Reconfigurable multi-robot coordination with guaranteed convergence in obstacle cluttered environments under local communication

Vrohidis, Constantinos; Vlantis, Panagiotis; Bechlioulis, Charalampos P.; Kyriakopoulos, Kostas J.

doi:10.1007/s10514-017-9660-y

Cited by 13 publications

(11 citation statements)

References 37 publications

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“…However, two disc‐shaped obstacles with radius ρ o =1 locate in the environment, blocking the direct way toward the target. Figure shows the results of the multirobot navigation using the approaches proposed in this work and by Vrohidis et al, respectively. Our approach successfully plans a path to bypass obstacles and drive the robots to move along the path to reach the target.…”

Section: Simulations and Resultsmentioning

confidence: 97%

“…(a) The states and trajectories of robots using the approach proposed in this work. (b) The states and trajectories of robots using the approach proposed by Vrohidis et al…”

Section: Simulations and Resultsmentioning

confidence: 99%

“…The time costs using the approaches proposed in this work (rapidly exploring random tree [RRT]‐distributed navigation function [DNF]) and by Vrohidis et al (DNF only)…”

Section: Simulations and Resultsmentioning

confidence: 99%

“…To apply the above framework in a navigation scenario for a team of nonholonomic robots, we implement it by developing a novel hybrid algorithm. Specifically, we extend the DNF‐based controller to nonholonomic models and integrate it with a basic version of RRT‐based path planner. The RRTs are attractive because they work well in practice problems with complex constraints …”

Section: Proposed Methodsmentioning

confidence: 99%

“…Li et al designed a potential field that integrates the navigation requirement, connectivity constraint, and obstacle avoidance simultaneously by building a DNF. Vrohidis et al considered collision avoidance constraint on the basis of the work of Li et al However, both focused only on first‐order integrator models and simple scenarios. Kan et al extended the navigation function method to the differential drive model.…”

Section: Related Workmentioning

confidence: 99%

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Distributed coordination with connectivity maintenance for nonholonomic robots

Huang

Wang

et al. 2018

Computer Animation & Virtual

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Multirobot systems have been studied extensively in the recent years. Maintaining connectivity has significant impacts on the stability and convergence of the multirobot systems. In this work, we design a three-layer framework for multirobot coordination. Furthermore, a novel distributed algorithm is proposed to achieve the navigation objective while satisfying connectivity maintenance and collision avoidance constraints. The algorithm is a hybrid of an rapidly exploring random tree-based planner and an extended distributed navigation function-based controller. The coordination framework and the distributed algorithm are demonstrated to be effective through a series of illustrative simulations. They outperform the current state-of-the-art method in terms of efficiency and applicability.

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Section: Simulations and Resultsmentioning

confidence: 97%

“…(a) The states and trajectories of robots using the approach proposed in this work. (b) The states and trajectories of robots using the approach proposed by Vrohidis et al…”

Section: Simulations and Resultsmentioning

confidence: 99%

“…The time costs using the approaches proposed in this work (rapidly exploring random tree [RRT]‐distributed navigation function [DNF]) and by Vrohidis et al (DNF only)…”

Section: Simulations and Resultsmentioning

confidence: 99%

Section: Proposed Methodsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 3 more Smart Citations

Distributed coordination with connectivity maintenance for nonholonomic robots

Huang

Wang

et al. 2018

Computer Animation & Virtual

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Distributed cohesive configuration controller for a swarm with low‐cost platforms

Lee

2022

Journal of Field Robotics

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This study presents a cohesive configuration controller for distributed space coverage by a swarm of robots. The goal is to build a dense, convex network that is robust against disconnection while robots are flocking with only incomplete knowledge about the network. The controller is an integrated framework of two different algorithms. First, we present a boundary force algorithm: physics‐based swarm intelligence that borrows the concept of surface tension force between liquid molecules. The combination of such a force with conventional flocking produces a convex and dense configuration without knowledge of the complete geometry of a robot network. Second, robots distributively determine when a configuration is on the verge of disconnection by identifying a local articulation point—a region where the removal of a single robot will change the local topology. When such a point is detected, robots switch their behavior to clustering, which aggregates them around the vulnerable region to remove every articulation point and retain a connected configuration. Finally, we introduced an index that objectively represents the level of risk of a robot configuration against the massive fragmentation, called vulnerability index. We provide theoretical performance analyses of each algorithm and validate the results with simulations and experiments using a set of low‐cost robots.

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