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.

Spring 2019 Course Information

Announcements

2/25: Homework 2 due date moved to March 18th, 11:59PM

Dates/times

Class meetings:

Mondays, Wednesdays, 1:30-2:50PM, NSH 3002

Instructor

Who	Email
Maxim Likhachev

Teaching Assistants

Who	Email
Shohin Mukherjee

Office Hours

Who	Location	Hours
Shohin	NSH 1502E	Mon & Thu, 9-10AM
Maxim	NSH 3211	By appointment or Friday around 10AM

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:

Three homeworks	33%
Exam	20%
In-class pop quizzes	10%
Final project	32%
Participation	5%

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. For example, if the assignment is worth 100 points, your maximum score will drop to 90 points for 1 additional late day and to 80 points for 2 additional late days, etc.

Class lectures/notes:

Tentative schedule for the class (PDF)

Date	Topic	Slides	Homeworks	Additional Info
1/14 (Mon)	Introduction, What is Robot Planning?	slides	-	-
1/16 (Wed)	Planning Representations: Skeleton- and Grid-based Graphs	slides	-	-
1/21 (Mon)	MLK Day - NO CLASS	-	-	-
1/23 (Wed)	*Search Algorithms: Uninformed A Search**	slides	-	-
1/28 (Mon)	*Search Algorithms: A Search**	slides	-	-
1/30 (Wed)	NO CLASS DUE TO WEATHER	-	HW1, Robot Chasing Target Code	-
2/4 (Mon)	*Search Algorithms: Heuristics, Backward A, Weighted A* Search**	slides	-	-
2/6 (Wed)	Interleaving Planning and Execution: Anytime Heuristic Search	slides	-	-
2/11 (Mon)	Interleaving Planning and Execution: Incremental Heuristic Search	slides	-	-
2/13 (Wed)	Interleaving Planning and Execution: Real-time Heuristic Search	slides	-	-
2/18 (Mon)	Planning Representations: Lattice-based Graphs, Explicit vs. Implicit Graphs	slides	-	-
2/20 (Wed)	Case Study: Planning for Autonomous Driving	slides	HW2, N-DoF Planar Arm Code	-
2/25 (Mon)	Planning Representations: Probabilistic Roadmaps for Continuous Spaces	slides	-	-
2/27 (Wed)	NO CLASS	-	-	-
3/4 (Mon)	Planning Representations/Search Algorithms: RRTs	slides	-	-
3/6 (Wed)	Case Study: Planning for Mobile Manipulators and Articulated Robots	slides	-	-
3/11 (Mon)	SPRING BREAK: NO CLASSES	-	-	-
3/13 (Wed)	SPRING BREAK: NO CLASSES	-	-	-
3/18 (Mon)	Search Algorithms: Multi-goal A, IDA	slides	-	-
3/20 (Mon)	Case Study: Planning for Coverage, Mapping and Surveyal	slides	-	slides on Markov Property (not covered)
3/25 (Mon)	Planning Representations: Symbolic Representation for Task Planning	slides	-	-
3/27 (Wed)	Presentation of Final Project Proposals	-	-	-
4/1 (Mon)	Search Algorithms: Planning on Symbolic Representations	slides	HW3	-
4/3 (Wed)	Planning under Uncertainty: Minimax Formulation	slides	-	-
4/8 (Mon)	Planning under Uncertainty: Expected Value Formulation	slides	-	-
4/10 (Wed)	Planning under Uncertainty: Solving Markov Decision Processes	slides	-	-
4/15 (Mon)	Planning under Uncertainty: Partially-Observable Markov Decision Processes	slides	-	-
4/17 (Wed)	Planning under Uncertainty: Partially-Observable Markov Decision Processes (cont'd)	Same slides	-	Exam Topics
4/22 (Mon)	Exam	-	-	-
4/24 (Wed)	Multi-Robot Planning	slides	-	-