Professor Chandra will teach CS 6501 - Multi-Robot Navigation in Spring 2026.
This course has been designed from first principles and developed entirely from scratch including all lectures and assignments. All instruction is delivered on the blackboard to encourage deep reasoning, step-by-step derivation, and conceptual understanding. The course is organized into three parts: Part I (Theory), Part II (Algorithms), and Part III (Student Participation), and is intended to prepare graduate students to both conduct rigorous theoretical research in multi-robot navigation (MRN) and to pursue application-driven work grounded in a strong mathematical foundation.
Part I formalizes the MRN problem, introduces a standard taxonomy (centralized vs. decentralized systems, communication protocols, observability, and cooperation), and examines key system properties such as safety, liveness, social compliance, and fairness. Part II develops the principles behind major MRN algorithmic paradigms including MAPF, MARL, Dynamic Game Theory, Collision Avoidance, Neural Control, and Foundation Models while engaging with influential recent research papers in each area. Part III is where students will apply what they have learned up til now in the form of in-class research paper and project presentations.
Link to SMGLib to be used in Projects: SMGLib Codebase.
| Date | Day | Topic | Assigned Reading |
|---|---|---|---|
| PART 1: Theory | |||
| 12-Jan-26 | Monday | Introduction + Logistics + Problem Formulation | Introduction Slides |
| 14-Jan-26 | Wednesday | Problem Formulation (contd.) and Taxonomy | Lecture Notes |
| 19-Jan-26 | Monday | Holiday (MLK Day) | |
| 21-Jan-26 | Wednesday | Safety - I (Intro to CBFs) |
Safety Barrier Certificates for Heterogeneous Multi-Robot Systems Lecture Notes |
| 26-Jan-26 | Monday | Guest Lecture |
Prof. Jiaoyang Li (CMU) Recent Advances in Multi-Agent Pathfinding |
| 28-Jan-26 | Wednesday | Safety - II (CBFs for multi-robot systems) |
Safety Barrier Certificates for Heterogeneous Multi-Robot Systems
Lecture Notes |
| 2-Feb-26 | Monday | Safety - III (HOCBFs and Neural CBFs) | BarrierNet: Differentiable Control Barrier Functions for Learning of Safe Robot Control |
| 4-Feb-26 | Wednesday | Liveness - I (symmetry & RHS-based deadlock resolution) |
Fast, On-line Collision Avoidance for Dynamic Vehicles Using Buffered Voronoi Cells
Lecture Notes |
| 9-Feb-26 | Monday | Liveness - II (minimally-invasive deadlock prevention) |
Deadlock-free, Safe, and Decentralized Multi-Robot Navigation in Social Mini-Games
DS-MPEPC: Safe and Deadlock-Avoiding Robot Navigation in Cluttered Dynamic Scenes Lecture Notes |
| 11-Feb-26 | Wednesday | Fairness - I (Mechanism Design) |
Lectures Notes on Algorithmic Game Theory (Ch. 2)
Lecture Notes |
| 16-Feb-26 | Monday | Fairness - II and Social Compliance |
GAMEOPT: Optimal Real-time Multi-Agent Planning and Control at Dynamic Intersections
VLM-Social-Nav: Socially Aware Robot Navigation through Scoring using Vision-Language Models Principles and Guidelines for Evaluating Social Robot Navigation Algorithms Lecture Notes |
| Project Check-in, Exam, and Spring Break | |||
| 18-Feb-26 | Wednesday | Project Check-ins | |
| 23-Feb-26 | Monday | Midterm (take home) | |
| 25-Feb-26 | Wednesday | Midterm (take home) | |
| 2-Mar-26 | Monday | Spring Break | |
| 4-Mar-26 | Wednesday | Spring Break | |
| PART 2: Algorithms | |||
| 9-Mar-26 | Monday | Guest Lecture |
Prof. Ferdinando Fioretto (UVA) Simultaneous Multi-Robot Motion Planning with Projected Diffusion Models |
| 11-Mar-26 | Wednesday | MAPF-I | Multi-Agent Path Finding – Overview |
| 16-Mar-26 | Monday | MAPF-II |
Socialmapf: Optimal and efficient multi-agent path finding with strategic agents
Multi-Agent Path Finding – Overview |
| 18-Mar-26 | Wednesday | MARL-I | Sequential Decision Theory |
| 23-Mar-26 | Monday | MARL-II | Game-Theoretic Multiagent Reinforcement Learning |
| 25-Mar-26 | Wednesday | Mid-Semester Project Presentation | |
| 30-Mar-26 | Monday | Mid-Semester Project Presentation | |
| 1-Apr-26 | Wednesday | Collision Avoidance | Reciprocal N-body Collision Avoidance (ORCA) |
| 6-Apr-26 | Monday | Dynamic Game Theory |
Game-Theoretic Planning for Risk-Aware Interactive Agents
Maximum-Entropy Multi-Agent Dynamic Games |
| 8-Apr-26 | Wednesday | Guest Lecture |
Prof. Negar Mehr (UC Berkeley) Learning and Control for Multi-Agent Interactions |
| 13-Apr-26 | Monday | Learning on Graphs |
GCBF+: A Neural Graph Control Barrier Function Framework
Deploying Ten Thousand Robots |
| PART 3: Student Presentations | |||
| 15-Apr-26 | Wednesday | Paper Presentation - I | |
| 20-Apr-26 | Monday | Paper Presentation - II | |
| 22-Apr-26 | Wednesday | Project Presentation | |
| 27-Apr-26 | Monday | Project Presentation | |
Other than the above two, you do not really need any prior background in robotics, control theory, or multi-agent systems, although it would enrich your learning experience if you do. Most importantly, you must show mathematical maturity, which means you should be able to read and understand technical research papers. Lectures in class will be fast-paced, so you should complete the assigned readings before coming to class to make sure you are able to follow along.
(There is a soft grading for class participation where extra credit or penalties may be awarded based on attendance, participating in discussions, and so on.)
Please note these guidelines: https://honor.virginia.edu/faculty-tas
Using generative AI tools such as ChatGPT to complete homeworks and exams is prohibited.
It is my goal to create a learning experience that is as accessible as possible. If you anticipate any issues related to the format, materials, or requirements of this course, please meet with me outside of class so we can explore potential options.
Students with disabilities may also wish to work with the Student Disability Access Center (SDAC) to discuss options for removing barriers in this course, including official accommodations.
We are fortunate to have an SDAC advisor, Courtney MacMasters, located in Engineering.
Email: cmacmasters@virginia.edu
For general questions, please visit the SDAC website.
If you have already been approved for accommodations through SDAC, please send me your accommodation letter and meet with me so we can develop an implementation plan together.
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Students requesting accommodation should email me as far in advance as possible.
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📞 434-924-3200
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