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Autonomous Multi-Robot Systems Spring 2012



Hierarchical robot control; Behavior-based robot control; Sensors and perception; Navigation and path planning; Localization; Reinforcement learning; Communication; Diversity.

Students should have strong programming skills.

Main Components of Course

First third, Basics:

  • Basics of behavior-based control for robots
  • Basics of multi-robot systems
  • Project: Simple multi-robot system, ASCII soccer (C programming language)

Second third, Research:

  • Survey of important literature
  • Each student chooses a group of papers on a multi-agent or multi-robot topic
  • Each student leads a 30 minute discussion of their topic

Last third, Build Multi-Robot Systems:

  • Several projects using BioSim, Java based multi agent simulation system (Java)
  • Key component is experimental evaluation of the performance of these systems.

Grading Components & Expectations

  • Basic projects: 30%
  • Presentation: 30% (re-do allowed)
  • Multi-robot projects: 30%
  • Quizzes: 10% (easy questions about the content of presentations)

If you take the course P/F you only need to do the presentation and quiz component.


Some papers and pointers:

Software we'll be using:


Strong programming skills. We will be using Unix, C, Java.

Midterm Preparation

  • Know
    • Graph-based decomposition for planning.
    • What guarantees do they each provide?
      • Completeness ?
      • Optimal path ?
      • Minimal computation
      • What is an admissible heuristic?
    • Grid-based planning (relationship to graph-based planning)


Tuesday January 10 Class overview

Thursday January 12 Sense Think Act cycle

multirobot lecture 1
First project discussed (ASCII Soccer)

Tuesday January 17 Class overview (repeat for France)

More on ascii soccer

Thursday January 19 ascii soccer workshop
Tuesday January 24 Topic
Thursday January 26 Topic
Tuesday January 31 Topic
Thursday February 2 Topic
Tuesday February 7 Topic
Thursday February 9 Topic
Tuesday February 14 Topic
Thursday February 16 Topic
Tuesday February 21 Topic
Thursday February 23 Topic
Tuesday February 28 Ant Navigation via pheromones.

Social Potentials

Thursday March 1 Topic
Tuesday March 6 Communication in multi-robot teams.
Thursday March 8 Motter (emergent behavior in swarms): presentation

The self-organizing exploratory pattern of the argentine ant J. -L. Deneubourg, S. Aron, S. Goss and J. M. Pasteels; Study of group food retrieval by ants as a model for multi-robot collective transport strategies. S. Berman, Q. Lindsey, M. Sakar, V. Kumar and S. Pratt
Dutton (collaborative manipulation):presentation
Cooperative multi-robot box-pushing - Mataric, M.J.; Nilsson, M.; Simsarin, K.T.; Cooperative localization and control for multi-robot manipulation - Spletzer, J.; Das, A.K.; Fierro, R.; Taylor, C.J.; Kumar, V.; Ostrowski, J.P.;

Tuesday March 13 Aziz (multi-agent learning):presentation

On Optimizing Interdependent Skills: A Case Study in Simulated 3D Humanoid Robot Soccer Daniel Urieli, Patrick MacAlpine, Shivaram Kalyanakrishnan, Yinon Bentor, Peter Stone; Cooperative Multi-Agent Learning: The State of the Art. Liviu Panait and Sean Luke
Novitzky (task assignment):presentation
Conditional Random Fields for Behavior Recognition of Autonomous Underwater Vehicles Michael Novitzky, Charles Pippin, Thomas R. Collins, Tucker R. Balch, and Michael E. West. Behaviour Recognition for Spatially Unconstrained Unmanned Vehicles, Rolf Baxter, David Lane, Yvan Petillot.

Thursday March 15

Molina (formation control):presentation
self_assembly using biologically_inspired multi agent control Programmable Self-Assembly Using Biologically-Inspired Multiagent Control. R. Nagpal; Boids, Craig Reynolds.
BioSim Tutorial by Bao:

Tuesday March 20 Spring Break
Thursday March 22 Spring Break
Tuesday March 27

Apte (swarm design):
Behavior-Based Coordination in Multi-Robot Systems. Chris Jones and Maja Mataric
Swarm-bot: A new distributed robotic concept. Mondada F., Pettinaro G., Guigrard A., Kwee I., Floreano D., Denebourg J-L, Nolfi S., Gambardella L.M. & Dorigo M. (2004)

