This document summarizes a presentation on using fractional complex central moments to control the trajectory of unmanned vehicle swarms. It introduces the research team members and their areas of focus. It then discusses the status of cooperative robot research and presents their Selabot project, which aims to develop a practical swarm robot model for various environments. The document outlines the problem of coordinating the motion of multi-sensor unmanned vehicles and proposes using particle swarm optimization with fractional central moments to achieve real-time dynamic control. It provides examples of potential swarm robot applications and concludes by defining complex center moments and related trajectory control methods.

1. High order fractional complex
central moment for UXV swarm
trajectory controls
Presenter: Jun Steed Huang
Principal Investigator：Yuhui Shi
Nanshan Zhiyuan Computer and Internet Technology Production and Research base
May 25, 2017

2. The Team Members
• Yuhui Shi is a Chair Professor.
• Jun Steed Huang is a Research Fellow.
• Chang Shao is a Research Associate Math.
• Qiqi Duan is a Research Associate SW.
• Lijun Sun is a Research Associate FW.
• Fan Yang is a Research Associate HW.
• 张胡梦圆, Research Assistant EE.
• 周朦, Research Assistant CS.
• 吴书琴, Research Assistant CS.
• 许梦婷, Research Assistant Math.
• 马策, Research Assistant CS.
• 李汉青, Research Assistant CS.
• 梁轩铨, Research Assistant Phy.
• 周雪凝, Research Assistant Bio.
• 倪犀子, Research Assistant CS.
• 张孜晟, Research Assistant Chem.

3. Yuhui Shi, Chair Professor, IEEE Fellow, BSO, PSO, evolutionary computation,
swarm intelligence, machine learning, data science.
Jun Steed Huang, Research Fellow, Ottawa Carleton Adj Prof, Canadian Academy
of Sciences Chemical Biological Electromagnetic Nuclear Radiation Water Land and
Space Soft Landing Emergency Countermeasure Plan.
研究助理 研究方向
邵昶 数论多目标优化算法
段琦琦 大规模高性能分布式优化与学习算法
孙立君 群体智能优化以及感知通信的实现与应用
扬帆 机械电子硬件的设计
张胡梦圆 电子工程
许梦婷 数学
梁轩铨 物理
周雪凝 生物
张孜晟 化学
周朦，吴书琴 计算机科学
马策，李汉青，倪犀
子
GPU仿真技术
About the Team

4. Basic Guiding Ideology
• We do the robot algorithm for the swarm
robots is not to let the workers unemployed.
• But in order to avoid unnecessary
casualties, the dangerous, embarrassing
work left to the swarm robots to do.
• Wool (group algorithm) out of the dog
(business community) who let the pig (large
users) to pay is today's business model.

5. Research Status of
Cooperative Robot
• In 2009, the Swiss Federal Institute of Technology,
Lausanne, made an e-puck system with eight
infrared sensors, a VGA color camera and eight
LEDs for a bit expensive.
• In 2014 the United States the Massachusetts
Institute of Technology did a Kilobot, there is an
infrared sensor, an LED, the cost down a lot, but
can only form a no hole connected pattern.
• 2016 France Aviz University and made a small
apes system Zooids, had a touch sensor, a 2.4G
radio, but only in the plane movement.

6. Our Research - Selaginella
• We are doing Selabot, the main purpose is to solve the land,
sea and air use of a variety of large and small micro-
environment detection or management of practical robot
swarm collaborative model.
Six Cylinder Tumbleweed
Prototype Salsola Tragus

7. The problem to Solve
• Synergy of Motion Trajectory of Multi-sensor UXV
swarm based on Particle Swarm Optimization.
• Unmanned various transport Vehicles (UXV)
sometimes need to work together, this time need a
unified real-time algorithm, otherwise the action
between them will be inconsistent.
• Gaussian distribution and variance are relatively
stable, but lack of dynamic real-time information,
only the high-order complex fractional central
moments calculated by time window contain more
dynamic directionality

8. PSO（Sky）
The geese consume the least amount of energy
to find their food at the fastest speed

9. PSO（Sea）
Sardines are arranged in large whale shapes to scare off sharks

10. PSO（Under）
大雁耗掉最少能量最快速度找到食物
一个质子与铅的原子核质子发生撞击，探测器中产生一个粒子群
The ultra-luminous quantum entanglement allows the glass
glue particles to have a mutually synchronized flight path!

11. The PSO Algorithm

12. Unmanned Aerial Vehicle

13. Unmanned Underwater Vehicle

14. Unmanned Ground Vehicle

15. Unmanned Emergency Vehicle

16. Unmanned Survey Vehicles

17. Extending Gaussian Var

18. Why Fractional Var?
-1
-1
-1
+1
+1
+1
-42 angle-18 angle
When the plane flies alone swing the left side and the right side does not matter,
but when they fly together the coordination is needed!
Euclidean - Newton Space Measure
Riemann Lobachevsky space metric

19. Defining Fractional Norm
• Fractional Norm:

20. Defining Fractional Moment
• Fractional center moment:
Given as a discrete random variable,
exist, define order k center moment as
where （）is the Gamma function

21. Application of UXV Swarm
1. Robot energy recovery High-capacity battery pack for fast charger
2. Fast large-scale machine crowd wireless charging device
3. A method of robot movement using three-axis magnetic force for
electromagnetic rotation
4. The use of three-axis magnetic overlap UAV and communication methods
5. The use of electromagnetic resonance induction of the conjoined machine
fish and synergistic methods
6. Brainstorming variance algorithm in coal mine lifesaving robot escape
positioning usage
7. Unmanned aircraft suspension touch controller system and method
8. The use of electromagnetic induction sterilization robot population and
control methods
9. multi-wisdom elderly care machine robot group
10. The use of light perception of heavy metal detection robot population
and control devices

22. Rolling coal mine rescue
bunkers’coordination

23. Artificial rainfall haze clean unmanned aerial
vehicles’coordination

24. Maritime search and rescue unmanned
fishes

25. Biomedical microagent population
control coordination

26. Conclusion
• We have defined Complex Center
Moment and related trajectory control.
• The method is dedicated to the
coordination of swarm robots.

27. Thank you!
Any question contact us: huangj@mail.sustc.edu.cn