MAE 598: Multi-Robot Systems  Fall 2016

Syllabus/Course Schedule with Reading and Team Presentation Assignments 

Final Project Proposal Guidelines and Template

Presentation guidelines:  Each 2-student team will be assigned a paper to present to the class. The team will give a 16-minute presentation, during which each student will present for 8 minutes.  The presentation can be in the form of slides, a discussion using the whiteboard, or a combination of both. The presentation should include: (1) a summary of the paper and its results, (2) possible applications of the research, (3) strengths and weaknesses/limitations of the paper, and (4) clarification of challenging material. Students may include videos and any other interesting supporting information in support of their presentation. The presenters will answer questions from the class afterward.


[R1]   “Multiple Mobile Robot Systems”, Lynne E. Parker, Chapter 40 in Springer Handbook of Robotics, Bruno Siciliano and Oussama Khatib (eds.), 2008. 

[R2]   “Networked Robots”, Vijay Kumar, Daniela Rus and Gaurav S. Sukhatme, Chapter 41 in Springer Handbook of Robotics, Bruno Siciliano and Oussama Khatib (eds.), 2008.

[R3]  “From swarm intelligence to swarm robotics,” Gerardo Beni. In Erol Sahin and William M. Spears, editors, Swarm Robotics – SAB 2004 International Workshop, volume 3342 of Lecture Notes in Computer Science, pages 1–9, July 2005. Springer-Verlag.

[R4]  “Swarm robotics: From sources of inspiration to domains of application,” Erol Sahin.  In Erol Sahin and William M. Spears, editors, Swarm Robotics – SAB 2004 International Workshop, volume 3342 of Lecture Notes in Computer Science, pages 10–20, 2005. Springer-Verlag.

[R5]   “Architecture, Abstractions, and Algorithms for Controlling Large Teams of Robots: Experimental Testbed and Results,” Nathan Michael, Jonathan Fink, Savvas Loizou, and Vijay Kumar.  In M. Kaneko and Y. Nakamura, editors, Robotics Research, STAR 66, pages 409-419, 2010. Springer-Verlag.

[R6]   “Coordinated Control of an Underwater Glider Fleet in an Adaptive Ocean Sampling Field Experiment in Monterey Bay,” Naomi E. Leonard, Derek A. Paley, Russ E. Davis, David M. Fratantoni, Francois Lekien and Fumin Zhang, Journal of Field Robotics, 27(6), p. 718-740, 2010.

[R7]  “Safe, Remote-Access Swarm Robotics Research on the Robotarium,” Pickem, D.; Wang, L.; Glotfelter, P.; Diaz-Mercado, Y.; Mote, M.; Ames, A.; Feron, E. & Egerstedt, M.  arXiv preprint arXiv:1604.00640, 2016

[R8]  “A General Method for Numerically Simulating the Stochastic Time Evolution of Coupled Chemical Reactions,” Daniel T. Gillespie, Journal of Computational Physics 22:403-434, 1976

[R9]  “Stochastic Simulation of Chemical Kinetics,” Daniel T. Gillespie, Annual Review of Physical Chemistry, 58: 35-55, 2007

[R10]  “Stochastic modelling of gene regulatory networks,” Hana El Samad, Mustafa KhammashLinda Petzold, and Dan Gillespie. Int. J. Robust Nonlinear Control 2005; 15:691–711

[R11]  “A review of probabilistic macroscopic models for swarm robotic systems,” K. Lerman, A. Martinoli, and A. Galstyan.  International Workshop on Swarm Robotics, 2004, pp. 143-152.

[R12]  “The statistical dynamics of programmed robotic self-assembly,” S. Burden, N. Napp, and E. Klavins. International Conference on Robotics and Automation (ICRA), Orlando, FL, USA, pp 1469–76, 2006.

[R13]  “Parameter Estimation and Optimal Control of Swarm-Robotic Systems,” Nikolaus Correll. International Conference on Robotics and Automation (ICRA), 2008.

[R14]  “Probabilistic Modeling of Swarming Systems,” Nikolaus Correll and Heiko Hamann, Springer Handbook of Computational Intelligence, pp. 1423-1432, 2015. 

[R15]  “Deciding on a new home: How do honeybees agree?,” N. F. Britton, N. R. Franks, S. C. Pratt, and T. D. Seeley, Proc. R. Soc. Lond. B (2002) 269:1383–1388.

[R16]  “Steady-states of receptor-ligand dynamics: a theoretical framework,” Madalena Chaves, Eduardo D Sontag, and Robert J Dinerstein. J. Theoretical Biology, 227(3):413–28, 2004.

