| Part A: Robots that Plan and Act in the World |
| 1 |
Introduction to Cognitive Robots
Remote Explorers and Human Interation Systems |
Muscettola, N., P. Nayak, B. Pell, and B. Williams. "Remote Agent: To Boldly Go Where No AI System Has Gone Before." Artificial Intelligence 103 (1998): 5-47.
Pineau, J., M. Montemerlo, M. Pollack, N. Roy, and S. Thrun. "Towards Robotic Assistants in Nursing Homes: Challenges and Results." Robotics and Autonomous Systems 42 (2003): 271-281. |
| A1: Robots that Deftly Navigate |
| 2 |
Planning Routes by Generating Maps
Configuration Spaces, Visibility Graphs, Voronai Diagrams, Potential Fields, and Cell Decomposition |
Bohlin, R., and L. Kavraki. "Path Planing Using Lazy PRM." ICRA (2000).
Latombe, Jean-Claude. Robot Motion Planning. Boston, MA: Kluwer Academic Publishers, 1991. ISBN: 079239206X.
Rimon, E., and D. E. Koditschek. "Exact Robot Navigation Using Artificial Potential Functions." IEEE Transactions on Robotics and Automation 8, no. 5 (October 1992): 501518.
Thrun, S. "Learning Metric-topological Maps for Indoor Mobile Robot Navigation." Artificial Intelligence 99, no. 1 (1998): 21-71. |
| 3 |
Randomized Path Planning
Kino-dynamic Planning, Planning with Moving Obstacles, Probabilistic Roadmaps (PRMs), Rapidly Exploring Random Trees (RRTs) |
Hsu, D., R. Kindel, J.C. Latombe, and S. Rock. "Randomized Kinodynamic Motion Planning with Moving Obstacles." Fourth International Workshop on Algorithmic Foundations of Robotics, 2000.
LaValle, Steven M. "Rapidly-Exploring Random Trees: A New Tool for Path Planning." Technical Report No. 98-11, Dept. of Computer Science, Iowa State University, October 1998. |
| A2: Planning and Executing Complex Missions |
| 4 |
Path Planning in Unknown Environments: An Overview |
Stentz, A. "Optimal and Efficient Path Planning for Partially-Known Environments." Proceedings IEEE International Conference on Robotics and Automation (May 1994). |
| 5 |
Incremental Path Planning
Single Source Shortest Path, D*, LRTA* |
Koenig, S., and M. Likhachev. "Incremental A*." In Advances in Neural Information Processing Systems (NIPS). Vol. 14. Cambridge, MA: MIT Press, 2002. ISBN: 0262042088. |
| 6 |
Mission-level Task Planning
Partial Order Planning, Constraint-based Interval Planning, and Simple Temporal Networks (STNs) |
Smith, David E., Jeremy Frank, and Ari Jonsson. "Bridging the Gap between Planning and Scheduling." Knowledge Engineering Review 15, no. 1 (2000).
Kim, P., B. Williams, and M. Abramson. "Executing Reactive, Model-based Programs through Graph-based Temporal Planning." IJCAI (2001): 487-493. |
| Part B: Robots that are State-Aware |
| 7 |
Foundations of Estimation
Bayes Filters, Kalman Filters, and HMMs |
Welch, G., and G. Bishop. "An Introduction to the Kalman Filter." University of North Carolina at Chapel Hill, Dept. of Computer Science, TR 95-041.
Leonard, J. J., and H. F. Durrant-Whyte. "Mobile Robot Localization by Tracking Geometric Beacons." IEEE Trans Robotics and Automation 7, no. 3 (June 1991): 376-382.
Rabiner, L. R. "A Tutorial on Hidden Markov Models." Proceedings of the IEEE 77 (1989): 257-286. |
| B1: Robots that Find Their Way in the World |
| 8 |
Determining Location Through Particle Filters
MCMC Methods, Rejection Sampling, Importance Sampling, Metropolis, Particle Filters for Localization |
Rabiner, L. R. "A Tutorial on Hidden Markov Models." Proceedings of the IEEE 77 (1989): 257-286.
Doucet, A., N. de Freitas, N. Gordon, eds.Sequential Monte Carlo Methods in Practice. New York, NY: Springer-Verlag, 2001. ISBN: 0387951466.
Neal, Radford M. Probabilistic Inference Using Markov Chain Monte Carlo Methods. University of Toronto CS Tech Report, 1993.
