Robohub.org
 

ShanghAI Lectures: Weidong Chen “Modeling and Control of Mobile Robot Networks”

by
27 December 2013



share this:

Guest talk in the ShanghAI Lectures, 2009-11-26
ChenSwarm intelligence of mobile robots is defined as a mobile robot network with only local interactions and finite sensing capabilities which can achieve global objectives and collective behaviors. The most well-known examples of swarm intelligence in nature are discovered in the collective behaviors of ant and bee colonies. Self-healing is one of the most important components in swarm intelligence.

In this talk, we will provide a theoretical model as well as a control method for self-healing of mobile robot networks based on motion synchronization. Using the graph and complex network theories, we establish the model of a mobile robot network which combines switched network topologies with an interaction dynamic model for describing the motion of the robots. We propose a performance metric of the network topology to evaluate the stability and the robustness of motion synchronization, analyze the effect of failed robots upon the network topology, and show the necessity and principle of the self-healing method based on only local interactions. A fully distributed and recursive topology control for self-healing with switched topologies is then proposed. We show that the self-healing algorithm can prevent the network topology from being separated into two or more disconnected parts, and maintain the performance of the network. Based on the Lyapunov exponent, we further provide a criterion of the stability of the network with the proposed distributed control. Finally, we demonstrate the advantages of our self-healing method by performing simulations of two typical tasks, formation generation and coverage.

The ShanghAI Lectures are a videoconference-based lecture series on Embodied Intelligence run by Rolf Pfeifer and organized by me and partners around the world.

Weidong Chen received the B.S. and M.S. degrees in Control Engineering in 1990 and 1993, and Ph.D. degree in Mechatronics in 1996, respectively, all from the Harbin Institute of Technology, Harbin, China. Since 2005 he has been a professor of the Department of Automation at the Shanghai Jiao Tong University, Shanghai, China, and director of the Institute of Robotics and Intelligent Processing. From 2003 to 2004, he was a visiting associate professor in the Department of Electrical and Computer Engineering at The Ohio State University. Dr. Chen’s research interests include autonomous mobile robot, multi-robot cooperation, and micro manipulation.

The ShanghAI lectures have brought us a treasure trove of guest lectures by experts in robotics. You can find the whole series from 2012 here. Now, we’re bringing you the guest lectures you haven’t yet seen from previous years, starting with the first lectures from 2009 and releasing a new guest lecture every Thursday until all the series are complete. Enjoy!



tags: , , , ,


Nathan Labhart Co-organizing the ShanghAI Lectures since 2009.
Nathan Labhart Co-organizing the ShanghAI Lectures since 2009.





Related posts :



Estimating manipulation intentions to ease teleoperation

Introducing an intention estimation model that relies on both gaze and motion features.
06 December 2022, by and

Countering Luddite politicians with life (and cost) saving machines

Beyond aerial tricks, drones are now being deployed in novel ways to fill the labor gap of menial jobs that have not returned since the pandemic.
04 December 2022, by

Call for robot holiday videos 2022

That’s right! You better not run, you better not hide, you better watch out for brand new robot holiday videos on Robohub!
02 December 2022, by

The Utah Bionic Leg: A motorized prosthetic for lower-limb amputees

Lenzi’s Utah Bionic Leg uses motors, processors, and advanced artificial intelligence that all work together to give amputees more power to walk, stand-up, sit-down, and ascend and descend stairs and ramps.

Touch sensing: An important tool for mobile robot navigation

Proximal sensing often is a blind spot for most long range sensors such as cameras and lidars for which touch sensors could serve as a complementary modality.
29 November 2022, by

Study: Automation drives income inequality

New data suggest most of the growth in the wage gap since 1980 comes from automation displacing less-educated workers.
27 November 2022, by





©2021 - ROBOTS Association


 












©2021 - ROBOTS Association