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.

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Fall 2025 Course Information

Announcements

• 8/25/25: Welcome to the class!
  

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, 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	HW3: Symbolic planning	-
10/27 (Mon)	Search Algorithms: Planning on Symbolic Representations	slides	-	-
10/29 (Wed)	Presentation of Final Project Ideas	-	-	-
11/3 (Mon)	Planning under Uncertainty: Minimax Formulation	slides	-	-
11/5 (Wed)	Planning under Uncertainty: Expected Cost Formulation, Solving MDPs	slides	-	-
11/10 (Mon)	Planning under Uncertainty: Expected Cost Formulation, Solving MDPs (cont'd)	-	-	-
11/12 (Wed)	Planning under Uncertainty: Partially-Observable Markov Decision Processes	slides	-	-
11/17 (Mon)	Planning under Uncertainty: Partially-Observable Markov Decision Processes (cont'd)	-	-	-
11/19 (Wed)	Multi-Robot Planning	slides	-	-
11/24 (Mon)	Exam	-	-	-
11/26 (Wed)	NO CLASS, Happy Thanksgiving!	-	-	-
12/1 (Mon)	Multi-Robot Planning (cont'd)	-	-	-

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