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Cellular reaction gene regulation network for swarm robots with pattern formation maneuvering control
Zhenlong Xiao1, Xin Wang1, Lin Hong1
1Department of Mechanical and Automation Engineering, Harbin Institute of Technology, Shenzhen, China.
Frontiers in Neurorobotics
|November 7, 2022
Summary
Swarm robots can now maintain stable formations while maneuvering using a novel cellular reaction gene regulatory network (CR-GRN). This bio-inspired approach enhances cooperation in complex environments.
Area of Science:
- Robotics
- Computational Biology
- Swarm Intelligence
Background:
- Swarm robots use gene regulatory networks (GRNs) for self-organized pattern formation without global knowledge.
- Maintaining formation stability during maneuvering is challenging due to local reaction rules.
Purpose of the Study:
- To propose a novel cellular reaction gene regulatory network (CR-GRN) for stable pattern formation maneuvering control in swarm robots.
- To enhance swarm robot cooperation and adaptability in complex environments.
Main Methods:
- Developed a CR-GRN integrating robots, environment, and target patterns for emergent swarm behavior.
- Utilized a novel diffusion equation to simulate morphogen diffusion for stable pattern generation.
- Defined internal/external cell states using genes, proteins, and morphogens in a feedback network.
Main Results:
- The CR-GRN successfully met turning curvature requirements and maintained robot uniformity.
- Simulation experiments validated the CR-GRN's effectiveness in stable adaptive pattern generation.
- Demonstrated improved cooperation and stable formations for robots in complex environments.
Conclusions:
- The CR-GRN enables swarm robots to maintain stable formations during maneuvering.
- This bio-inspired approach significantly enhances swarm robot adaptability and cooperative capabilities.
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