The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Layered costmaps for context-sensitive navigation
Abstract
Many navigation systems, including the ubiquitous ROS navigation stack, perform path-planning on a single costmap, in which the majority of information is stored in a single grid. This approach is quite successful at generating collision-free paths of minimal length, but it can struggle in dynamic, people-filled environments when the values in the costmap expand beyond occupied or free space. We have created and implemented a new method called layered costmaps, which work by separating the processing of costmap data into semantically-separated layers. Each layer tracks one type of obstacle or constraint, and then modifies a master costmap which is used for the path planning. We show how the algorithm can be integrated with the open-source ROS navigation stack, and how our approach is easier to fine-tune to specific environmental contexts than the existing monolithic one. Our design also results in faster path planning in practical use, and exhibits a cleaner separation of concerns that the original architecture. The new algorithm also makes it possible to represent complex cost values in order to create navigation behavior for a wide range of contexts.
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Cites
ROS: an open-source Robot Operating System
Quigley, M. (2009) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · Cited by 8,729
Sensor Fusion in Certainty Grids for Mobile Robots
Moravec, H. P. (1989) · Sensor Devices and Systems for Robotics · doi:10.1007/978-3-642-74567-6_19 · Cited by 964
The Office Marathon: Robust navigation in an indoor office environment
Marder-Eppstein, E., Berger, E., Foote, T., Gerkey, B., & Konolige, K. (2010) · 2010 IEEE International Conference on Robotics and Automation · doi:10.1109/robot.2010.5509725 · Cited by 517
A Human Aware Mobile Robot Motion Planner
Sisbot, E. A., Marin-Urias, L. F., Alami, R., & Simeon, T. (2007) · IEEE Transactions on Robotics · doi:10.1109/tro.2007.904911 · Cited by 499
COMPANION: A Constraint-Optimizing Method for Person-Acceptable Navigation
Kirby, R., Simmons, R. G., & Forlizzi, J. (2009) · IEEE RO-MAN · doi:10.1109/roman.2009.5326271 · Cited by 180
Integration of sonar and stereo range data using a grid-based representation
Matthies, L. H., & Elfes, A. (2003) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.1988.12145 · Cited by 176
Learning occupancy grids with forward models
Thrun, S. (2002) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2001.977219 · Cited by 107
Tuning Cost Functions for Social Navigation
Lu, D. V., Allan, D., & Smart, W. D. (2013) · Lecture notes in computer science · doi:10.1007/978-3-319-02675-6_44 · Cited by 27
Self-citationEfficiently Using Cost Maps For Planning Complex Maneuvers
Ferguson, D., & Likhachev, M. A. (2008) · Scholarly Commons (University of Pennsylvania) · Cited by 21
Cited by
SEAN 2.0: Formalizing and Generating Social Situations for Robot Navigation
Tsoi, N., Xiang, A., Yu, P., Sohn, S. S., Schwartz, G., Ramesh, S., Hussein, M., Gupta, A. W., Kapadia, M., & Vazquez, M. (2022) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2022.3196783 · Cited by 44
Metadata
- Authors
- Lu, D. V., Hershberger, D., & Smart, W. D.
- Venue
- 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
- Publisher
- IEEE
- Published
- 2014-09
- Pages
- 709-715
- OpenAlex
- W2021096542
- Cited by
- 295
- References
- 9
- FWCI
- 5.95
- Type
- conference paper
- Language
- en
- Open access
- closed
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