The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Structured control for autonomous robots
Abstract
To operate in rich, dynamic environments, autonomous robots must be able to effectively utilize and coordinate their limited physical and computational resources. As complexity increases, it becomes necessary to impose explicit constraints on the control of planning, perception, and action to ensure that unwanted interactions between behaviors do not occur. This paper advocates developing complex robot systems by layering reactive behaviors onto deliberative components. In this structured control approach, the deliberative components handle normal situations and the reactive behaviors, which are explicitly constrained as to when and how they are activated, handle exceptional situations. The Task Control Architecture (TCA) has been developed to support this approach. TCA provides an integrated set of control constructs useful for implementing deliberative and reactive behaviors. The control constructs facilitate modular and evolutionary system development: they are used to integrate and coordinate planning, perception, and execution, and to incrementally improve the efficiency and robustness of the robot systems. To date, TCA has been used in implementing a half-dozen mobile robot systems, including an autonomous six-legged rover and indoor mobile manipulator.>
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Citations
Cites
A robust layered control system for a mobile robot
Brooks, R. (1986) · IEEE Journal on Robotics and Automation · doi:10.1109/jra.1986.1087032 · Cited by 7,799
An architecture for reflexive autonomous vehicle control
Payton, D. (1986) · Proceedings. 1986 IEEE International Conference on Robotics and Automation · doi:10.1109/robot.1986.1087458 · Cited by 200
Cited by
Robot Operating System 2: Design, architecture, and uses in the wild
Macenski, S., Foote, T., Gerkey, B., Lalancette, C., & Woodall, W. (2022) · Science Robotics · doi:10.1126/scirobotics.abm6074 · Cited by 1,585
Alami, R., Chatila, R., Fleury, S., Ghallab, M., & Ingrand, F. (1998) · The International Journal of Robotics Research · doi:10.1177/027836499801700402 · Cited by 561
Deliberation for autonomous robots: A survey
Ingrand, F., & Ghallab, M. (2017) · Artificial Intelligence · doi:10.1016/j.artint.2014.11.003 · Cited by 309
The CLARAty architecture for robotic autonomy
Volpe, R., Nesnas, I., Estlin, T., Mutz, D., Petras, R., & Das, H. (2002) · 2001 IEEE Aerospace Conference Proceedings (Cat. No.01TH8542) · doi:10.1109/aero.2001.931701 · Cited by 265
Understanding World or Predicting Future? A Comprehensive Survey of World Models
Ding, J., Zhang, Y., Shang, Y., Zhang, Y., Zong, Z., Feng, J., Yuan, Y., Su, H., Li, N., Sukiennik, N., et al. (2026) · ACM Computing Surveys · doi:10.1145/3746449 · Cited by 169
“Autonomous vehicles typically utilize cameras, radar, and lidar to perceive the real-world, gathering information through images, video data, and point cloud data.”
Metadata
- Authors
- Simmons, R. G.
- Venue
- IEEE Transactions on Robotics and Automation
- Published
- 1994
- Volume
- 10
- Issue
- 1
- Pages
- 34-43
- ISSN
- 1042-296X (ISSN-L)
- OpenAlex
- W2133453031
- Cited by
- 344
- References
- 2
- FWCI
- 22.41
- Type
- journal article
- Language
- en
- Open access
- closed
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- Simmons, R. G. (1994). Structured control for autonomous robots. IEEE Transactions on Robotics and Automation. https://doi.org/10.1109/70.285583
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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