3 papers
cs.RO2026
ECo-MoE: Embodiment-Conditioned Mixture of Experts Increases the Evolvability of Robots
Yibin Wang, Muhan Li, Zihan Guo +1
In this paper, we introduce a model of evolution and learning in robots that co-optimizes a distribution of latent design vectors (genotypes) and a mixture of control experts (neur…
cs.RO2026
Creating manufacturable blueprints for coarse-grained virtual robots
Zihan Guo, Muhan Li, Shuzhe Zhang +1
Over the past three decades, countless embodied yet virtual agents have freely evolved inside computer simulations, but vanishingly few were realized as physical robots. This is be…
cs.RO2025
Tactile-based Object Retrieval From Granular Media
Jingxi Xu, Yinsen Jia, Dongxiao Yang +5
We introduce GEOTACT, the first robotic system capable of grasping and retrieving objects of potentially unknown shapes buried in a granular environment. While important in many ap…