From the 1 of 19 linked papers with an AI index.
8 papers · 1 filter
ReTouch: Empowering Contact-Rich Dexterous Manipulation with Online-Refined Tactile Prediction
Shiqi Zhang, Xin Zhang, Yedong Shen +9
Fusing tactile signals has proven effective for contact-rich manipulation, enabling robots to perceive contact states and adapt to rapidly changing physical interactions. Yet effec…
TacWAM: Anchor-Guided World Action Model with Mechanics-Aware Tactile Prediction
Lei Jin, Yiding Ma, Xin Zhang +3
The paper introduces TacWAM, a mechanics-aware tactile world action model that predicts future tactile signals and uses them as supervision for training contact-rich robot manipula…
WorldScape Policy 2.0: Empowering Steerable World Action Modeling with Reasoning-Augmented Memory
Haisheng Su, Zongdai Liu, Xin Jin +13
World Action Models (WAMs) offer a promising paradigm for robotic manipulation by jointly modeling visual state transitions and robot actions. However, existing WAMs are constraine…
Worldscape-MoE: A Unified Mixture-of-Experts World Model for Scalable Heterogeneous Action Control
Jianjie Fang, Yongyan Xu, Ziyou Wang +13
World models are rapidly becoming a core infrastructure for embodied intelligence and interactive agents: they provide controllable simulators in which agents can perceive, act, fo…
WorldArena 2.0: Extending Embodied World Model Benchmarking on Modality, Functionality and Platform
Yu Shang, Yinzhou Tang, Yiding Ma +22
World models have emerged as a central paradigm for embodied intelligence, enabling agents to predict action-conditioned future and reason about environmental dynamics. However, ex…
WorldVLN: Autoregressive World Action Model for Aerial Vision-Language Navigation
Baining Zhao, Jiacheng Xu, Weicheng Feng +13
Aerial vision-language navigation (VLN) requires agents to follow natural-language instructions through closed-loop perception and action in 3D environments. We argue that aerial V…