What Types of Interactions do Bio-Inspired Robot Swarms and Flocks Afford a Human?

This paper uses simulations to identify what types of human influence are afforded by the flocking and swarming structures that emerge from Couzin’s bio-inspired model [4]. The goal is to allow a human to influence a decentralized agent collective without resorting to centralized human control. Evidence is provided that, when nominal agents use switching-based control to respond to human-guided predators and leaders, the resulting behavior is responsive to human input but is obtained at the cost of causing the dynamic structure of the collective to follow a single flocking structure. Leaders are more effective in influencing coherent flocks, but predators can be used to divide the flock into sub-flocks, yielding higher performance on some problems. Introducing a so-called “stakeholder” leadership style makes it possible for a human to guide the agents while maintaining several different types of structures; doing so requires more than one human-controlled agent. We then demonstrate that it is possible to produce potentially useful emergent dynamics without centralized human control, and identify an important type of emergent dynamics: automatic switches between structure types.

[1]  Debasish Ghose,et al.  Generalization of Linear Cyclic Pursuit With Application to Rendezvous of Multiple Autonomous Agents , 2006, IEEE Transactions on Automatic Control.

[2]  Zsolt Kira,et al.  Exerting human control over decentralized robot swarms , 2000, 2009 4th International Conference on Autonomous Robots and Agents.

[3]  Andry Tanoto,et al.  Analysis and design of human-robot swarm interaction in firefighting , 2008, RO-MAN 2008 - The 17th IEEE International Symposium on Robot and Human Interactive Communication.

[4]  Prasanna Velagapudi,et al.  Teams organization and performance in multi-human/multi-robot teams , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.

[5]  Michael A. Goodrich,et al.  On using mixed-initiative control: A perspective for managing large-scale robotic teams , 2009, 2009 4th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[6]  S Erol Swarm Robotics: From Sources of Inspiration to Domains of Application , 2005 .

[7]  Eric Forgoston,et al.  Noise, bifurcations, and modeling of interacting particle systems , 2011, IROS 2011.

[8]  I. Couzin,et al.  Collective memory and spatial sorting in animal groups. , 2002, Journal of theoretical biology.

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

[10]  I. Couzin,et al.  Effective leadership and decision-making in animal groups on the move , 2005, Nature.

[11]  Marc Steinberg,et al.  Biologically-inspired approaches for self-organization, adaptation, and collaboration of heterogeneous autonomous systems , 2011, Defense + Commercial Sensing.

[12]  K. Valavanis,et al.  Unmanned ground vehicle swarm formation control using potential fields , 2007, 2007 Mediterranean Conference on Control & Automation.

[13]  L. Alboul,et al.  Mixed human-robot team navigation in the GUARDIANS project , 2008, 2008 IEEE International Workshop on Safety, Security and Rescue Robotics.

[14]  Stephen Whitlow,et al.  A playbook interface for mixed initiative control of multiple unmanned vehicle teams , 2002, Proceedings. The 21st Digital Avionics Systems Conference.

[15]  Brian Scassellati,et al.  The Oz of Wizard: Simulating the human for interaction research , 2009, 2009 4th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[16]  James McLurkin,et al.  Speaking Swarmish: Human-Robot Interface Design for Large Swarms of Autonomous Mobile Robots , 2006, AAAI Spring Symposium: To Boldly Go Where No Human-Robot Team Has Gone Before.

[17]  D. Sumpter The principles of collective animal behaviour , 2006, Philosophical Transactions of the Royal Society B: Biological Sciences.

[18]  Mary L. Cummings,et al.  Automation Architecture for Single Operator, Multiple UAV Command and Control, , 2007 .

[19]  Magnus Egerstedt,et al.  Executive Decision Support: Single-Agent Control of Multiple UAVs , 2009 .