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About Us
The Agile Robot Control and Design (ARCaD) Lab aims to advance the dynamic capabilities in legged robots, through devising innovative control algorithms and hardware. Our research goal is to apply optimal control, mechatronics integration and reinforcement learning to achieve agile motions on hardware platforms. By bridging the gap between theoretical foundations and practical implementations, we strive to push the boundaries of legged robot agility and versatility.
An excellent starting point to learn about our research is our YouTube Channel
Recent Projects
We introduce a kinodynamic model predictive control (MPC) framework that exploits unidirectional parallel springs (UPS) to improve the energy efficiency of dynamic legged robots. Preliminary hardware experiments show a 14.8% reduction in energy consumption.
Contact Sensing via Joint Torque Sensors and a Force/Torque Sensor for Legged Robots
We propose a generalized momentum-based observer framework for detecting and localizing contact with data from (a) a hip-mounted force-torque (FT) sensor and (b) distributed low-cost strain-gauge-based joint torque sensors.
News
12/2025: Congratulations to Yue for passing the Comprehensive Qualifying Exam (CQE)!
08/2025: ARCAD Lab has received research grant from the Schaeffler Group
07/2025: Our paper "Contact Sensing via Joint Torque Sensors and a Force/Torque Sensor for Legged Robots " has been accepted to CASE 2025.
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