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Constraint-Driven Coordinated Control of Multi-Robot Systems
Robotics · Submitted 4 Nov 2018
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim The developed control framework has been tested on a team of ground mobile robots implementing long-term environmental monitoring.
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The abstract, sentence by sentence
In this paper we present a reformulation--framed as a constrained optimization problem--of multi-robot tasks which are encoded through a cost function that is to be minimized. The advantages of this approach are multiple. The constraint-based formulation provides a natural way of enabling long-term robot autonomy applications, where resilience and adaptability to changing environmental conditions are essential. Moreover, under certain assumptions on the cost function, the resulting controller is guaranteed to be decentralized. Furthermore, finite-time convergence can be achieved, while using local information only, and therefore preserving the decentralized nature of the algorithm. The developed control framework has been tested on a team of ground mobile robots implementing long-term environmental monitoring.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | In this paper we present a reformulation--framed as a constrained optimization problem--of multi-robot tasks which are encoded through a cost function that is to be minimized. | contribution 0.94 | 0.92 | 0.15 | asserted 1.00 |
| s1 | The advantages of this approach are multiple. | interpretation 0.75 | 0.32 | 0.04 | asserted 0.90 |
| s2 | The constraint-based formulation provides a natural way of enabling long-term robot autonomy applications, where resilience and adaptability to changing environmental conditions are essential. | interpretation 0.84 | 0.37 | 0.13 | asserted 0.97 |
| s3 | Moreover, under certain assumptions on the cost function, the resulting controller is guaranteed to be decentralized. | result 0.69 | 0.80 | 0.12 | asserted 0.97 |
| s4 | Furthermore, finite-time convergence can be achieved, while using local information only, and therefore preserving the decentralized nature of the algorithm. | result 0.61 | 0.80 | 0.12 | asserted 0.81 |
| s5 | The developed control framework has been tested on a team of ground mobile robots implementing long-term environmental monitoring. | method 0.57 | 0.95 | 0.15 | asserted 1.00 |
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The paper
Original abstract
In this paper we present a reformulation--framed as a constrained optimization problem--of multi-robot tasks which are encoded through a cost function that is to be minimized. The advantages of this approach are multiple. The constraint-based formulation provides a natural way of enabling long-term robot autonomy applications, where resilience and adaptability to changing environmental conditions are essential. Moreover, under certain assumptions on the cost function, the resulting controller is guaranteed to be decentralized. Furthermore, finite-time convergence can be achieved, while using local information only, and therefore preserving the decentralized nature of the algorithm. The developed control framework has been tested on a team of ground mobile robots implementing long-term environmental monitoring.
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How the literature uses it
3 arXiv papers cite this in 5 sentences
Papers citing it · 1 sentence without a confident label
Uses its method or tool 2 papers
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The control architecture makes use of the techniques presented in [ref] and [ref] for encoding the desired behaviours of the robot as dynamic constraints onto the control input.
Bidirectional Communication Control for Human-Robot Collaboration · Control Layer · 0.99
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This can be encoded in the following convex optimization problem [ref] : [equation] where $α(·)$ is an extended class $𝒦$ function[An extended class $𝒦$ is a function $ϕ:ℝ→ℝ$ such that $ϕ$ is strictly increasing and $ϕ(0)=0$] and where we have considered that the input of [ref] is $u=q̇$.
An Optimization Approach for a Robust and Flexible Control in Collaborative Applications · Control Barrier Functions based architecture · 0.95
Cites it as background 1 paper
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On the other hand, control barrier functions (CBFs) [ref] were proposed to guarantee that an agent remains in a certain region of the state space (i.e., forward invariance [ref] ) by using a locally accurate model of the agent dynamics (i.e., a model that accurately predicts a time derivative of the state at the current state and control input).
Constraint Learning for Control Tasks with Limited Duration Barrier Functions · Related Work · 1.00
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