Thrun, S., D. Fox, W. Burgard, and F. Dellaert. "Robust Monte Carlo Localization for Mobile Robots." Artificial Intelligence 128 (2001): 1-2 and 99-141. |
| 9 |
Learning Maps
Scan-matching, ICP, SLAM using Kalman Filters, Topological maps, Fast-Slam |
Leonard, J. J., I. J. Cox, and H. F. Durrant-Whyte. "Dynamic Map Building for an Autonomous Mobile Robot." Int. J. Robotics Research 11, no. 4 (August 1992): 286-298.
Kuipers, B. J., and Y. T. Byun. "A Robot Exploration and Mapping Strategy Based on a Semantic Hierarchy of Spatial Representations." Journal of Robotics and Autonomous Systems 8 (1991): 47-63. |
| B2: Robots that Deduce and Control Their Internal State |
| 10 |
Model-based Programming and Model-based Diagnosis
Model-based Diagnosis |
Davis, R. and W. C. Hamscher. "Model-based Reasoning: Troubleshooting." InExploring Artificial Intelligence: Survey Talks from the National Conferences on Artificial Intelligence. Edited by Shrobe, H. E. San Mateo, CA: Morgan Kaufmann, 1988, pp. 297-346. ISBN: 0934613699.
de Kleer, J., and B. Williams. "Diagnosing Multiple Faults." Artificial Intelligence 32, no. 1 (April 1987): 97-130. |
| 11 |
Conflict-directed Diagnosis & Probabilistic Mode Estimation
Consistency-based Diagnosis |
de Kleer, Johan, Alan K. Mackworth, and Raymond Reiter. "Characterizing Diagnoses and Systems." Artificial Intelligence 56 (1992).
de Kleer, Johan, and Brian C. Williams. "Diagnosis with Behavioral Modes." In Proceedings of the International Joint Conference on Artificial Intelligence, Detroit, MI, 1989, pp. 1324-1330. Also in Hamscher et al., Eds. Readings in Model-based Diagnosis. Morgan Kaufman, 1992, pp. 124-130. |
| 12 |
Incremental Mode Estimation and Hybrid Systems
Incremental Logical Inference, Trajectory Tracking for Constraint-based, Gaussian Filtering for Hybrid HMMs (K-Best and Rao-Blackwell Particle Filtering) |
Williams, Brian C., Michel Ingham, Seung H. Chung, and Paul H. Elliott. "Model-based Programming of Intelligent Embedded Systems and Robotic Space Explorers." Invited paper in Proceedings of the IEEE: Special Issue on Modeling and Design of Embedded Software 9, no. 1 (January 2003): 212-237.
Kurien, J., and P. Nayak. "Back to the Future for Consistency Based Trajectory Tracking." Proceedings from the 17th National Conference on Artificial Intelligence, Austin, TX, August 2000. pp. 370377.
Hofbaur, M. W., and B. C. Williams. "Mode Estimation of Probabilistic Hybrid Systems." In Hybrid Systems: Computation and Control (2002).
Funiak, S., and B. C. Williams. "Multi-modal Particle Filtering for Hybrid Systems with Autonomous Mode Transitions." In: DX-2003, SafeProcess 2003. |
| 13 |
Optimal CSPs and Conflict-directed A*
Constraint Satisfaction Problems and Conflict-directed A* Search |
Williams, Brian C., and Robert Ragno. "Conflict-directed A* and its Role in Model-based Embedded Systems." To appear in the Special Issue on Theory and Applications of Satisfiability Testing, Journal of Discrete Applied Math. |
| 14 |
Context-based Vision
Bill Freeman Guest lecture |
Murphy, K., A. Torralba, and W. Freeman. "Using the Forest to See the Trees: A Graphical Model Relating Features, Objects, and Scenes." NIPS (2003). |
| Fast Planning |
| 15 |
Planning as Heuristic Forward Search
FF Planning
Student Advanced Lectures
LPG: Local Search for Planning Graphs (Seung Chung) |
Hoffmann, Jorg, and Bernhard Nebel. "The FF Planning System: Fast Plan Generation Through Heuristic Search." Journal of Artificial Intelligence Research (2001).
Gerevini, A., A. Saetti, and I. Serina. "Planning through Stochastic Local Search and Temporal Action Graphs." To appear in Journal of Artificial Intelligence Research (JAIR).
Bonet, Blai, and Hector Geffner. "Planning as Heuristic Search." Artificial Intelligence Journal (2001). |
| 16 |
Student Advanced Lectures (cont.)
Fast Solutions to Constraint Satisfaction Problems (Robert Effinger & Dan Lovell) |
Ginsberg, Matthew L. "Dynamic Backtracking." Journal of Artificial Intelligence Research 1 (1993): 25-46.
Prosser, P. "Hybrid Algorithms for the Constraint Satisfaction Problem." Computational Intelligence 9 (1993): 268-299. |
| Cooperative Planning |
| 17 |
Student Advanced Lectures (cont.)
