Please access Zoom class lectures via Canvas.
Discussion board: https://us.edstem.org/courses/424/discussion/Use this board to discuss the content of the course. Feel free to discuss homeworks, projects, and any confusion over topics discussed in class. It is also acceptable to ask for clarifications about the statement of homework problems, but not about their solutions.
Probabilistic Robotics, S. Thrun, W. Burgard, and D. Fox., MIT Press, Cambridge, MA, September 2005.
Date | Topic | Slides | Reading (textbook/papers) | Homework/Project |
31-Mar | Introduction | Intro | Chapter 1, 2 of Probabilistic Robotics | - |
2-Apr | Bayesian state estimation, Filtering | Prob | Chapters 1, 2 of Probabilistic Robotics | - |
7-Apr | Gaussian Processes | GP | Chapter 2 (Rasmussen book), GP-BayesFilters, GP-Control | HW1 posted |
9-Apr | Gaussian Processes, Neural Networks | Neural-nets | Chapter 6, 9 of Deep Learning | - |
14-Apr | Neural Networks | Neural-nets | Chapter 6, 9 of Deep Learning | - |
16-Apr | Motion and Sensor Models | Motion models, sensor models | Chapter 5, 6 of Probabilistic Robotics | - |
17-Apr | Guided Project 1 Proposal Due Open-ended Project Proposal Due |
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20-Apr | HW1 Due | |||
21-Apr | Kalman Filters (linear, EKF) | Kalman filters | Chapters 3 and 7 (skip 3.5 and derivations) | - |
23-Apr | Particle Filters | Particle filters | Chapters 4 and 8 (skip derivations) | - |
28-Apr | Particle Filters | Guided Project 1 Mid-progress Report Due | ||
30-Apr | Occupancy maps, SLAM | Occupancy mapping, SLAM | Chapters 9 and 10, Octomaps | |
5-May | - | |||
7-May | Graph-SLAM and Fast-SLAM | Fast-SLAM | GTSAM, Chapter 11 and 13 | - |
10-May | Guided Project 1 Final Report Due Open-ended Project Mid-progress Report Due |
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11-May | HW3 posted Guided Project 2 posted |
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12-May | Fast-SLAM, Exploration | Exploration | Multi-robot, Curiosity-driven learning, Object modeling | - |
14-May | Deterministic planning | Det-Planning | Motion planning, A* slides from 473 | - |
15-May | HW2 Due | |||
19-May | Sampling based planning w/ RRTs | RRT | Complex motion planning, Anytime and replanning A*, RRT page | - |
21-May | RRTs, Markov Decision Processes | MDPs | Book chapter 14 | - |
26-May | MDPs, Inverse Reinforcement Learning | IOC | - | |
28-May | Task and motion planning | TAMP | - | |
2-Jun | Learning to grasp | Grasp | GraspNet, clutter | - |
4-Jun | Summary | Summary | SE3-Nets, Langrangian Networks | - |