| Lec # | TOPICS | KEY DATES |
|---|---|---|
| 1 | Introduction to Cognitive Robotics Learning Objectives, Remote Explorers, Model-based Programming | Students fill out sign-up sheet and review candidate lectures |
| Robots that Deftly Navigate | ||
| 2 | Kinodynamic and Randomized Path Planning Review of Configuration Spaces, Visibility Graphs, Voronoi Diagrams, Potential Fields, and Cell Decomposition Kino-dynamic Planning, Planning with Moving Obstacles, Probabilistic Roadmaps (PRMs), Rapidly Exploring Random Trees (RRTs) | |
| 3 | Introduction to Simultaneous Localization and Mapping (SLAM) (Guest: Paul Robertson) Localization, SLAM, Kalman Filter, Large Scale SLAM | Problem set 1 due Student survey responses discussed |
| 4 | Vision Based SLAM (Guest: Paul Robertson) Topological Maps, Hidden Markov Models (HMM), SIFT, Vision-based Localization | |
| Deducing State and Diagnosing Failure | ||
| 5 | Model-based Diagnosis and Mode Estimation Consistency-based Diagnosis: Candidates, Conflicts, Diagnoses, and Kernel Diagnoses Conflict Extraction and Candidate Generation, Mode Estimation and Probabilistic Diagnosis, Active Probing | |
| 6 | Solving Optimal CSPs through Conflict-Learning Optimal Constraint Satisfaction Problems, Constraint-based A*, Conflict-directed A*, Conflict Extraction | Problem set 2 due Benchmark examples reviewed |
| Reasoning About Soft Constraints | ||
| 7 | Soft Constraint Satisfaction Problems (SCSPs) (Guest: Martin Sachenbacher) Valued Constraint Satisfaction Problems (VCSPs), Branch-and-bound Search for Soft Constraints, Variable Elimination for Soft Constraints, Tree Decomposition, Dynamic Programming | |
| 8 | Solving CSPs and SCSPS via Decomposition and Abstraction (Guest: Martin Sachenbacher) Reduced Ordered Binary Decision Diagrams (ROBDDs), Representing and Manipulating Soft Constraints using Algebraic Decision Diagrams (ADDs) | |
| Planning Complex Missions | ||
| 9 | Mission-level Task Planning (Guest: Robert Tappan Morris) Partial Order Planning, Constraint-based Interval Planning, and Simple Temporal Networks (STNs) | |
| 10 | Dynamic Plan Execution Under Uncertainty STNS, Dispatchable Networks and Dispatching Execution, STNUs, Strong and Dynamic Controllability | |
| 11 | Mixed Human Robotic Exploration (Guest: Jeff Hoffman) | Problem set 3 due |
| Robots that Plan on the Fly | ||
| 12 | Hidden State and Model-based Reactive Planning Universal Planning, Structure Decomposition for Model-based Reactive Planning (MRP), Binary Decision Diagrams, Symbolic MRP | |
| 13 | Continuous, Incremental Path Planning and Exploration Single Source Shortest Path, D*, LRTA* | Advanced lecture schedule assigned |
| 14 | Planning with POMDPs (Student Presenters: Brian Bairstow, Tony Jimenez, and Larry Bush) An Introduction to the Fundamentals of POMDPs, State of the Art in POMDP Research, A Pedagogical Explanation of the Respective Algorithm | |
| 15 | Model-based, Multi-Agent Reasoning in Texas Hold'em Poker (Student Presenters: Brian Edward Mihok and Michael Terry) Leading Techniques in Games Reasoning, Emphasis on Uncertainty Techniques Hidden Markov Models and Bayesian Inference, Neural Networks | |
| 16 | Cognitive Game Theory (Student Presenters: Justin Fox, Jeremie Pouly, and Jennifer Novosad) Alpha-Beta and its Extensions An Evolutionary Algorithm Applied to Chess Inductive Adversary Modeler | Problem set 4 due |
| 17 | Mode Estimation for Hybrid Discrete/Continuous Systems (Student Presenters: Lars Blackmore) Trajectory Tracking for Constraint-based HMMs, Gaussian Filtering for Hybrid HMMs (K-Best and Rao-Blackwell Particle Filtering) | |
| 18 | Particle Filters and their Applications (Student Presenters: Kaijen Hsiao, Jason Miller, and Henry Lefebvre de Plinval-Salgues) Particle Filters in SLAM in Fault Diagnosis | |
| 19 | Hello Computer? (Student Presenters: Shuonan Dong, Shen Qu, and Thomas Coffee) SharedPlan, Plan Recognition, and COLLAGEN | |
| 20 | Advanced Topics in Bayesian Networks (Student Presenters: Tom Temple, Ethan Howe, and James Lenfestey) Dynamic Bayes Networks, Exact Inference, Approximate Inference (PF), Learning, Probabilistic Relational Models, Parameter/Structure Estimation | |
| Sensing and Manipulating at the Cognitive Level | ||
| 21 | Visual Interpretation using Probabilistic Grammars (Guest: Paul Robertson) Statistical Parsing, Image Segmentation, Monte Carlo Methods, Language Learning | |
| 22 | Safe Execution of Bipedal Walking Tasks (Guest: Andreas Hoffman) Motivation and Requirements, Bipedal Balance Control Strategies, Common Control Approaches (and their Failings), Task-level Control using Model-based Executives, Whole-body Control | |
| Human - Robot Interaction | ||
| 23 | Working with and Learning from Humans as Partners (Guest: Cynthia Breazeal) Multi-modal Communication, Human-robot Teamwork, Socially Guided Learning | |
| 24 | Nursebot: Dialogue as a Decision Making Process (Guest: Nick Roy) Model-based Dialog Management, Hierarchical Planning under Uncertainty, Reinforcement Learning for Human Interaction | |
| 25 | Project Demonstrations | |
| 26 | Project Demonstrations (cont.) | |