Robotics & Autonomous Systems Research
Leading the way on self-driving cars and autonomous drones that are safe and efficient.
Link Lab is studying autonomous science and system control regarding actions and interactions of man, machine, and environment. Our work is pushing the boundaries of machine learning and artificial intelligence applied to both individual systems and collectives. The goal of this work is to develop systems that are cognizant, task-able, adaptive, ethical, and understood across all aspects of objectives, time, resources, and security.
AUTONOMOUS SYSTEMS INTERACTING WITH HUMAN OPERATORS (L. Feng):
Human-in-the-Loop Mission Planning for Unmanned Aerial Vehicles (UAV)
Human-Interpretable Diagnostic Information for Robotics Planning
F1/10 AUTONOMOUS RACING (M. Behl)
Formation Control of Heterogeneous Unmanned Systems (L. Barnes)
MICRO AIR VEHICLE (H. Dong)
MICRO AERIAL VEHICLE STABILITY (D. Quinn)
Resilient Cyber-Physical Systems for Robotic Surgery (H. Alemzadeh)
F1/10 Undergraduate Course at UVA [Fall 2024]
Course title: F1/10 Autonomous Racing - Perception, Planning, & Control Course Instructor: Prof. Madhur Behl, Computer Science, University of Virginia Fall 2024 - CS 4501/SYS 4582 Course website: https://www.f1tenth.racing/ Students will work in teams to build, drive, and race 1/10th scale autonomous cars, while learning about the principles of perception, planning, and control. You will learn to use robot operating system (ROS), integrate various sensors (IMU, Cameras, LIDAR) on an embedded computer, and implement algorithms for localization, mapping, path planning, and control. The course culminates in a F1/10 ‘battle of algorithms’ race amongst the teams.
New interdisciplinary course on Principles of Modeling for Cyber-Physical Systems
Course Website: https://linklab-uva.github.io/modeling_cps/