49 citations · 50 across the 5 of their papers we have counts for
6 papers
M-ABD: Scalable, Efficient, and Robust Multi-Affine-Body Dynamics
Zhiyong He, Dewen Guo, Minghao Guo +6
Simulating large-scale articulated assemblies poses a significant challenge due to the numerical stiffness and geometric complexity of jointed structures. Conventional rigid body s…
Newton to Einstein: Axiom-Based Discovery via Game Design
Pingchuan Ma, Benjamin Tod Jones, Tsun-Hsuan Wang +4
This position paper argues that machine learning for scientific discovery should shift from inductive pattern recognition to axiom-based reasoning. We propose a game design framewo…
Fabrica: Dual-Arm Assembly of General Multi-Part Objects via Integrated Planning and Learning
Yunsheng Tian, Joshua Jacob, Yijiang Huang +10
Multi-part assembly poses significant challenges for robots to execute long-horizon, contact-rich manipulation with generalization across complex geometries. We present Fabrica, a…
AI-Enhanced Automatic Design of Efficient Underwater Gliders
Peter Yichen Chen, Pingchuan Ma, Niklas Hagemann +4
The development of novel autonomous underwater gliders has been hindered by limited shape diversity, primarily due to the reliance on traditional design tools that depend heavily o…
Learning Object Properties Using Robot Proprioception via Differentiable Robot-Object Interaction
Peter Yichen Chen, Chao Liu, Pingchuan Ma +5
Differentiable simulation has become a powerful tool for system identification. While prior work has focused on identifying robot properties using robot-specific data or object pro…
KAN 2.0: Kolmogorov-Arnold Networks Meet Science
Ziming Liu, Pingchuan Ma, Yixuan Wang +2
A major challenge of AI + Science lies in their inherent incompatibility: today's AI is primarily based on connectionism, while science depends on symbolism. To bridge the two worl…