8 papers
DASH Robot: Minimalistic Design and Optimal Aerial-Terrestrial Locomotion via Contact-Implicit Control
Ryan Gomes Paiva, Conrad Ho, Jiarong Kang +3
We present a novel and minimalistic design of an aerial-terrestrial robot DASH: Ducted Aerial Spring Hopper. The goal is to enable both aerial and ground locomotion capabilities on…
PRIME: Physically-consistent Robotic Inertial and Motion Estimation for Legged and Humanoid Robots
Jiarong Kang, Kunzhao Ren, Tao Pang +1
Humanoid and legged robots interact with the environment through intermittent contacts, making accurate motion estimation fundamentally dependent on reasoning about contact dynamic…
Simultaneous Calibration of Noise Covariance and Kinematics for State Estimation of Legged Robots via Bi-level Optimization
Denglin Cheng, Jiarong Kang, Xiaobin Xiong
Accurate state estimation is critical for legged and aerial robots operating in dynamic, uncertain environments. A key challenge lies in specifying process and measurement noise co…
Articulated-Body Dynamics Network: Dynamics-Grounded Prior for Robot Learning
Sangwoo Shin, Kunzhao Ren, Xiaobin Xiong +1
Recent work in reinforcement learning has shown that incorporating structural priors for articulated robots, such as link connectivity, into policy networks improves learning effic…
Efficient and Versatile Quadrupedal Skating: Optimal Co-design via Reinforcement Learning and Bayesian Optimization
Hanwen Wang, Zhenlong Fang, Josiah Hanna +1
In this paper, we present a hardware-control co-design approach that enables efficient and versatile roller skating on quadrupedal robots equipped with passive wheels. Passive-whee…
SPARK: Skeleton-Parameter Aligned Retargeting on Humanoid Robots with Kinodynamic Trajectory Optimization
Hanwen Wang, Qiayuan Liao, Bike Zhang +3
Human motion provides rich priors for training general-purpose humanoid control policies, but raw demonstrations are often incompatible with a robot's kinematics and dynamics, limi…