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 2025 Course Information

Announcements

8/25/25: Welcome to the class!

Dates/times

Class meetings:

Mondays, Wednesdays, 12:30-1:50PM, NSH 3002

Instructor

Who	Email
Maxim Likhachev

Teaching Assistants

Who	Email
Alvin Zou
Barath Satheeshkumar

Office Hours

Who	Location	Hours
Instructor	Online	By appointment
TA Alvin Zou	TBD	Thu 2-3PM
TA Barath Satheeshkumar	NSH 4224	Mon 4:30-5:30PM

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 with an upper limit on the penalty of 50%. 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
8/25 (Mon)	Introduction, What is Planning, Role of planning in Robots.	slides	-	-
8/27 (Wed)	Planning Representations: Implicit vs. Explicit Graphs; Skeletonization, Cell decomposition, Lattice-based Graphs	slides	-	-
9/1 (Mon)	LABOR DAY: NO CLASS	-	-	-
9/3 (Wed)	Search Algorithms: A, Multi-goal A, Weighted A, Backward A	slides	HW1: Robot Catching a Target	-
9/8 (Mon)	Search Algorithms: Heuristic Functions, Multi-Heuristic A*	slides	-	-
9/10 (Wed)	*Search Algorithms: Heuristic Functions, Multi-Heuristic A (cont'd)**	-	-	-
9/15 (Mon)	Interleaving Planning and Execution: Anytime and Incremental A*	slides	-	-
9/17 (Wed)	Interleaving Planning and Execution: Real-time Heuristic Search	slides	-	-
9/22 (Mon)	Case Study: Planning for Autonomous Driving	slides	-	-
9/24 (Wed)	Planning Representations: Probabilistic Roadmaps for Continuous Spaces	slides	HW2: Planning for N-DOF Arm	-
9/29 (Mon)	Planning Representations/Search Algorithms: RRT, RRT-Connect, RRT*	slides	-	-
10/1 (Wed)	Case Study: Planning for Mobile Manipulators and Legged Robots	slides	-	-
10/6 (Mon)	Search Algorithms: Markov Property, Dependent Variables, Dominance	slides	-	-
10/8 (Wed)	Search Algorithms: Markov Property, Dependent Variables, Dominance (cont'd)	-	-	-
10/13 (Mon)	FALL BREAK: NO CLASS	-	-	-
10/15 (Wed)	FALL BREAK: NO CLASS	-	-	-
10/20 (Wed)	Case Study: Planning for Coverage, Mapping and Surveyal	slides	-	-
10/22 (Wed)	Planning Representations: Symbolic Representation for Task Planning	slides	-	-