TORL-VLA: Tactile Guided Online Reinforcement Learning for Contact-Rich Manipulation
Meituan（美团）；Beijing Institute of Technology（北京理工大学）；Beihang University（北京航空航天大学）；State Key Lab of Multimodal Artificial Intelligence Systems, Institute of Automation, CAS（中国科学院自动化研究所多模态人工智能系统国家重点实验室）；China University of Mining and Technology (Beijing)（中国矿业大学（北京））
Huaihang Zheng, Yi Yang, Kai Ma, Shenglin Xu, Tian Xie, Guozheng Li, Xiangyu Wang, Yiren Ma, Si Liu, Yinian Mao, Baoxu Liu
Vision-Language-Action (VLA) models have become a powerful framework for robotic manipulation, and recent studies have introduced tactile or force feedback into VLAs to address contact-rich tasks. However, these models are typically deployed as offline policies. When contact conditions shift from the training distribution, the policy cannot perform online adaptation, leading to problems such as inappropriate contact forces and inefficient retries. Therefore, we propose TORL-VLA, a tactile-guided online reinforcement learning framework that couples tactile feedback with policy refinement for contact-rich manipulation. Our method introduces a tactile-derived wrench-aware VLA to predict reference actions and future wrench sequences, while a lightweight online RL module is used to refine the reference actions. To stabilize learning from mixed exploratory policy-generated and human-intervention data, we introduce an intervention-censored critic that prevents post-intervention success from being wrongly credited to policy-generated actions preceding intervention. Real-robot experiments on long-horizon contact-rich tasks, including latch manipulation, coffee-cup placement, and egg handling, show that TORL-VLA improves success rates at both subtask and full-task levels, as well as time-bounded execution efficiency over strong baselines. Project page: https://torl-vla.github.io/
TaF-VLA: Tactile-Force Alignment in Vision-Language-Action Models for Force-aware Manipulation
Beihang University（北航大学）；ShanghaiTech University（上海科技大学）；Beijing Institute for General Artificial Intelligence（北京一般人工智能研究院）；The University of Hong Kong（香港大学）
TacVLA: Contact-Aware Tactile Fusion for Robust Vision-Language-Action Manipulation
Human-Robot Interfaces and Interaction Lab, Istituto Italiano di Tecnologia（人机交互实验室，意大利理工学院）；Ph.D. program of national interest in Robotics and Intelligent Machines (DRIM) and Università di Genova（机器人与智能机器国家级博士项目（DRIM）和热那亚大学）；Edwardson School of Industrial Engineering, Purdue University（工业工程学院，普渡大学）
UniTacVLA: Unified Tactile Understanding and Prediction in Vision Language Action Models
Harbin Institute of Technology（哈尔滨工业大学）；Great Bay University（大湾区大学）；Shanghai Jiao Tong University（上海交通大学）；Fudan University（复旦大学）；Nanjing University（南京大学）；Daimon Robotics
TacCoRL: Integrating Tactile Feedback into VLA via Simulation
University of California, Los Angeles（加利福尼亚大学洛杉矶分校）；University of California, San Diego（加利福尼亚大学圣迭戈分校）；University of Electronic Science and Technology of China（电子科技大学）；Peking University（北京大学）；University of Utah（犹他大学）
Feeling the Unexpected: ResTacVLA for Contact-Rich Manipulation via Residual Tactile Representation
School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；Zhongguancun Academy（中关村科学城）；Dexmal（德克斯马尔）
UniVTAC: A Unified Simulation Platform for Visuo-Tactile Manipulation Data Generation, Learning, and Benchmarking
ScaleLab, Shanghai Jiao Tong University（上海交通大学ScaleLab）；D-Robotics；ViTai Robotics；The University of Hong Kong（香港大学）；Nanjing University（南京大学）；Shenzhen University（深圳大学）；Wuhan University（武汉大学）；Fudan University（复旦大学）；Tsinghua University（清华大学）
TactileReflex: Noise-Statistics-Driven Vision-Tactile Reflex Control for Force-Sensitive Manipulation
Thrust of Robotics and Autonomous Systems, The Hong Kong University of Science and Technology (Guangzhou)（机器人与自主系统研究所，香港科学与技术大学（广州））；School of Mechanical Engineering, Shanghai Jiao Tong University（上海交通大学机械工程学院）
Representation-Aligned Tactile Grounding for Contact-Rich Robotic Manipulation
Shanghai Key Lab of Intelligent Information Processing, College of Computer Science and Artificial Intelligence, Fudan University（复旦大学计算机科学与人工智能学院智能信息处理上海市重点实验室）；College of Intelligent Robotics and Advanced Manufacturing, Fudan University（复旦大学智能机器人与先进制造学院）；Lenovo CTO Organization（联想首席技术官组织）；Nanyang Technological University（南洋理工大学）；TeleAl, China Telecom（中国电信天翼人工智能公司）
OpenViTac: Learning and Benchmarking Visuo-Tactile Policies in a Unified Sim-and-Real Framework
Fudan University（复旦大学）；Shanghai Key Laboratory of Multimodal Embodied AI（上海多模态具身智能重点实验室）；Hefei University of Technology（合肥工业大学）；National University of Singapore（新加坡国立大学）；Neote AI；China Unicom（中国联通）
VTLA: Vision-Tactile-Language-Action Model with Preference Learning for Insertion Manipulation
State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences（多模态人工智能系统国家重点实验室，自动化研究所，中国科学院）；Samsung R&D Institute China–Beijing（三星中国北京研发中心）；Beijing Academy of Artificial Intelligence（北京人工智能研究院）
Towards Human-Like Manipulation through RL-Augmented Teleoperation and Mixture-of-Dexterous-Experts VLA
Shanghai Jiao Tong University（上海交通大学）；Sharpa；Shanghai AI Lab（上海人工智能实验室）；Zhongguancun Academy（中关村学院）；National University of Singapore（新加坡国立大学）；Shanghai Innovation Institute（上海创新研究院）
MLA: A Multisensory Language-Action Model for Multimodal Understanding and Forecasting in Robotic Manipulation
State Key Laboratory of Multimedia Information Processing, School of Computer Science, Peking University（多媒体信息处理国家重点实验室，计算机科学学院，北京大学）；Beijing Innovation Center of Humanoid Robotics (X-Humanoid)（北京类人机器人创新中心（X-Humanoid））；The Chinese University of Hong Kong (CUHK)（香港中文大学（CUHK））