[R17]  “Ant groups optimally amplify the effect of transiently informed individuals,” Aviram Gelblum et al., Nature Communications 6, 2015.    Supplementary Material

[R18]  “Information Consensus in Multivehicle Cooperative Control,” Wei Ren, Randal W. Beard, and Ella M. Atkins, IEEE Control Systems Magazine, April 2007.

[R19]  “Consensus and Cooperation in Networked Multi-Agent Systems,” Reza Olfati-Saber, J. Alex Fax, and Richard M. Murray, Proceedings of the IEEE, Vol. 95, No. 1, Jan. 2007.

[R20]  “Information Consensus in Distributed Multiple Vehicle Coordinated Control,” Randal W. Beard and Vahram Stepanyan, IEEE Conf. on Decision and Control (CDC), Dec. 2003.

[R21]  “Novel Type of Phase Transition in a System of Self-Driven Particles,” T. Vicsek et al., Physical Review Letters, vol. 75, no. 6, Aug 1995.

[R22]  “Stable Flocking of Mobile Agents, Part I: Fixed Topology,” Herbert G. Tanner, Ali Jadbabaie, and George J. Pappas, IEEE Conference on Decision and Control (CDC), Dec. 2003.

[R23]   “Virtual Leaders, Artificial Potentials and Coordinated Control of Groups,” Naomi Ehrich Leonard and Edward Fiorelli, IEEE Conference on Decision and Control (CDC), 2001.

[R24]   “Motion Coordination with Distributed Information,” Sonia Martinez, Jorge Cortes, and Francesco Bullo, IEEE Control Systems Magazine, August 2007.

[R25]  “Controlling a Team of Ground Robots via an Aerial Robot,” Nathan Michael, Jonathan Fink, and Vijay Kumar, IEEE International Conference on Intelligent Robots and Systems (IROS), San Diego, CA, 2007.

[R26]  “Distributed Coverage Control with Sensory Feedback for Networked Robots,” Mac Schwager, James McLurkin, and Daniela Rus, Robotics: Science and Systems (RSS) II, pp. 49-56, 2006.

[R27]  “Communication-Aware Coverage Control for Robotic Sensor Networks,” Yiannis Kantaros and Michael M. Zavlanos, IEEE Conference on Decision and Control (CDC), 2014.

[R28]  “Connectivity Management in Mobile Robot Teams,” Ethan Stump, Ali Jadbabaie, Vijay Kumar, IEEE International Conference on Robotics and Automation (ICRA), 2008.

[R29]  “Constrained Coverage for Mobile Sensor Networks,” Sameera Poduri and Gaurav Sukhatme, IEEE International Conference on Robotics and Automation (ICRA), 2004.

[R30]  “Mobile Sensor Network Deployment using Potential Fields: A Distributed, Scalable Solution to the Area Coverage Problem,”  Andrew Howard, Maja J Mataric, and Gaurav S Sukhatme, International Symposium on Distributed Autonomous Robotics Systems (DARS), 2002.

[R31]  “Controlling Swarms of Robots Using Interpolated Implicit Functions,” Luiz Chaimowicz, Nathan Michael and Vijay Kumar, IEEE International Conference on Robotics and Automation (ICRA), 2005.

[R32]  “Graph-Theoretic Connectivity Control of Mobile Robot Networks,” Michael Zavlanos, Magnus Egerstedt, and George Pappas, Proceedings of the IEEE2011.

[R33]  “Controlling Wild Mobile Robots Using Virtual Gates and Discrete Transitions,” Leonardo Bobadilla, Fredy Martinez, and Eric Gobst, American Control Conference (ACC), 2012.

[R34]  “Topological Mapping of Unknown Environments using an Unlocalized Robotic Swarm,” Alireza Dirafzoon and Edgar Lobaton, Intelligent Robots and Systems (IROS), 2013.

[R35]  “Cooperative Grasping and Transport using Multiple Quadrotors,” Daniel Mellinger, Michael Shomin, Nathan Michael, and Vijay Kumar, Distributed Autonomous Robotic Systems (DARS), 2010.

[R36]  “Multi-Robot Manipulation with no Communication Using Only Local Measurements,” Zijian Wang and Mac Schwager, Conference on Decision and Control (CDC), 2015.

[R37]  “Constraint-Aware Coordinated Construction of Generic Structures,” David T. Stein, Ryan Schoen, and Daniela Rus, Int’l. Conf. on Intelligent Robots and Systems (IROS), 2011.

[R38]  “Bio-inspired construction with mobile robots and compliant pockets,” Touraj Soleymani, Vito Trianni, Michael Bonani, Francesco Mondada, and Marco Dorigo, Robotics and Autonomous Systems, 74 (2015) 340–350.

