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Shape-Changing Truss Robots

Intercepting Rogue Robots: An Algorithm for Capturing Multiple Evaders with Multiple Pursuers

A Distributed Algorithm for Mapping the Graphical Structure of Complex Environments with a Swarm of Robots

Active Motion-Based Communication for Robots with Monocular Vision

Decentralized Adaptive Control for Collaborative Manipulation

Wireframe Mapping for Resource-Constrained Robots

Bio-Inspired Non-Cooperative Multi-Robot Herding

Vision-Based Distributed Formation Control without an External Positioning System

Multi-Robot Manipulation without Communication

Welcome to the Multi-robot Systems Lab (MSL) at Stanford University. We study distributed algorithms for control, sensing, and learning in groups of robots and animals. Our current and past research topics include:

– Distributed controllers for the deployment of mobile sensor networks
– Agile coordinated multi-robot control
– Multi-robot control with adversaries and environmental hazards
– Persistent monitoring and persistent environmental sampling with robots
– Information based active sensing and estimation
– Multi-robot manipulation

You can learn more about our research on the Projects page, or read some of our Publications.

Recent News

June 5, 2020

Congratulations to Ola Shorinwa, Javier Yu, Trevor Halsted, Alex Koufos, and Mac Schwager for winning the 2020 IEEE ICRA Best Paper Award in Multi-Robot Systems!

May 5, 2020

Congratulations to Dr. Nathan Usevitch for successfully defending his PhD thesis!

March 18, 2020

Congratulations to Nathan Usevitch, whose paper was pubished in Science Robotics, and was covered by the Stanford Press Office, IEEE Spectrum, TechXplore, and others.