6 papers
Bayesian Optimization in Chemical Compound Sub-Spaces using Low-Dimensional Molecular Descriptors
Yun-Wen Mao, Roman V. Krems
Efficient optimization of molecules with targeted properties remains a significant challenge due to the vast size and discrete nature of chemical compound space. Conventional machi…
Direction Matters: Learning Force Direction Enables Sim-to-Real Contact-Rich Manipulation
Yifei Yang, Anzhe Chen, Zhenjie Zhu +6
Sim-to-real transfer for contact-rich manipulation remains challenging due to the inherent discrepancy in contact dynamics. While existing methods often rely on costly real-world d…
UnIRe: Unsupervised Instance Decomposition for Dynamic Urban Scene Reconstruction
Yunxuan Mao, Rong Xiong, Yue Wang +1
Reconstructing and decomposing dynamic urban scenes is crucial for autonomous driving, urban planning, and scene editing. However, existing methods fail to perform instance-aware d…
Efficient Alignment of Unconditioned Action Prior for Language-conditioned Pick and Place in Clutter
Kechun Xu, Xunlong Xia, Kaixuan Wang +6
We study the task of language-conditioned pick and place in clutter, where a robot should grasp a target object in open clutter and move it to a specified place. Some approaches le…
NGEL-SLAM: Neural Implicit Representation-based Global Consistent Low-Latency SLAM System
Yunxuan Mao, Xuan Yu, Kai Wang +3
Neural implicit representations have emerged as a promising solution for providing dense geometry in Simultaneous Localization and Mapping (SLAM). However, existing methods in this…
-DBA: Neural Implicit Dense Bundle Adjustment Enables Image-Only Driving Scene Reconstruction
Yunxuan Mao, Bingqi Shen, Yifei Yang +4
The joint optimization of the sensor trajectory and 3D map is a crucial characteristic of bundle adjustment (BA), essential for autonomous driving. This paper presents -DBA, a…