Collective fission behavior in swarming systems with density-based interaction

Zhang, Shuai; Lei, Xiaokang; Zheng, Zhicheng; Peng, Xingguang

doi:10.1016/j.physa.2022.127723

Cited by 7 publications

(5 citation statements)

References 31 publications

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“…There is still an insufficient investigation and utilization of density information to reflect the group-level configurations. In our previous work [12,13,34], we use a novel density-based framework to design the control policy of swarm robots; these studies showed that density-based interactions can endow the swarm robots with various unique capabilities, such as spontaneously forming multiple-/single-ring configurations and symmetric shrinking and expanding [34]. These backgrounds motivate us to address the TSC task by using the density-based control framework for swarm robots.…”

Section: Motivation and Contributionsmentioning

confidence: 99%

“…To estimate the spatial density field of objects (i.e., the robots and targets) by our swarm robots, we adopt the kernel-function-based definition of spatial density from our previous works [13,34]. For an object i with position X , a locally spatial density field is attached to its neighborhood, and the intensity (i.e., density) of this spatial-relevant field decays monotonically with increasing distance from the object.…”

Section: Spatial Density Estimationmentioning

confidence: 99%

“…In our earlier studies [13,34], based on the concept of the spatial density field, we proposed a novel density-based control framework for swarm robotics. In [13], we used the density-based control framework to achieve swarm robots' trapping of multiple targets, and the properties of the density-based control framework are analyzed in detail in [14].…”

Section: Density-driven Control Framework For Swarm Robotsmentioning

confidence: 99%

“…Based on the density-driven control framework mentioned above, the swarm robot can perform specific abilities such as group splitting, group merging, multi-target trapping, and multi-ring encirclement with remarkable robustness and scalability [34]. This paper focuses on the TSC mission, we employ the density-driven control framework to design the distributed control policy for the searchers and the collectors to search, evaluate, and collect the targets with patch distribution.…”

Section: Density-driven Control Framework For Swarm Robotsmentioning

confidence: 99%

“…Note that although this information is collected globally, the control of each robot only uses the local information within its sensing range. A more detailed description about the SwarmBang robot system can be found in our previous work [12,13,34]. The control parameters of the searching robots are v s 0 = 20 mm/s, R s = 2 m, δ s = 0.5; the collecting robots are set as v c 0 = 10 mm/s, R c = 1 m, δ c = 0.1.…”

Section: Experiments Set-upmentioning

confidence: 99%

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Self-Organized Patchy Target Searching and Collecting with Heterogeneous Swarm Robots Based on Density Interactions

et al. 2023

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The issue of searching and collecting targets with patchy distribution in an unknown environment is a challenging task for multiple or swarm robots because the targets are unevenly dispersed in space, which makes the traditional solutions based on the idea of path planning and full spatial coverage very inefficient and time consuming. In this paper, by employing a novel framework of spatial-density-field-based interactions, a collective searching and collecting algorithm for heterogeneous swarm robots is proposed to solve the challenging issue in a self-organized manner. In our robotic system, two types of swarm robots, i.e., the searching robots and the collecting robots, are included. To start with, the searching robots conduct an environment exploration by means of formation movement with Levy flights; when the targets are detected by the searching robots, they spontaneously form a ring-shaped envelope to estimate the spatial distribution of targets. Then, a single robot is selected from the group to enter the patch and locates at the patch’s center to act as a guiding beacon. Subsequently, the collecting robots are recruited by the guiding beacon to gather the patch targets; they first form a ring-shaped envelope around the target patch and then push the scattered targets inward by using a spiral shrinking strategy; in this way, all targets eventually are stacked near the center of the target patch. With the cooperation of the searching robots and the collecting robots, our heterogeneous robotic system can operate autonomously as a coordinated group to complete the task of collecting targets in an unknown environment. Numerical simulations and real swarm robot experiments (up to 20 robots are used) show that the proposed algorithm is feasible and effective, and it can be extended to search and collect different types of targets with patchy distribution.

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Section: Motivation and Contributionsmentioning

confidence: 99%

Section: Spatial Density Estimationmentioning

confidence: 99%

Section: Density-driven Control Framework For Swarm Robotsmentioning

confidence: 99%

Section: Density-driven Control Framework For Swarm Robotsmentioning

confidence: 99%

Section: Experiments Set-upmentioning

confidence: 99%

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Self-Organized Patchy Target Searching and Collecting with Heterogeneous Swarm Robots Based on Density Interactions

et al. 2023

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Self-organized multi-target trapping of swarm robots with density-based interaction

Lei

Zhang

Xiang

et al. 2023

Complex Intell. Syst.

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The task of multi-target trapping in swarm robots can often be solved by global shape planning and target assignment, but it still remains a challenge to achieve fully self-organized multi-target trapping behavior based on local information. In this paper, inspired by the concept of spatial density in physics and biology, we proposed a novel density-based method to enable the swarm robots to entrap multiple targets with either single-ring, multi-ring or multi-subgroup formation in a distributed and self-organized way while neither communication among robots nor encirclement function is required. Each robot’s local spatial density is considered as the main clue for the individual’s motion decision-making and the enclosed configurations emerge from such individual-level interactions rather than being explicitly designed. Numerical simulations and real robotic experiments are conducted to validate the effectiveness of the proposed method. The results show that the proposed self-organized trapping method allows a swarm of robots to entrap multiple moving targets in a stable, flexible, noise-tolerate and size-scalable fashion.

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Self-organized swarm robot for multi-target trapping based on self-regulated density interaction

Zhou,

Tao,

Lei

et al. 2024

Information Sciences

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Collective fission behavior in swarming systems with density-based interaction

Cited by 7 publications

References 31 publications

Self-Organized Patchy Target Searching and Collecting with Heterogeneous Swarm Robots Based on Density Interactions

Self-Organized Patchy Target Searching and Collecting with Heterogeneous Swarm Robots Based on Density Interactions

Self-organized multi-target trapping of swarm robots with density-based interaction

Self-organized swarm robot for multi-target trapping based on self-regulated density interaction

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