Localization in Densely Packed Swarms Using Interrobot Collisions as a Sensing Modality

As the size of robots decreases in multirobot systems, collisions cease to be catastrophic events that need to be avoided at all costs. This implies that less conservative, coordinated control strategies can be employed, where collisions are not only tolerated, but can potentially be harnessed as an information source. In this paper, we follow this line of inquiry by employing collisions as a sensing modality that provides information about the robots’ surroundings. We envision a collection of robots moving around with no sensors other than binary, tactile sensors that can determine if a collision occurred, and let the robots use this information to determine their locations. We apply a probabilistic localization technique based on mean-field approximations that allows each robot to maintain and update a probability distribution over all possible locations. Simulations and real multirobot experiments illustrate the feasibility of the proposed approach.

[1]  Sonia Martínez,et al.  Coverage control for mobile sensing networks , 2002, IEEE Transactions on Robotics and Automation.

[2]  F R Adler,et al.  Information Collection and Spread by Networks of Patrolling Ants , 1992, The American Naturalist.

[3]  Vicsek,et al.  Novel type of phase transition in a system of self-driven particles. , 1995, Physical review letters.

[4]  Magnus Egerstedt,et al.  Sleep scheduling of wireless sensor networks using hard-core point processes , 2013, 2013 American Control Conference.

[5]  Tuong Phuoc-Tho,et al.  A study of pipe-cleaning and inspection robot , 2011, 2011 IEEE International Conference on Robotics and Biomimetics.

[6]  T. W. Anderson,et al.  Statistical Inference about Markov Chains , 1957 .

[7]  M. R. Leadbetter.  Poisson Processes , 2011, International Encyclopedia of Statistical Science.

[8]  Dylan A. Shell,et al.  Space-Efficient Filters for Mobile Robot Localization from Discrete Limit Cycles , 2018, IEEE Robotics and Automation Letters.

[9]  J. Besag,et al.  Statistical Analysis of Spatial Point Patterns by Means of Distance Methods , 1976 .

[10]  Ronald C. Arkin,et al.  An Behavior-based Robotics , 1998 .

[11]  D. Gordon,et al.  What is the function of encounter patterns in ant colonies? , 1993, Animal Behaviour.

[12]  P. Abbeel,et al.  LQG-MP: Optimized path planning for robots with motion uncertainty and imperfect state information , 2011 .

[13]  J. C. Munger,et al.  LONG-TERM YIELD FROM HARVESTER ANT COLONIES: IMPLICATIONS FOR HORNED LIZARD FORAGING STRATEGY' , 1984 .

[14]  Serge Kernbach,et al.  Get in touch: cooperative decision making based on robot-to-robot collisions , 2009, Autonomous Agents and Multi-Agent Systems.

[15]  D. Stoyan,et al.  Stochastic Geometry and Its Applications , 1989 .

[16]  Yinan Zhang,et al.  Ganging up: team-based aggression expands the population/performance envelope in a multi-robot system , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[17]  J. Ludwig,et al.  Statistical ecology: a primer on methods & computing , 1988 .

[18]  Ronald C. Arkin,et al.  Cooperative multiagent robotic systems , 1998 .

[19]  John Cocke,et al.  Optimal decoding of linear codes for minimizing symbol error rate (Corresp.) , 1974, IEEE Trans. Inf. Theory.

[20]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[21]  Spring Berman,et al.  Optimized Stochastic Policies for Task Allocation in Swarms of Robots , 2009, IEEE Transactions on Robotics.

[22]  Serge Kernbach,et al.  Re-embodiment of Honeybee Aggregation Behavior in an Artificial Micro-Robotic System , 2009, Adapt. Behav..

[23]  Ian Holmes,et al.  Dynamic Programming Alignment Accuracy , 1998, J. Comput. Biol..

[24]  W. Marsden.  I and J , 2012 .

[25]  Gordon M. Barrow,et al.  Physical chemistry for the life sciences , 1974 .

[26]  Francesco Zanichelli.  Topological Maps and Robust Localization for Autonomous Navigation , 1999, IJCAI 1999.

[27]  Li Wang,et al.  Control Barrier Certificates for Safe Swarm Behavior , 2015, ADHS.

[28]  Ron Alterovitz,et al.  Estimating probability of collision for safe motion planning under Gaussian motion and sensing uncertainty , 2012, 2012 IEEE International Conference on Robotics and Automation.

[29]  Spring Berman,et al.  Design of ant-inspired stochastic control policies for collective transport by robotic swarms , 2014, Swarm Intelligence.

