16.412J/6.834J COGNITIVE ROBOTICS

Schedule and Posted Lectures, Spring 2005

MW 10:30 12:00 in 33-418

 

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Lecture notes hyperlinked to lecture title on date given.

Problem set hyperlinked to problem set name on date out.

Topics
Handouts
W 2 Feb
(1) Introduction to Cognitive Robotics

Learning Objectives, Remote Explorers, Model-based Programming

Lecture notes (1a) & (1b)

Student sign-up sheet

Candidate Lectures

Robots that Deftly Navigate

 

 
M 7 Feb

(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)

Lecture Notes
W 9 Feb

(3) Introduction to Simultaneous Localization and Mapping (SLAM)

(Guest: Paul Robertson)

Localization, SLAM, Kalman Filter, Large Scale SLAM

Lecture Notes, Pset #1

Student Topics & Interests

M 14 Feb

(4) Vision Based SLAM

(Guest: Paul Robertson)

Topological Maps, Hidden Markov Models (HMM), SIFT, Vision-based localization.

Lecture Notes

Deducing State and Diagnosing Failure
   
W 16 Feb

(5) Model-based Diagnosis & Mode Estimation

Consistency-based diagnosis: candidates, conflicts, diagnoses, and kernel diagnoses. conflict extraction and candidate generation, mode estimation and probabilistic diagnosis, active probing.

Lecture Notes

T Feb 22

(6) Solving Optimal CSPs Through Conflict-Learning


Optimal Constraint Satisfaction Problems, Constraint-based A*, Conflict-directed A*, conflict extraction

Lecture Notes

Pset #2

Benchmark Examples

Reasoning About Soft Constraints
 

 

 

W 23 Feb

(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.

Lecture Notes

M 28 Feb

(8) Solving CSPs and SCSPS via Decomposition & Abstraction

(Guest: Martin Sachenbacher)

Reduced ordered binary decision diagrams (ROBDDs), representing and manipulating soft constraints using algebraic decision diagrams (ADDs).

Lecture Notes

Planning Complex Missions
   
W 2 Mar

(9) Mission-level Task Planning

Partial Order Planning, Constraint-based Interval Planning, and Simple Temporal Networks (STNs)

Lecture Notes (a) Lecture Notes (b)

M 7 Mar

(10) Dynamic Plan Execution Under Uncertainty

STNS, Dispatchable Networks and Dispatching Execution, STNUs, Strong and Dynamic Controllability.

Lecture Notes

W 9 Mar

(11) Mixed Human Robotic Exploration

(Guest: Jeff Hoffman (Astronaut))

 

Pset #3

 
Robots that Plan on the Fly
   
M 14 Mar

(12) Hidden State and Model-based Reactive Planning

Universal Planning, Structure Decomposition for Model-based Reactive Planning (MRP), Binary Decision Diagrams, Symbolic MRP.

Lecture Notes

W 16 Mar

(13) Continuous, Incremental Path Planning and Exploration

Single source shortest path, D*, LRTA*

Lecture notes (a) & (b),

Advanced Lecture Schedule

 

******* SPRING BREAK *******
   
M 28 Mar

Planning with POMDPs

(Brian Bairstow, Tony Jimenez, Larry Bush)

An introduction to the fundamentals of POMDPs, state of the art in POMDP research, a pedagogical explanation of the respective algorithm.

Preliminary Materials

Lecture Notes

W 30 Mar

Model-based, Multi-Agent Reasoning in Texas Holdem Poker

(Brian Edward Mihok, Michael Terry)

Leading techniques in games reasoning, emphasis on uncertainty techniques. Hidden Markov Models and Bayesian Inference, neural networks.

Preliminary Materials

Lecture Notes

M 4 Apr

Cognitive Game Theory

(Justin Fox, Jeremie Pouly, and Jennifer Novosad)

Alpha-Beta and Its Extensions; An Evolutionary Algorithm Applied to Chess; Inductive Adversary Modeler

Preliminary Materials

Lecture Notes

Pset #4

W 6 Apr

Mode Estimation for Hybrid Discrete/Continuous Systems

(Lars Blackmore)

Trajectory Tracking for Constraint-based HMMs,
Gaussian Filtering for Hybrid HMMs
(K-Best and Rao-Blackwell Particle Filtering)

Lecture Notes

M 11 Apr

Particle Filters and their Applications

(Kaijen Hsiao, Jason Miller, Henry Lefebvre de Plinval-Salgues)

Particle filters in SLAM, in Fault Diagnosis

Preliminary Materials

Lecture Notes

W 13 Apr

Hello Computer?

(Shuonan Dong, Shen Qu, Thomas Coffee)

SharedPlan, Plan Recognition, and COLLAGEN

Lecture Notes

W 20 Apr

Advanced Topics in Bayesian Networks

(Tom Temple, Ethan Howe, and James Lenfestey)

Intro, Dynamic Bayes Networks, Exact inference,
Approximate Inference (PF), Learning, Probabilistic Relational Models, , Parameter/Structure estimation

Preliminary Materials

Lecture Notes (a)

Lecture Notes (b)

 
Sensing and Manipulating at the Cognitive Level
   
M 25 Apr

(15) Visual Interpretation using Probabilistic Grammars

(Guest: Paul Robertson)

Statistical Parsing, Image Segmentation, Monte-Carlo Methods, Language Learning

Lecture Notes

W 27 Apr

Safe Execution of Bipedal Walking Tasks

(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
   
M 2 May

(17) Working with and Learning from Humans as Partners

(Guest: Cynthia Breazeal)

Multi-modal communication, human-robot teamwork, socially guided learning

 
W 4 May

(18) Nursebot: dialogue as a decision making process

(Guest: Nick Roy)

Model-based dialog management, hierarchical planning under uncertainty, reinforcement learning for human interaction

Lecture Notes

W 9 May

Project Demonstrations

(15 Min. student presentation)

   
W 11 May

Project Demonstrations

(15 Min. student presentation)

   

 

 

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