Adaptive Control Parameters for Dispersal of Multi-Agent Mobile Ad Hoc Network (MANET) Swarms

A mobile ad hoc network is a collection of independent nodes that communicate wirelessly with one another. This paper investigates nodes that are swarm robots with communications and sensing capabilities. Each robot in the swarm may operate in a distributed and decentralized manner to achieve some goal. This paper presents a novel approach to dynamically adapting control parameters to achieve mesh configuration stability. The presented approach to robot interaction is based on spring force laws (attraction and repulsion laws) to create near-optimal mesh like configurations. In prior work, we presented the extended virtual spring mesh (EVSM) algorithm for the dispersion of robot swarms. This paper extends the EVSM framework by providing the first known study on the effects of adaptive versus static control parameters on robot swarm stability. The EVSM algorithm provides the following novelties: 1) improved performance with adaptive control parameters and 2) accelerated convergence with high formation effectiveness. Simulation results show that 120 robots reach convergence using adaptive control parameters more than twice as fast as with static control parameters in a multiple obstacle environment.

[1]  Chunming Qiao,et al.  Coordinated Locomotion and Monitoring Using Autonomous Mobile Sensor Nodes , 2011, IEEE Transactions on Parallel and Distributed Systems.

[2]  John K. Bennett,et al.  Virtual Spring Mesh Algorithms for Control of Distributed Robotic Macrosensors ; CU-CS-996-05 , 2005 .

[3]  Oussama Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1985, Autonomous Robot Vehicles.

[4]  Sergiu-Dan Stan,et al.  A Novel Robust Decentralized Adaptive Fuzzy Control for Swarm Formation of Multiagent Systems , 2012, IEEE Transactions on Industrial Electronics.

[5]  Weiping Li,et al.  Applied Nonlinear Control , 1991 .

[6]  Hongyan Wang,et al.  Social potential fields: A distributed behavioral control for autonomous robots , 1995, Robotics Auton. Syst..

[7]  Frank L. Lewis,et al.  Neural Network Control Of Robot Manipulators And Non-Linear Systems , 1998 .

[8]  Kristian Hengster-Movric,et al.  Bell-shaped potential functions for multi-agent formation control in cluttered environment , 2010, 18th Mediterranean Conference on Control and Automation, MED'10.

[9]  Youfu Li,et al.  Enhanced Particles With Pseudolikelihoods for Three-Dimensional Tracking , 2009, IEEE Transactions on Industrial Electronics.

[10]  Douglas W. Gage,et al.  Command Control for Many-Robot Systems , 1992 .

[11]  T. Murphey,et al.  Switching Rules for Decentralized Control with Simple Control Laws , 2007, 2007 American Control Conference.

[12]  Nak Young Chong,et al.  Low-Cost Dual Rotating Infrared Sensor for Mobile Robot Swarm Applications , 2011, IEEE Transactions on Industrial Informatics.

[13]  Magnus Egerstedt,et al.  Autonomous Formation Switching for Multiple, Mobile Robots , 2003, ADHS.

[14]  William M. Spears,et al.  Distributed, Physics-Based Control of Swarms of Vehicles , 2004 .

[15]  Brian Shucker,et al.  Scalable Control of Distributed Robotic Macrosensors , 2004, DARS.

[16]  Dianguo Xu,et al.  The Application of Particle Swarm Optimization to Passive and Hybrid Active Power Filter Design , 2009, IEEE Transactions on Industrial Electronics.

[17]  A. Edelman,et al.  Mesh generation for implicit geometries , 2005 .

[18]  David Taniar,et al.  Voronoi-Based Continuous $k$ Nearest Neighbor Search in Mobile Navigation , 2011, IEEE Transactions on Industrial Electronics.

[19]  Tucker R. Balch,et al.  Social potentials for scalable multi-robot formations , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[20]  G. R. Noakes University Physics , 1942, Nature.

[21]  Enamul Hoque,et al.  Bundle: A Group-Based Programming Abstraction for Cyber-Physical Systems , 2010, IEEE Transactions on Industrial Informatics.

[22]  Milos Manic,et al.  Extended Virtual Spring Mesh (EVSM): The Distributed Self-Organizing Mobile Ad Hoc Network for Area Exploration , 2011, IEEE Transactions on Industrial Electronics.

[23]  Yuanyuan Yang,et al.  Adaptive Triangular Deployment Algorithm for Unattended Mobile Sensor Networks , 2005, IEEE Transactions on Computers.

[24]  Michael Kass,et al.  An introduction to continuum dynamics for computer graphics , 1995 .

[25]  James McLurkin,et al.  Distributed Algorithms for Dispersion in Indoor Environments Using a Swarm of Autonomous Mobile Robots , 2004, DARS.

[26]  Steven J. Owen Nonsimplicial unstructured mesh generation , 1999 .

[27]  J. K. Bennett,et al.  An approach to switching control beyond nearest neighbor rules , 2006, 2006 American Control Conference.

[28]  B. Shucker,et al.  Target tracking with distributed robotic macrosensors , 2005, MILCOM 2005 - 2005 IEEE Military Communications Conference.

[29]  Xin-She Yang,et al.  Introduction to Algorithms , 2021, Nature-Inspired Optimization Algorithms.

[30]  Mac Schwager,et al.  Decentralized, Adaptive Control for Coverage with Networked Robots , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[31]  Ronald C. Arkin,et al.  Motor Schema — Based Mobile Robot Navigation , 1989, Int. J. Robotics Res..

[32]  Todd D. Murphey,et al.  Convergence-Preserving Switching for Topology-Dependent Decentralized Systems , 2008, IEEE Transactions on Robotics.

[33]  Mohammad Bagher Menhaj,et al.  Coverage control for mobile sensing robots in unknown environments using neural network , 2010, 2010 IEEE International Symposium on Intelligent Control.

[34]  Maja J. Matarić,et al.  Cover Me! A Self-Deployment Algorithm for Mobile Sensor Networks , 2001 .

[35]  James McLurkin,et al.  Analysis and implementation of distributed algorithms for multi-robot systems , 2008 .

[36]  Ching-Chih Tsai,et al.  Parallel Elite Genetic Algorithm and Its Application to Global Path Planning for Autonomous Robot Navigation , 2011, IEEE Transactions on Industrial Electronics.