Thursday March 29 Ponnau (collaborative exploration) France

Value-based action selection for exploration and dynamic target observation with robot teams Stroupe, A.W.; Ravichandran, R.; Balch, T.; Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
Lenel (collaborative exploration) France
Who Goes There? Selecting a Robot to Reach a Goal Using Social Regret - Meytal Traub, Gal A. Kaminka, Noa Agmon
Multi-Robot Exploration Controlled By A Market Economy R.M. Zlot, A. Stentz, M.B. Dias, and S. Thayer IEEE International Conference on Robotics and Automation, May, 2002
Fabregue (patrolling) France
(one paper only) Multi-Robot Perimeter Patrol in Adversarial Settings Noa Agmon, Sarit Kraus and Gal A. Kaminka
El Amarani (task assignment) France
(one paper only) A Distributed Multi-Robot Cooperation Framework for Real Time Task Achievement Sanem Sariel1⋆ and Tucker Balch

TuesdayApril 3 Topic: Quiz (Balch Travel)
Thursday April 5 Bao presentation regarding Clay: Clay

Hai présentation regarding software for project: [2]

Tuesday April 10

Wang (task assignment)
(one paper only) Simple Auctions with Performance Guarantees for Multi-Robot Task Allocation, Michail G. Lagoudakis Marc Berhault, Sven Koenig, Pinar Keskinocak, Anton J. Kleywegt
Mooney (multi-robot path planning)
Real-Time Randomized Path Planning for Robot Navigation, James Bruce, Manuela Veloso
Walker (efficient guaranteed search for multi-agent teams)
Efficient, Guaranteed Search with Multi-agent Teams Geoffrey Hollinger and Sanjiv Singh
Somani (multi-agent learning):
Multiagent learning using a variable learning rate, Michael Bowling, , Manuela Veloso

Thursday April 12

Sephus (emergent behavior in biological swarms)
Schooling Fishes: The school, a truly egalitarian form of organization in which all members of the group are alike in influence, offers substantial benefits to its … E Shaw - American Scientist, 1978 - JSTOR
Garcia (social insect cooperative behavior)
The Blind Leading the Blind: Modeling Chemically Mediated Army Ant Raid Patterns J. L. Deneubourg, 1'3 S. Goss, 1 N. Franks, 2 and J. M. Pasteels

Tuesday April 17

Ong (multi-robot SLAM) (prefers April)
Multi-robot simultaneous localization and mapping using particle filters A Howard - The International Journal of Robotics Research, 2006
Coisne (emergent behavior in biological swarms) France
Experimental analysis of the social value of flocking by starlings (Sturnus vulgaris) in relation to predation and foraging GVN Powell - Animal Behaviour, 1974

Thursday April 19

Quitmeyer (social insects collective decision making)
(paper of choice)
(plus) Eusociality: Origin and consequences Edward O. Wilson*† and Bert Hölldobler
Gavai (swarm design)
A Physical Implementation of the Self-reconfiguring Crystalline Robot, Daniela Rus
OK (multi-robot SLAM) Towards Multi-Vehicle Simultaneous Localisation and Mapping Stefan B. Williams1, Gamini Dissanayake2, Hugh Durrant-Whyte

Tuesday April 24

Sung Lee (formation control):
M. Egerstedt and X. Hu. Formation Constrained Multi-Agent Control.;
Social potentials for scalable multi-robot formations, T Balch, M Hybinette
Oberoi (emergent behavior, artificial swarm)
Evolving Self-Organizing Behaviors for a Swarm-Bot MARCO DORIGO AND VITO TRIANNI
Kimoon (collaborative manipulation):
Decentralized controllers for shape generation with robotic swarms, V Kumar, L Chaimowicz - Robotica, 2008.
Composition of Vector Fields for Multi-Robot Manipulation via Caging Jonathan Fink, Nathan Michael and Vijay Kumar

Thursday April 26

Maurice (swarm design):
Flocks, herds and schools: A distributed behavioral model CW Reynolds - ACM SIGGRAPH Computer Graphics, 1987
Hai ShangTBD
Brian HrolenokTBD
Other potential papers
Inspiring and Modeling Multi-Robot Search with Particle Swarm Optimization Jim Pugh and Alcherio Martinoli
Stupid robot tricks: A behavior-based distributed algorithm library for programming swarms of robots, JD McLurkin - 2004
Coordinated multi-robot exploration Burgard, W.; Moors, M.; Stachniss, C.; Schneider, F.E.;
Behavioral Control for Multi-Robot Perimeter Patrol: A Finite State Automata approach Alessandro Marino, Lynne Parker, Gianluca Antonelli and Fabrizio Caccavale
Decentralized Control of Autonomous Swarm Systems Using Artificial Potential Functions: Analytical Design Guidelines Dong Hun Kim, Hua Wang and Seiichi Shin

Week April 30 - May 4 Final Exam Week


Content We May Use

Previous Assignments We May Use


Grading will be based on projects and tests as follows as follows:

  • Midterm exam: 10%
  • Final exam: 10%
  • Programming assignments: 70%
  • Paper presentation: 10%


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