Publications (14)
BodyGen: Advancing Towards Efficient Embodiment Co-Design
Haofei Lu, Zhe Wu, Junliang Xing +4
Embodiment co-design aims to optimize a robot's morphology and control policy simultaneously. While prior work has demonstrated its potential for generating environment-adaptive ro…
GoNet: An Approach-Constrained Generative Grasp Sampling Network
Zehang Weng, Haofei Lu, Jens Lundell +1
This work addresses the problem of learning approach-constrained data-driven grasp samplers. To this end, we propose GoNet: a generative grasp sampler that can constrain the grasp…
Dynamic Multi-View Scene Reconstruction Using Neural Implicit Surface
Decai Chen, Haofei Lu, Ingo Feldmann +2
Reconstructing general dynamic scenes is important for many computer vision and graphics applications. Recent works represent the dynamic scene with neural radiance fields for phot…
MoDex: A Diffusion Policy for Sequential Multi-Object Dexterous Grasping
Haofei Lu, Hongjia Liu, Yifei Dong +3
This work addresses sequentially grasping multiple objects with a single dexterous hand without releasing those already held. Most dexterous grasping methods commit all of the hand…
Enabling Robot Manipulation of Soft and Rigid Objects with Vision-based Tactile Sensors
Michael C. Welle, Martina Lippi, Haofei Lu +3
Endowing robots with tactile capabilities opens up new possibilities for their interaction with the environment, including the ability to handle fragile and/or soft objects. In thi…
DexDiffuser: Generating Dexterous Grasps with Diffusion Models
Zehang Weng, Haofei Lu, Danica Kragic +1
We introduce DexDiffuser, a novel dexterous grasping method that generates, evaluates, and refines grasps on partial object point clouds. DexDiffuser includes the conditional diffu…