The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
The Hybrid Reciprocal Velocity Obstacle
Abstract
We present the hybrid reciprocal velocity obstacle for collision-free and oscillation-free navigation of multiple mobile robots or virtual agents. Each robot senses its surroundings and acts independently without central coordination or communication with other robots. Our approach uses both the current position and the velocity of other robots to compute their future trajectories in order to avoid collisions. Moreover, our approach is reciprocal and avoids oscillations by explicitly taking into account that the other robots sense their surroundings as well and change their trajectories accordingly. We apply hybrid reciprocal velocity obstacles to iRobot Create mobile robots and demonstrate direct, collision-free, and oscillation-free navigation.
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Cites
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An Introduction to the Kalman Filter
Welch, G., & Bishop, G. (1995) · CiteSeer X (The Pennsylvania State University) · Cited by 4,895
LaValle, S. M. (2006) · Cited by 4,177
The dynamic window approach to collision avoidance
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RRT-connect: An efficient approach to single-query path planning
Kuffner, J. J., & LaValle, S. M. (2000) · Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065) · doi:10.1109/robot.2000.844730 · Cited by 3,555
Marker tracking and HMD calibration for a video-based augmented reality conferencing system
Kato, H., & Billinghurst, M. (2003) · Proceedings 2nd IEEE and ACM International Workshop on Augmented Reality (IWAR'99) · doi:10.1109/iwar.1999.803809 · Cited by 2,194
Motion Planning in Dynamic Environments Using Velocity Obstacles
Fiorini, P., & Shiller, Z. (1998) · The International Journal of Robotics Research · doi:10.1177/027836499801700706 · Cited by 2,008
Reciprocal n-Body Collision Avoidance
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Self-citationReciprocal Velocity Obstacles for real-time multi-agent navigation
van den Berg, J., Lin, M., & Manocha, D. (2008) · 2008 IEEE International Conference on Robotics and Automation · doi:10.1109/robot.2008.4543489 · Cited by 1,722
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Cited by
Zooids: Building Blocks for Swarm User Interfaces
Le Goc, M., Kim, L. H., Parsaei, A., Fekete, J.-D., Dragicevic, P., & Follmer, S. (2016) · Proceedings of the 29th Annual Symposium on User Interface Software and Technology · doi:10.1145/2984511.2984547 · Cited by 267
Model Predictive Control for Aerial Collision Avoidance in Dynamic Environments
Castillo-Lopez, M., Sajadi-Alamdari, S. A., Sanchez-Lopez, J. L., Olivares-Mendez, M. A., & Voos, H. (2018) · 2018 26th Mediterranean Conference on Control and Automation (MED) · doi:10.1109/med.2018.8442967 · Cited by 44
Metadata
- Authors
- Snape, J., Berg, J. V. D., Guy, S. J., & Manocha, D.
- Venue
- IEEE Transactions on Robotics
- Published
- 2011-08
- Volume
- 27
- Issue
- 4
- Pages
- 696-706
- ISSN
- 1552-3098 (ISSN-L)
- 1941-0468
- OpenAlex
- W2097639646
- Cited by
- 448
- References
- 18
- FWCI
- 16.91
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
