Taking RoboRacer Off-Road: Learning Extreme Off-Road Mobility

Описание: We will cover two recent research thrusts from the RobotiXX lab in taking RoboRacer off-road: high-speed off-road navigation and wheeled mobility on vertically challenging terrain. For high-speed off-road navigation, we will introduce a sequential line of work with every work inspired by and built upon its prior work, ranging from inverse kinodynamics learning based on inertia and vision to forward kinodynamics to enable competence awareness. For wheeled mobility on vertically challenging terrain, we will introduce this new problem formulation and a recently developed ecosystem around this topic, from research infrastructure, kinodynamics modeling and planning, to off-road mobility learning. We will also share the latest research on combining these two thrusts, i.e., making high-speed vehicles safely fly over uneven terrain through in-air maneuvers.

Bio:
Xuesu Xiao is an Assistant Professor in the Department of Computer Science at George Mason University. Xuesu (Prof. XX) directs the RobotiXX lab, in which researchers (XX-Men and XX-Women) and robots (XX-Bots) work together at the intersection of motion planning and machine learning with a specific focus on developing highly capable and intelligent mobile robots that are robustly deployable in the real world with minimal human supervision. Xuesu’s work has been deployed in real-world robot field missions, including search and rescue effort in the Mexico City earthquake and the Greece refugee crisis, decommissioning effort in the Fukushima nuclear disaster, and multiple search and rescue exercises in the US. Xuesu’s research has been featured by The New York Times, InDro Robotics, Google AI Blog, Clearpath Robotics, IEEE Spectrum, US Army, Robotics Business Review, Tech Briefs, NSF Science Nation, WIRED, and KBTX-TV. Xuesu has been awarded George Mason University Presidential Award for Faculty Excellence in Research and College of Engineering and Computing 2025 Faculty Excellence Award for Research.