16891: Multi-Robot Planning and Coordination

The course provides a graduate-level introduction to the field of multi-robot planning and coordination from both AI and robotics perspectives. Topics for the course include multi-robot cooperative task planning, multi-robot path/motion planning, learning for coordination, coordinating robots under uncertainty, etc. The course will particularly focus on state-of-the-art Multi-Agent Path Finding algorithms that can coordinate hundreds of robots with rigorous theoretical guarantees. Current applications for these technologies will be highlighted, such as mobile robot coordination for warehouses and drone swarm control.

Instructor: Prof. Jiaoyang Li

Term: Fall

Location: a

Time: a

Course Overview

Schedule

Week Date Topic Materials
1 Feb 5 Introduction to Data Science

Overview of the data science workflow and key concepts.

2 Feb 12 Data Collection and APIs

Methods for collecting data through APIs, web scraping, and databases.

3 Feb 19 Data Cleaning and Preprocessing

Techniques for handling missing values, outliers, and data transformation.

4 Feb 26 Exploratory Data Analysis

Descriptive statistics, visualization, and pattern discovery.

5 Mar 4 Statistical Analysis

Hypothesis testing, confidence intervals, and statistical inference.

6 Mar 11 Data Visualization

Principles and tools for effective data visualization.