16-350 Planning Techniques for Robotics

Planning is one of the core components that enable robots to be autonomous. Robot planning is responsible for deciding in real-time what the robot should do next, how to do it, where the robot should move next and how to move there. This class does an in-depth study of popular planning techniques in robotics and examines their use in ground and aerial robots, humanoids, mobile manipulation platforms and multi-robot systems. The students learn the theory of these methods and also implement them in a series of programming-based projects.

To take the class students should have a good knowledge of programming and data structures.

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Spring 2023 Course Information

Announcements

Dates/times

Instructor

Teaching Assistants

Office Hours

Grading

The criteria used to compute the final grade will consist of a combination of scores obtained on the exam, three programming assignments (homeworks), pop quizzes, final project and class participation:

Each student has a total of 3 free late days that may be used as needed for homeworks. No late days may be used for the final project!
Additional details: A late day is defined as a 24-hour period after the deadline. After the free late days are used up, each additional late day will incur a 10% penalty on the maximum achievable score with an upper limit on the penalty of 50%. For example, if the assignment is worth 100 points and you score is 80, then you actual score will be 72 if you have 1 additional late day, 64 if you have 2 additional late days, etc.

Class lectures/notes:

Tentative schedule for the class (PDF)

Date	Topic	Slides	Homeworks	Additional Info
1/18 (Wed)	Introduction, What is Robot Planning?	slides	-	-
1/23 (Mon)	Planning Representations: Skeleton- and Grid-based Graphs, Explicit vs. Implicit Graphs	slides	-	-
1/25 (Wed)	Search Algorithms: Uninformed A* Search	slides	-	-
1/30 (Mon)	Search Algorithms: A* Search, Multi-goal A*	slides	Robot Chasing Target Planning HW1	-
2/1 (Wed)	Search Algorithms: Heuristics, Backward A*, Weighted A* Search	slides	-	-
2/6 (Mon)	Interleaving Planning and Execution: Anytime Heuristic Search	slides	-	-
2/8 (Wed)	Interleaving Planning and Execution: Incremental Heuristic Search	slides	-	-
2/13 (Mon)	Interleaving Planning and Execution: Real-time Heuristic Search	slides	-	-
2/15 (Wed)	Planning Representations: Lattice-based Graphs	slides	-	-
2/20 (Mon)	Case Study: Planning for Autonomous Driving	slides	-	-
2/22 (Wed)	Planning Representations: Probabilistic Roadmaps for Continuous Spaces	slides	N-DoF Planar Arm Planning HW2	-
2/27 (Mon)	Planning Representations/Search Algorithms: RRT, RRT-Connect, RRT*	slides	-	-
3/1 (Wed)	Planning Representations/Search Algorithms: RRT, RRT-Connect, RRT* (cont'd)	-	-	-
3/6 (Mon)	SPRING BREAK: NO CLASSES	-	-	-
3/8 (Mon)	SPRING BREAK: NO CLASSES	-	-	-
3/13 (Mon)	Case Study: Planning for Mobile Manipulators and Articulated Robots	slides	-	-
3/15 (Wed)	Search Algorithms: Markov property, independent vs. dependent variables	slides	-	-
3/20 (Mon)	Case Study: Planning for Coverage, Mapping and Surveyal	slides	-	-
3/22 (Wed)	Planning Representations: Symbolic Representation for Task Planning	slides	Symbolic Planning HW3	-
3/27 (Mon)	Search Algorithms: Planning on Symbolic Representations (guest lecture by Alex LaGrassa)	slides	-	-
3/29 (Wed)	Presentation of Final Project Proposals	-	-
4/3 (Mon)	Search Algorithms: Planning on Symbolic Representations (cont'd)	-	-	-
4/5 (Wed)	Planning under Uncertainty: Minimax Formulation	slides	-	-
4/10 (Mon)	NO CLASS	-	-	-
4/12 (Wed)	Planning under Uncertainty: Expected Value Formulation	slides	-	-
4/17 (Mon)	Exam	-	-	-
4/19 (Wed)	Planning under Uncertainty: Solving Markov Decision Processes	slides	-	-
4/24 (Mon)	Multi-Robot Planning	slides	-	-

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