[30]  Maja J. Mataric,et al.  On foraging strategies for large-scale multi-robot systems , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[31]  Jesper Moller,et al.  Modelling Aggregation on the Large Scale and Regularity on the Small Scale in Spatial Point Pattern Datasets , 2015, 1505.07215.

[32]  Gaurav S. Sukhatme,et al.  Go ahead, make my day: Robot conflict resolution by aggressive competition , 2000 .

[33]  S. Shankar Sastry,et al.  Conflict resolution for air traffic management: a study in multiagent hybrid systems , 1998, IEEE Trans. Autom. Control..

[34]  Spring Berman,et al.  Mean-field controllability and decentralized stabilization of Markov chains , 2017, 2017 IEEE 56th Annual Conference on Decision and Control (CDC).

[35]  Adrian Baddeley,et al.  Spatial Point Processes and their Applications , 2007 .

[36]  Siddharth Mayya,et al.  Collisions as Information Sources in Densely Packed Multi-Robot Systems Under Mean-Field Approximations , 2017, Robotics: Science and Systems.

[37]  Li Wang,et al.  Safe, Remote-Access Swarm Robotics Research on the Robotarium , 2016, ArXiv.

[38]  Daryl J. Daley,et al.  An Introduction to the Theory of Point Processes , 2013 .

[39]  E. S. Pearson,et al.  THE USE OF CONFIDENCE OR FIDUCIAL LIMITS ILLUSTRATED IN THE CASE OF THE BINOMIAL , 1934 .

[40]  Pattie Maes,et al.  A Study of Territoriality: The Role of Critical Mass in Adaptive Task Division , 1996 .

[41]  Eric Feron,et al.  A Framework for Collision-Tolerant Optimal Trajectory Planning of Autonomous Vehicles , 2016, ArXiv.

[42]  Magnus Egerstedt,et al.  Graph Theoretic Methods in Multiagent Networks , 2010, Princeton Series in Applied Mathematics.

[43]  D. Goldman,et al.  Glass-like dynamics in confined and congested ant traffic. , 2015, Soft matter.

[44]  Richard T. Vaughan,et al.  Adaptive multi-robot bucket brigade foraging , 2008, ALIFE.

[45]  Ken Sugawara,et al.  Cooperative acceleration of task performance: foraging behavior of interacting multi-robots system , 1997 .

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

[47]  Jean-Yves Le Boudec,et al.  A Generic Mean Field Convergence Result for Systems of Interacting Objects , 2007, Fourth International Conference on the Quantitative Evaluation of Systems (QEST 2007).

[48]  Joel W. Burdick,et al.  Probabilistic Collision Checking With Chance Constraints , 2011, IEEE Transactions on Robotics.

[49]  E. Feron,et al.  Real-time motion planning for agile autonomous vehicles , 2000, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[50]  S. Chapman,et al.  An introduction to the kinetic theory of gases , 1941 .

[51]  Jason M. O'Kane,et al.  Localization With Limited Sensing , 2007, IEEE Transactions on Robotics.

[52]  Robin J. Evans,et al.  Nearest Neighbor Distance Distribution in Hard-Core Point Processes , 2016, IEEE Communications Letters.

[53]  Maja J. Mataric,et al.  Interference as a Tool for Designing and Evaluating Multi-Robot Controllers , 1997, AAAI/IAAI.

[54]  Dinesh Manocha,et al.  Reciprocal collision avoidance with acceleration-velocity obstacles , 2011, 2011 IEEE International Conference on Robotics and Automation.

[55]  Werner Nachtigall,et al.  Bionics by Examples: 250 Scenarios from Classical to Modern Times , 2014 .

[56]  W. T. Grandy,et al.  Kinetic theory : classical, quantum, and relativistic descriptions , 2003 .

[57]  Demetri Terzopoulos,et al.  Autonomous pedestrians , 2005, SCA '05.

[58]  Reid G. Simmons,et al.  Probabilistic Robot Navigation in Partially Observable Environments , 1995, IJCAI.

[59]  J. Wakefield,et al.  Spatial epidemiology: methods and applications. , 2000 .

[60]  Deborah M. Gordon,et al.  Group-Level Exploration Tactics in Fire Ants , 1988 .

[61]  Dominique Gruyer,et al.  A fast Monte Carlo algorithm for collision probability estimation , 2008, 2008 10th International Conference on Control, Automation, Robotics and Vision.

[62]  Vijay Kumar,et al.  Design of small, safe and robust quadrotor swarms , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).