Distributed CSPs and Task Assignment (Thomas Leaute & Justin Werfel) |
Yokoo, M., E. Durfee, T. Ishida, and K. Kuwabara. "The Distributed Constraint Satisfaction Problem: Formalization and Algorithms." IEEE Transactions on Knowledge and Data Engineering 10, no. 5 (September/October 1998).
Zlot, R., A. Stentz, M. Dias, and S. Thayer. "Multi-Robot Exploration Controlled by a Market Economy." IEEE International Conference on Robotics and Automation (May 2002). |
| 18 |
Student Advanced Lectures (cont.)
Distributed Reinforcement Learning and MDPs (Lars Blackmore & Steve Block) |
Tan. M. "Multi-Agent Reinforcement Learning: Independent vs. Cooperative Agents." Proceedings of the Tenth International Conference on Machine Learning (1993): 330-337. Amherst, MA.
Ahmadabadi, M., and M. Asadpour. "Expertness Based Cooperative Q-Learning." IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics 32, no. 1 (February 2002).
Eshgh, S., and M. Ahmadabadi. "An Extension of Weighted Strategy Sharing in Cooperative Q-Learning for Specialized Agents." Proceedings of the 9th International Conference on Neural Information Processing (ICONIP02) 1 (2002). |
| Vision-based Exploration |
| 19 |
Student Advanced Lectures (cont.)
Vision-based SLAM (Soren Riisgaard) |
Se, S., D. Lowe, and J. Little. "Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual Landmarks." The International Journal of Robotics Research 21, no. 8 (August, 2002): 735-758. |
| 20 |
Student Advanced Lectures (cont.)
Information Based Adaptive Robotic Exploration (Morten Rufus Blas) & Uncertainty and Visual Exploration Alexander Omelchenko) |
Bourgault, F., A. Makarenko, S. B. Williams, B. Grocholsky, and H. F. Durrant-Whyte. "Information Based Adaptive Robotic Exploration." IEEE/RSJ Intl. Workshop on Intelligent Robots and Systems (2002).
Whaite, P., and F. P. Ferrie. "From Uncertainty to Visual Exploration." IEEE Transactions on Pattern Analysis and Machine Intelligence 13, no. 10 (October 1991). |
| Part C: Robots that Preplan for an Uncertain Future |
| 21 |
Reactive Planning in Large State Spaces Through Decomposition and Serialization
Student Advanced Lectures (cont.)
SIFT SLAM Vision Details (Vikash Mansinghka) |
Se, S., D. Lowe, and J. Little. "Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual Landmarks." The International Journal of Robotics Research 21, no. 8.
Williams, Brian C., and P. Pandurang Nayak. "A Reactive Planner for a Model-based Executive." In Proceedings of the International Joint Conference on Artificial Intelligence (1997).
Chung, S., and B. C. Williams. "A Factored Symbolic Approach to Reactive Planning." In International Conference on Self-Adaptive Software, Washington DC (June 2003). |
| 22 |
The Linear Programming Approach to Approximate Dynamic Programming (Guest Lecturer: Daniela Pucci de Farias)
Markov Decision Processes, Approximate Dynamic Programming and Linear Programming, Performance and Error Analysis, and Constraint Sampling |
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| 23 |
Partially Observable Markov Decision Processes
POMDPs, Policy Trees and Value Iteration |
Kaelbling, L., M. Littman, and A. Cassandra. "Planning and Acting in Partially Observable Stochastic Domains." Artificial Intelligence 101 (1998).
Pineau, J., G. Gordon, and S. Thrun. "Point-based value iteration: An anytime algorithm for POMDPs." In International Joint Conference on Artificial Intelligence (IJCAI). Acapulco, Mexico. August 2003. |
| 24 |
Approximate Solutions to POMDPs
Heuristics, Coastal Navigation, and Real World Apps |
Cassandra, Anthony R. "Exact and Approximate Algorithms for Partially Observable Markov Decision Processes." Chapter 6, Ph.D. Thesis. Brown University, Department of Computer Science, Providence, RI, 1998. |
| 25 |
Dynamic Scheduling and Execution
Temporal Plan Execution, Dynamic Scheduling, and Simple Temporal Networks |
Dechter, R., I. Meiri, and J. Pearl. "Temporal Constraint Networks." Artificial Intelligence 49 (May 1991): 61-95.
Muscettola, N., P. Morris, and I. Tsamardinos. "Reformulating Temporal Plans for Efficient Execution." In Proc. Of Sixth Int. Conf. on Principles of Knowledge Representation and Reasoning (KR 98), 1998. |
| 26 |
Project Demonstrations
10 minute Student Presentations |
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