16-782 Planning and Decision-making in Robotics

Planning and Decision-making are critical components of autonomy in robotic systems. These components are responsible for making decisions that range from path planning and motion planning to coverage and task planning to taking actions that help robots understand the world around them better. This course studies underlying algorithmic techniques used for planning and decision-making in robotics and examines case studies in ground and aerial robots, humanoids, mobile manipulation platforms and multi-robot systems. Students in the class will learn these algorithms and implement them in a series of programming-based projects.

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

Fall 2020 Course Information

Announcements

8/31/20: Welcome to the class!

Dates/times

Class meetings:

Mondays, Wednesdays, 1:30-2:50PM, Online

Instructor

Who	Email
Maxim Likhachev

Teaching Assistants

Who	Email
Ramkumar Natarajan
Shivam Vats

Office Hours

Who	Location	Hours
Instructor	Online	By appointment
TA Ramkumar Natarajan	Online	Wed, 5-6PM
TA Shivam Vats	Online	Mon, 10:30-11:30AM

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 posted here (PDF)

Date	Topic	Slides	Homeworks	Additional Info
8/31 (Mon)	Introduction, What is Planning, Role of planning in Robots.	slides	-	-
9/2 (Wed)	Planning Representations: Implicit vs. Explicit Graphs; Skeletonization, Cell decomposition, Lattice-based Graphs	slides	-	-
9/7 (Mon)	LABOR DAY: NO CLASS	-	-	-
9/9 (Wed)	Search Algorithms: A, Weighted A, Backward A*	slides	-	-
9/14 (Mon)	*Search Algorithms: A, Weighted A, Backward A (cont'd)**	-	HW1: Robot Catching a Target	-
9/16 (Wed)	Search Algorithms: Heuristic Functions, Multi-Heuristic A*	slides	-	-
9/21 (Mon)	*Search Algorithms: Heuristic Functions, Multi-Heuristic A (cont'd)**	-	-	-
9/23 (Wed)	Search Algorithms: Multi-goal A*	slides	-	-
9/28 (Mon)	Interleaving Planning and Execution: Anytime and Incremental A*	slides	-	-
9/30 (Wed)	*Interleaving Planning and Execution: Anytime and Incremental A (cont'd)**	-	-	-
10/5 (Mon)	Interleaving Planning and Execution: Real-time Heuristic Search	slides	-	-
10/7 (Wed)	Case Study: Planning for Autonomous Driving	slides	-	-
10/12 (Mon)	Planning Representations: Probabilistic Roadmaps for Continuous Spaces	slides	HW2: Planning for an Arm	-
10/14 (Wed)	Planning Representations/Search Algorithms: RRT, RRT-Connect, RRT*	slides	-	-
10/19 (Mon)	*Planning Representations/Search Algorithms: RRT, RRT-Connect, RRT (cont'd)**	-	-	-
10/21 (Wed)	*Planning Representations/Search Algorithms: RRT, RRT-Connect, RRT (cont'd)**	-	-	-
10/26 (Mon)	*Planning Representations/Search Algorithms: BIT (lecture by Shivam Vats)**	slides	-	-
10/28 (Wed)	Planning Representations/Search Algorithms: Trajectory Optimization Techniques (lecture by Ramkumar Natarajan), updated	slides	-	-
11/2 (Mon)	Case Study: Planning for Mobile Manipulators and Legged Robots	slides	-	-
11/4 (Wed)	Case Study: Planning for Coverage, Mapping and Surveyal	slides	-	-
11/9 (Mon)	Presentation of Final Project Ideas	-	-	-
11/11 (Wed)	Planning Representations: Symbolic Representation for Task Planning	slides	HW3: Symbolic planning	-
11/16 (Wed)	Search Algorithms: Planning on Symbolic Representations	slides	-	-
11/18 (Wed)	Planning under Uncertainty: Minimax Formulation	slides	-	-
11/23 (Mon)	Planning under Uncertainty: Expected Cost Formulation, Solving MDPs	slides	-	-
11/25 (Wed)	NO CLASS, Happy Thanksgiving!	-	-	-
11/30 (Mon)	Planning under Uncertainty: Partially-Observable Markov Decision Processes	slides	-	-
12/2 (Wed)	Planning under Uncertainty: Partially-Observable Markov Decision Processes (cont'd)	-	-	-
12/7 (Mon)	Multi-Robot Planning	slides	-	-
12/9 (Wed)	Multi-Robot Planning (cont'd)	-	-	-