Segregation of multiple heterogeneous units in a robotic swarm

Several natural systems adopt self-sorting mechanisms based on segregative behaviors. Among these, cell segregation is of particular interest since it plays an important role in the formation of tissues, organs, and living organisms. The Differential Adhesion Hypothesis states that cells naturally segregate because of differences in affinity, which lead similar cells to strongly adhere to each other. By exploring this principle, we propose a controller that can segregate a heterogeneous swarm of robots according to the characteristics of each agent, such that similar robots form homogeneous teams and dissimilar robots are segregated. We apply LaSalle's Invariance Principle to show convergence and perform simulated experiments in order to demonstrate the robustness and effectiveness of the proposed controller. Results show that our approach allows a swarm of multiple heterogeneous robots to segregate in a coherent and smooth fashion, without any inter-agent collisions.

[1]  D. Wilkinson,et al.  Molecular mechanisms of cell segregation and boundary formation in development and tumorigenesis. , 2012, Cold Spring Harbor perspectives in biology.

[2]  Erol Sahin,et al.  Swarm Robotics: From Sources of Inspiration to Domains of Application , 2004, Swarm Robotics.

[3]  Vijay Kumar,et al.  Leader-to-formation stability , 2004, IEEE Transactions on Robotics and Automation.

[4]  Paolo Fiorini,et al.  Motion Planning in Dynamic Environments Using Velocity Obstacles , 1998, Int. J. Robotics Res..

[5]  Francesco Mondada,et al.  Segregation in swarms of mobile robots based on the Brazil nut effect , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[6]  Vijay Kumar,et al.  Segregation of Heterogeneous Units in a Swarm of Robotic Agents , 2010, IEEE Transactions on Automatic Control.

[7]  Reza Olfati-Saber,et al.  Flocking for multi-agent dynamic systems: algorithms and theory , 2006, IEEE Transactions on Automatic Control.

[8]  Vijay Kumar,et al.  Swarm Coordination Based on Smoothed Particle Hydrodynamics Technique , 2013, IEEE Transactions on Robotics.

[9]  Jean-Louis Deneubourg,et al.  The dynamics of collective sorting robot-like ants and ant-like robots , 1991 .

[10]  N. Franks,et al.  Brood sorting by ants: distributing the workload over the work-surface , 1992, Behavioral Ecology and Sociobiology.

[11]  George J. Pappas,et al.  Flocking in Fixed and Switching Networks , 2007, IEEE Transactions on Automatic Control.

[12]  Luiz Chaimowicz,et al.  Hierarchical congestion control for robotic swarms , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[13]  Malcolm S. Steinberg,et al.  Reconstruction of Tissues by Dissociated Cells , 1963 .

[14]  Craig W. Reynolds.  Flocks, herds, and schools: a distributed behavioral model , 1998 .

[15]  Calin Belta,et al.  Abstraction and control for Groups of robots , 2004, IEEE Transactions on Robotics.

[16]  T. Magnuson,et al.  Genomic imprinting and epigenetic control of development. , 2012, Cold Spring Harbor perspectives in biology.

[17]  Tucker R. Balch,et al.  Behavior-based formation control for multirobot teams , 1998, IEEE Trans. Robotics Autom..

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

[19]  Roderich Groß,et al.  Segregation in swarms of e-puck robots based on the Brazil nut effect , 2012, AAMAS.

[20]  Mario Fernando Montenegro Campos,et al.  On Segregative Behaviors Using Flocking and Velocity Obstacles , 2012, DARS.

[21]  Naomi Ehrich Leonard,et al.  Virtual leaders, artificial potentials and coordinated control of groups , 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

[22]  O. Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1985, Proceedings. 1985 IEEE International Conference on Robotics and Automation.