrated Adaptive Architecture for Mobile Robotics
Abstract : In this paper we describe MAGELLAN, an integrated architecture for mobile robotics. The system represents its spatial knowledge in terms of a topological network that connects a set ofExpand
An Atlas framework for scalable mapping
TLDR
Atlas is described, a hybrid metrical/topological approach to SLAM that achieves efficient mapping of large-scale environments using a graph of coordinate frames that captures the local environment and the current robot pose along with the uncertainties of each. Expand
A real-time algorithm for mobile robot mapping with applications to multi-robot and 3D mapping
  • S. Thrun, W. Burgard, D. Fox
  • Computer Science
  • Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065)
  • 2000
We present an incremental method for concurrent mapping and localization for mobile robots equipped with 2D laser range finders. The approach uses a fast implementation of scan-matching for mapping,Expand
Incremental mapping of large cyclic environments
  • Jens-Steffen Gutmann, K. Konolige
  • Computer Science
  • Proceedings 1999 IEEE International Symposium on Computational Intelligence in Robotics and Automation. CIRA'99 (Cat. No.99EX375)
  • 1999
TLDR
A method, called local registration and global correlation, for reliable reconstruction of consistent global maps from dense range data, is presented, attractive because it is incremental, producing an updated map with every new sensor input; and runs in constant time independent of the size of the map. Expand
...
1
2
3
4
...