12 citations · 12 across the 5 of their papers we have counts for
5 papers
Triplet2Track: A Hierarchical System with Object-Centric Representations for Reliable Long-Horizon Manipulation
Jianxiang Liu, Gaojing Zhang, Chuan Wen +4
Ensuring reliability in uncertain environments remains difficult for long-horizon robotic manipulation. End-to-end VLA models are data-heavy and opaque, making diagnosis and verifi…
FAWAM: Force-Aware World Action Models for Closed-Loop Contact-Rich Manipulation
Haotian He, Zeyu Yan, Qipeng Liu +2
Force signals provide critical interaction cues for contact-rich robotic manipulation. However, existing methods mostly use force as an additional observation modality, without ful…
CLASH: Collision Learning via Augmented Sim-to-real Hybridization to Bridge the Reality Gap
Haotian He, Ning Guo, Siqi Shi +2
The sim-to-real gap, particularly in the inaccurate modeling of contact-rich dynamics like collisions, remains a primary obstacle to deploying robot policies trained in simulation.…
Look, Zoom, Understand: The Robotic Eyeball for Embodied Perception
Jiashu Yang, Yifan Han, Yucheng Xie +2
In embodied AI, visual perception should be active rather than passive: the system must decide where to look and at what scale to sense to acquire maximally informative data under…
Adaptive trajectory-constrained exploration strategy for deep reinforcement learning
Guojian Wang, Faguo Wu, Xiao Zhang +2
Deep reinforcement learning (DRL) faces significant challenges in addressing the hard-exploration problems in tasks with sparse or deceptive rewards and large state spaces. These c…