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Temnothorax albipennis migration inspired semi-flocking control for mobile sensor networks.
Wanmai Yuan1, Nuwan Ganganath2, Chi-Tsun Cheng3
1School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, People's Republic of China.
Chaos (Woodbury, N.Y.)
|July 4, 2019
Summary
This study introduces a new distributed semiflocking algorithm for mobile sensor networks (MSNs). This algorithm enhances target detection and tracking while reducing energy consumption on various terrains.
Area of Science:
- Robotics and Control Systems
- Distributed Systems
- Sensor Networks
Background:
- Mobile sensor networks (MSNs) are crucial for target seeking and tracking.
- Agent dynamics and interactions pose challenges for cooperative control in MSNs.
Purpose of the Study:
- To propose a distributed semiflocking algorithm for MSNs.
- To improve target detection and tracking efficiency and energy consumption.
Main Methods:
- A distributed semiflocking algorithm inspired by the Temnothorax albipennis migration model.
- Simulation-based performance evaluation compared to existing algorithms.
Main Results:
- The proposed algorithm enables faster target detection and lower energy consumption in MSNs.
- The algorithm demonstrates energy efficiency on both flat and uneven terrains.
Conclusions:
- The distributed semiflocking algorithm offers promising performance for target seeking and tracking in MSNs.
- This approach enhances the robustness and efficiency of mobile sensor network operations.
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