From the 1 of 10 linked papers with an AI index.
10 papers
TAC-LOCO: Unified Whole-Body Control for Quadrupedal TACtile-Informed LOCO-Manipulation
Muqun Hu, Yuhao Zhou, Kabir Ray Malik +4
The paper introduces TAC-LOCO, a reinforcement learning framework that integrates tactile sensor data with proprioception to enable unified whole-body control of a quadrupedal robo…
Learning Tactile-Aware Quadrupedal Loco-Manipulation Policies
Pokuang Zhou, Yuhao Zhou, Quan Khanh Luu +7
Quadrupedal loco-manipulation is commonly built on visual perception and proprioception. Yet reliable contact-rich manipulation remains difficult: vision and proprioception alone c…
Imagining the Sense of Touch: Touch-Informed Manipulation via Imagined Tactile Representations
Zhiyuan Zhang, Adeesh Desai, Jyun-Chi Hu +7
Tactile sensing can substantially improve contact-rich robotic manipulation, yet its practical deployment remains limited by the fragility, calibration requirements, and maintenanc…
StemVLA:An Open-Source Vision-Language-Action Model with Future 3D Spatial Geometry Knowledge and 4D Historical Representation
Jiasong Xiao, Yutao She, Kai Li +2
Vision-language-action (VLA) models integrate visual observations and language instructions to predict robot actions, demonstrating promising generalization in manipulation tasks.…
ContactWorld: What Matters in Vision-Tactile World Models for Contact-Rich Manipulation
Zhiyuan Zhang, Pokuang Zhou, Kaidi Zhang +6
Contact-rich manipulation requires world models to reason over complex contact dynamics from multimodal sensory observations. However, it remains unclear which representation prope…
Learning When to See and When to Feel: Adaptive Vision-Torque Fusion for Contact-Aware Manipulation
Jiuzhou Lei, Chang Liu, Yu She +2
Vision-based policies have achieved a good performance in robotic manipulation due to the accessibility and richness of visual observations. However, purely visual sensing becomes…