A bio-inspired TDMA scheduling algorithm for underwater robotic swarms

In this paper, the frog-call-inspired anti-phase synchronization algorithm is investigated and applied to allocate communication time slots among robotic swarms. The main goal of the work is to solve interference and jamming problems which becomes vital in swarm robot communication and sensing, especially in underwater application. A novel distributed model of this biologically-inspired approach is investigated to improve scalability and enable decentralization of the algorithm. It is proven from the simulated experiment that the model can be applied for scheduling underwater swarm communication within a limited local communication range, however with an acceptable amount (less than 5%) of packet loss. In the end, a real robot experiment using underwater swarm robot platforms is also presented.

[1]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[2]  Felix Schill,et al.  A Communication Module and TDMA Scheduling for a Swarm of Small Submarines , 2007 .

[3]  B. Ermentrout,et al.  An adaptive model for synchrony in the firefly Pteroptyx malaccae , 1991 .

[4]  A. Tyrrell,et al.  On the accuracy of firefly synchronization with delays , 2008, 2008 First International Symposium on Applied Sciences on Biomedical and Communication Technologies.

[5]  Paul Levi,et al.  Minimalistic approach towards communication and perception in microrobotic swarms , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[6]  Thomas Schmickl,et al.  Profiling Underwater Swarm Robotic Shoaling Performance Using Simulation , 2013, TAROS.

[7]  Serge Kernbach,et al.  CoCoRo -- The Self-Aware Underwater Swarm , 2011, 2011 Fifth IEEE Conference on Self-Adaptive and Self-Organizing Systems Workshops.

[8]  M. Murata,et al.  Frog call-inspired self-organizing anti-phase synchronization for wireless sensor networks , 2009, 2009 2nd International Workshop on Nonlinear Dynamics and Synchronization.

[9]  Christian Blum,et al.  Distributed graph coloring in wireless ad hoc networks: A light-weight algorithm based on Japanese tree frogs' calling behaviour , 2011, 2011 4th Joint IFIP Wireless and Mobile Networking Conference (WMNC 2011).

[10]  Taixiong Zheng,et al.  Multi-robot task allocation and scheduling based on fish swarm algorithm , 2010, 2010 8th World Congress on Intelligent Control and Automation.

[11]  Radhika Nagpal,et al.  Firefly-inspired sensor network synchronicity with realistic radio effects , 2005, SenSys '05.

[12]  Christian Blum,et al.  Distributed graph coloring: an approach based on the calling behavior of Japanese tree frogs , 2010, Swarm Intelligence.

[13]  Paul Levi,et al.  Collective-adaptive Lévy flight for underwater multi-robot exploration , 2013, 2013 IEEE International Conference on Mechatronics and Automation.

[14]  Gunther Auer,et al.  Fireflies as Role Models for Synchronization in Ad Hoc Networks , 2006, 2006 1st Bio-Inspired Models of Network, Information and Computing Systems.

[15]  S H Strogatz,et al.  Coupled oscillators and biological synchronization. , 1993, Scientific American.

[16]  Felix Schill,et al.  Distributed Dynamical Omnicast Routing , 2006, Complex Syst..

[17]  Paul Levi,et al.  Collective AI: context awareness via communication , 2005, IJCAI.

[18]  Kazuyuki Aihara,et al.  Mathematical modeling of frogs’ calling behavior and its possible application to artificial life and robotics , 2008, Artificial Life and Robotics.

[19]  Serge Kernbach,et al.  Multi-Modal Local Sensing and Communication for Collective Underwater Systems , 2011, ArXiv.

[20]  S. Strogatz,et al.  Synchronization of pulse-coupled biological oscillators , 1990 .

[21]  Jochen Trumpf,et al.  Towards Optimal TDMA Scheduling for Robotic Swarm Communication , 2005 .