33 citations · 33 across the 6 of their papers we have counts for
7 papers
SDC-GON: Singular Decomposition and Consistency-Regularized Green's Operator Networks for Solving Partial Differential Equations
Yingchao Huang, Xin Wang, Shanshan Yao +2
Green's function based operator approximation offers an efficient route for solving linear partial differential equations under varying boundary conditions and source terms. Once t…
Generative Evolutionary Design of Voxel-Based Soft Robots with Provable Optimality
Junru Song, Huan Xiao, Yang Yang +8
Voxel-based soft robots (VSRs) present a promising avenue for developing artificial organisms with lifelike intelligence. However, the vast design spaces and expensive evaluations…
Shaping the Evolutionary Dynamics of Robot Morphology via Adaptive Control Learning
Junru Song, Yang Yang, Yaqing Xu +5
Robot co-design via bi-level optimization couples within-lifetime controller learning for fitness evaluation with cross-generational morphological evolution. Prior work has establi…
JailWAM: Jailbreaking World Action Models in Robot Control
Hanqing Liu, Songping Wang, Jiahuan Long +9
World Action Models (WAMs) have emerged as a promising paradigm for robotic manipulation, enabling physical interaction across diverse tasks and environments. However, their abilit…
A physics-driven sensor placement optimization methodology for temperature field reconstruction
Xu Liu, Wen Yao, Wei Peng +3
Perceiving the global field from sparse sensors has been a grand challenge in the monitoring, analysis, and design of physical systems. In this context, sensor placement optimizati…
HeteroMorpheus: Universal Control Based on Morphological Heterogeneity Modeling
YiFan Hao, Yang Yang, Junru Song +4
In the field of robotic control, designing individual controllers for each robot leads to high computational costs. Universal control policies, applicable across diverse robot morp…
RBF-MGN:Solving spatiotemporal PDEs with Physics-informed Graph Neural Network
Zixue Xiang, Wei Peng, Wen Yao
Physics-informed neural networks (PINNs) have lately received significant attention as a representative deep learning-based technique for solving partial differential equations (PD…