[R39]  “Real-Time Automated Modeling and Control of Self-Assembling Systems,” Gregory Mermoud, Massimo Mastrangeli, Utkarsh Upadhyay and Alcherio Martinoli, Int’l. Conf. on Robotics and Automation (ICRA), 2012.

[R40]  “Feedback Control of Many Magnetized Tetrahymena pyriformis Cells by Exploiting Phase Inhomogeneity,” Aaron Becker, Yan Ou, Paul Kim, Min Jun Kim, and Agung Julius, Int’l. Conf. on Intelligent Robots and Systems (IROS), 2013.

Supplementary Material

[S1]  “Deterministic modelling and stochastic simulation of biochemical pathways using MATLAB,” M. Ullah, H. Schmidt, K.-H. Cho, and O. Wolkenhauer, IEE Proc.-Syst. Biol., Vol. 153, No. 2, March 2006 

[S2]  “Modeling and simulating chemical reactions,” D.J. Higham, SIAM Review, 50 (2), pp. 347-368, 2008, ISSN 0036-1445.

[S3]  “Coordination of groups of mobile autonomous agents using nearest neighbor rules,” Ali Jadbabaie, Jie Lin, and A. Stephen Morse, IEEE Trans. on Automatic Control, vol. 48, no, 6, June 2003.

[S4]  “Exact Robot Navigation using Artificial Potential Functions,” Elon Rimon and Daniel E. Koditschek, IEEE Trans. on Robotics and Automation, 8(5): 501-518, Oct. 1992.

[S5]  Elementary Applied Topology, by Robert Ghrist, ed. 1.0, Createspace, 2014.

[S6]  “Collective Manipulation and Construction,” Lynne Parker, Springer Handbook of Computational Intelligence, pp. 1395-1406, 2015.

[S7] Decentralized Sliding Mode Control for Autonomous Collective Transport by Multi-Robot Systems,” Hamed Farivarnejad, Sean Wilson, and Spring Berman, IEEE Conference on Decision and Control (CDC), Las Vegas, NV, 2016. 

[S8]  “Self-Assembly at the Macroscopic Scale,” Roderich Gross and Marco Dorigo, Proceedings of the IEEE, 2008.

[S9]  “Biomedical Applications of Untethered Mobile Milli/Microrobots,” Metin Sitti, Hakan Ceylan, Wenqi Hu, Joshua Giltinan, Mehmet Turan, Sehyuk Yim, and Eric Diller, Proceedings of the IEEE, 2015.

[S10] “Robotics: Ethics of Artificial Intelligence,” Stuart Russell, Sabine Hauert, Russ Altman, and Manuela Veloso, Nature, 521:415-418, 2015.

Lecture Notes and Slides

Lecture 1 Slides: Introduction to multi-robot systems

Lecture 2 Slides: Multi-robot representations and control architectures

Lecture 3 Notes: Stochastic models and controllers for individual robots

Lecture 4 Notes: Master equation and mean-field (ODE) abstractions of population dynamics 

Lecture 5 Slides: Formulations of ODE abstractions of population dynamics

Lecture 6 Notes: Analysis of linear ODE abstractions of population dynamics      

Lecture 6 Slides: Analysis of multi-affine ODE abstractions of population dynamics

Lecture 7 Slides: Control and optimization of ODE abstractions

Supplementary Notes: Examples of Chemical Reaction Network (CRN) Modeling and Analysis

Lecture 8 Slides: Collective Transport in Ants

Lecture 9 Slides: Prof. Ted Pavlic, “An Ecological Approach to Unifying Biology and Robotics”

Lecture 10 Slides: PDE Macroscopic Models of Swarm Population Dynamics

Lecture 10-12 Notes: Consensus Problems in Multi-Robot Systems

Lecture 11 Slides: Consensus Problems – Flocking and Formation Control

Lecture 12 Notes: Stability Analysis using Lyapunov Functions

Lecture 13-14 Notes: Applying Lyapunov Theory to Analyzing Consensus Problems

Lecture 16-18 Notes: Multi-Robot Motion Coordination using Geometric Representations 

Lecture 19-21 Notes: Convex Optimization Problems

Lecture 22 Notes: Concepts from Topology – Navigation Functions

Lecture 22-23 Slides: Implicit Motion Planning using Potential Fields

Lecture 23 Notes: Hybrid Systems

Lecture 24 Notes: Concepts from Topology – Topological Data Analysis

Lecture 25-27 Notes: A Decentralized Approach to Multi-Robot Collective Transport

Lecture 25-26 Slides: Cooperative Manipulation

Lecture 27-28 Notes: Collective Construction using Voronoi Partitions

Lecture 28 Slides: Collective Construction