10 papers
DeltaWorld: Physically Consistent Interactive World Simulators via Action-Conditioned Latent Increment Learning
Boyuan Hou, Xiaoge Cao, Chaofan Zhang +2
Interactive world simulators can provide scalable environments for robot planning, policy training, and evaluation by predicting action consequences while reducing reliance on repe…
HiTac-WAM: A Hierarchical Tactile World Action Model for Contact-Rich Robot Manipulation
Chao Xue, Chaofan Zhang, Wenxuan Ma +3
World action models jointly predict future visual observations and actions, whereas existing tactile-aware variants typically represent future touch as an image or latent stream wi…
TacPrint: A Wearable Fingertip Tactile Sensor for Human-to-Robot Contact Reproduction
Yongxi Liu, Chaofan Zhang, Xingyu Zhang +4
Human-centric data collection is emerging as a significant paradigm for robot skill acquisition, but seamlessly integrating low-cost, scalable tactile sensing systems that capture…
FeelWorld: Visuo-Tactile World Model for Hierarchical Contact Prediction and Planning
Wenxuan Ma, Chaofan Zhang, Chao Xue +4
Humans plan physical interactions by imagining the possible outcomes of candidate actions. However, existing visual world models primarily capture appearance dynamics while overloo…
FTP-1: A Generalist Foundation Tactile Policy Across Tactile Sensors for Contact-Rich Manipulation
Chengbo Yuan, Zicheng Zhang, Mingjie Zhou +14
Despite the success of vision-based generalist robotic policies, existing tactile-based policies remain tied to fixed embodiments and sensor setups. This is because tactile signals…
FG-CLTP: Fine-Grained Contrastive Language Tactile Pretraining for Robotic Manipulation
Wenxuan Ma, Chaofan Zhang, Yinghao Cai +3
Recent advancements in integrating tactile sensing into vision-language-action (VLA) models have demonstrated transformative potential for robotic perception. However, existing tac…
SpikingTac: A Miniaturized Neuromorphic Visuotactile Sensor for High-Precision Dynamic Tactile Imprint Tracking
Tianyu Jiang, Chaofan Zhang, Shaolin Zhang +2
High-speed event-driven tactile sensors are essential for achieving human-like dynamic manipulation, yet their integration is often limited by the bulkiness of standard event camer…
DexTac: Learning Contact-aware Visuotactile Policies via Hand-by-hand Teaching
Xingyu Zhang, Chaofan Zhang, Boyue Zhang +3
For contact-intensive tasks, the ability to generate policies that produce comprehensive tactile-aware motions is essential. However, existing data collection and skill learning sy…
VTLA: Vision-Tactile-Language-Action Model with Preference Learning for Insertion Manipulation
Chaofan Zhang, Peng Hao, Xiaoge Cao +3
While vision-language models have advanced significantly, their application in language-conditioned robotic manipulation is still underexplored, especially for contact-rich tasks t…
CLTP: Contrastive Language-Tactile Pre-training for 3D Contact Geometry Understanding
Wenxuan Ma, Xiaoge Cao, Yixiang Zhang +7
Recent advancements in integrating tactile sensing with vision-language models (VLMs) have demonstrated remarkable potential for robotic multimodal perception. However, existing ta…