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Defend the practicality of single-integrator models in multi-robot coordination control
Abstract
Single-integrator models have been widely used to model robot kinematics in multi-robot coordination control problems. However, it is also widely believed that this model is too simple to lead to practically useful control laws. In this paper, we prove that if a gradient-descent distributed control law designed for single integrators has been proved to be convergent for a given coordination task, then the control law can be readily modified to adapt for various motion constraints including velocity saturation, obstacle avoidance, and nonholonomic models. This result is valid for a wide range of coordination tasks. It defends the practical usefulness of many existing coordination control laws designed based on single-integrator models and suggests a new methodology to design coordination control laws subject motion constraints.
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This approach allows relaxing the constraint on obstacle avoidance to guarantee feasible solutions in tight situations by introducing a penalty term in the objective function (6a).
“Similarly to [22], [23], this approach allows relaxing the constraint on the obstacle avoidance to guarantee feasible solutions in tight situations by introducing a penalty term in the objective function (6a), i.e., ‖ s j ‖ 2 Q 2 .”
From A Perception-Aware NMPC for Vision-Based Target Tracking and Collision Avoidance with a Multi-Rotor UAV (2022) · cites this paper as [23]
The Obstacle Avoidance section (p. 5) describes steering a robot away from an obstacle by changing its motion direction. It does not describe relaxing an obstacle-avoidance constraint, adding a penalty term to an objective function, or guaranteeing feasibility in tight situations. Searches for penalty terms, slack variables, and feasibility found no passage supporting that attributed mechanism. (LLM, conf=0.76)
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Cites
Consensus Problems in Networks of Agents With Switching Topology and Time-Delays
Olfati-Saber, R., & Murray, R. M. (2004) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2004.834113 · Cited by 12,788 · cited 1×
“is the consensus protocol proposed in [10], [11].”
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Research works printed but not linked: 16
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Dmytruk, A., Silano, G., Bicego, D., Licea, D. B., & Saska, M. (2022) · 2022 International Conference on Unmanned Aircraft Systems (ICUAS) · doi:10.1109/icuas54217.2022.9836071 · Cited by 8
“described in [24], demonstrating numerical convergence with this model guarantees convergence even with more complex models, as long as the control law is suitably adapted to the various motion constraints.”
Background
Metadata
- Authors
- Zhao, S., & Sun, Z.
- Affiliations
- University of Sheffield (GB)
- Australian National University (AU)
- Venue
- 2017 13th IEEE International Conference on Control & Automation (ICCA)
- Publisher
- IEEE
- Published
- 2017-07
- Pages
- 666-671
- ISSN
- 1948-3449 (ISSN-L)
- OpenAlex
- W2612914963
- Cited by
- 23
- References
- 1
- Citations by year
- 2025: 2 · 2024: 5 · 2023: 4 · 2022: 3 · 2021: 4 · 2020: 3 · 2019: 1 · 2017: 1
- FWCI
- 1.09
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Control and Automation (publishedVersion)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
- ANU Open Research (Australian National University) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Distributed Control Multi-Agent Systems
- Physical Sciences › Engineering › Control and Systems Engineering › Control and Dynamics of Mobile Robots
- Physical Sciences › Engineering › Mechanical Engineering › Modular Robots and Swarm Intelligence
- Keywords
- multi-robot coordination, distributed control, convergence analysis, velocity saturation, obstacle avoidance, nonholonomic mobile robots, motion constraints, robot kinematics
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