Robotic Manipulation

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Robotic manipulation studies how machines use sensing and motion to change objects and environments, from picking and assembly to tool use and handling deformable materials. Approaches combine geometric planning and force or impedance control with imitation learning, reinforcement learning, diffusion policies, and vision-language-action models; world models, memory, tactile feedback, and human-video demonstrations are also used. Methods are tested in simulation and on real robots using suites such as LIBERO, RoboTwin, ManiSkill, and RLBench, across clutter, bimanual coordination, mobile manipulation, and precision contact tasks. A central challenge is turning benchmark performance into safe, reliable long-horizon behavior across new objects, cameras, robot bodies, and real-world dynamics, while limiting data collection and inference costs.

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1,704 papers341 papers in the last four weeks, up 29% on the four weeks before. 2.0% of all new papers.

Zero-WAM: In-Context World-Action Modeling from Human Videos for Open-Ended Task Generalization
Aug 26, 2026Jiaming Zhou, Qihang Zhang, Gangwei Xu +9Zero-Shot Robotic Manipulation Generalization in Robotic Manipulation
Robbyant · HKUST (GZ) · HKUST
One Policy, Many Embodiments: Unified Camera-Centric Action Geometry Pre-training for Heterogeneous Embodied Manipulation
Aug 26, 2026Xiaomi Embodied Intelligence Team, University of Macau, : +21Robot Learning Cross-Embodiment Robot Learning
Xiaomi Embodied Intelligence Team · University of Macau
Low-Resolution Perception for Robotic Packing
Aug 26, 2026Giuseppe Fabio Preziosa, Federico Vignoni, Chiara Castellano +3Robotic Perception Robotic Manipulation
Politecnico di Milano, Piazza Leonardo da Vinci, 32. Milano (Italy).
GaussianDream++: Efficient 3D Gaussian World Modeling for Robotic Manipulation
Aug 26, 2026Yuqing Jiang, Zijian Zhang, Weitao Zhou +8World Models for Robotics Robotic Manipulation
University of Chinese Academy of Sciences · Institute of Automation, Chinese Academy of Sciences · Tuojing Intelligence +7
A Taxonomy of Construction Task Activities for Robot Workers
Aug 26, 2026Sadman Sakib, Zhangyi Peng, Yujie Pang +2Robotic Construction Robotic Manipulation
The authors are with the Nhu Department of Electrical Engineering and Computer Science, University of California-Irvine, Irvine, CA, USA · The authors contributed during the UCInspire program · The author is with the Department of Civil and Environmental Engineering, University of California-Irvine, Irvine, CA, USA
V-Link: Recovering Lost Visual Representations in Action DiT for Vision-Language-Action Models
Aug 26, 2026Yehao Lu, Jiarui Yang, Yuning Su +10Spatial Grounding for VLA Models Vision-Language-Action Models
Zhejiang University · AGIBOT · The Hong Kong University of Science and Technology (Guangzhou) +1
Sequential Object Placement Optimization with Convex Decomposition
Aug 25, 2026Yuezhe Zhang, Xiangyu Lyu, Sohan Rudra +2Combinatorial Optimization Robotic Manipulation
Interactive Robot Perception & Learning, Technical Univsersity of Darmstadt, Germany · Intelligent Autonomous Systems, Technical Univsersity of Darmstadt, Germany · Robotics and Semantic Systems, Lund University, Sweden +1
Latent Action as Intention Enables Efficient Future Imagination for World Action Models
Aug 25, 2026Xiang Li, Yupeng Zheng, Songen Gu +11Latent Action Learning World Models for Robotics
1CollegeAI, THU · 2AIR, THU · 4TARS Robotics +6
Gripper-aware Vision Language Action Models
Aug 25, 2026Hanyi Zhang, Zihong Luo, Tianyu Li +16Vision-Language-Action Models VLMs for Robotics
University of Liverpool, UK · Mohamed bin Zayed University of Artificial Intelligence, UAE · Indian Institute of Science, India +5
Fiber Optic Sensing Glove for High Performance Dexterous Manipulation Capture
Aug 25, 2026J. D. Peiffer, Taylor Niehues, Li Guan +23D Hand Pose Estimation Wearable Sensing
Meta, Redmond, Washington, 98052, USA · Department of Biomedical Engineering, Northwestern University, Evanston, Illinois, 60208, USA · Work done at Meta
A Durable Vision-Based Tactile Fingertip for Robotic Manipulation
Aug 25, 2026F. Richard Cottrell, Megha H. Tippur, Edward H. AdelsonTactile Sensing Robotic Tactile Sensing
MIT CSAIL
Coverage Planning for Robotic Tooth Preparation in Densely Constrained Environments
Aug 25, 2026Yunwen Li, Chen Chen, Xiangjie Yan +4Robotics Coverage Path Planning
Department of Automation, Tsinghua University, China · Department of Mechanical and Process Engineering, ETH Zürich, Switzerland · Tsingscribe Medical Ltd., China +1
Trajectory-Level Continuous Action Representation for Robotic Manipulation
Aug 25, 2026Tong Yang, Jingkai Jia, Yuecheng Xu +3Trajectory Representation Learning Robotic Manipulation
Shanghai Key Lab of Intelligent Information Processing, College of Computer Science and Artificial Intelligence, Fudan University, Shanghai, China · TeleAI, China Telecom, Shanghai, China · College of Intelligent Robotics and Advanced Manufacturing, Fudan University, Shanghai, China
GlanceWAM: Sparse Test-Time Imagination for World-Action Models
Aug 25, 2026Linhan Wang, Zijian An, Mingyuan Zhang +8Efficient Inference for World Action Models Robotic Manipulation
Virginia Tech · Drexel University · Northeastern University +1
Act with Intent: Distilling Behavior Intent for Vision-Language-Action Models
Aug 24, 2026Sangoh Lee, Sangwoo Mo, Wook-Shin HanVLA Model Training Vision-Language-Action Models
GSAI, POSTECH · IME, POSTECH
Pointing-VLA: Typed Spatial Grounding Interfaces for Vision-Language-Action Manipulation
Aug 24, 2026Xiwen Chen, Zelin Li, Zhiruo Zhou +3Spatial Grounding for VLA Models Vision-Language-Action Models
SIGS, Tsinghua University, China · Shanghai Jiao Tong University, China · Wuhan University of Technology, China +2
InstructMove: A Text-Indispensable Benchmark for Instruction-Following Manipulation
Aug 24, 2026Mengao Zhao, Ziang Li, Chaodong Huang +15Robot Manipulation Benchmarks Language-Conditioned Robot Manipulation
Horizon Robotics · Southeast University · Huazhong University of Science and Technology +1
Reproducible Vision-Guided 6-DoF Robotic Manipulator with a Mixed Stepper-Driver Architecture and Browser-Native Control
Aug 24, 2026Lasan Perera, Deneth Priyadarshana, Dulana Pitiwaduge +2Robotics Robotic Manipulation
Department of Electronic and Telecommunication Engineering, University of Moratuwa, Moratuwa, Sri Lanka
EMPIRE: Explicit Manipulation Planning as a Learnable Intermediate Representation for Egocentric Hand-Motion Forecasting
Aug 23, 2026Wen Wang, Ruibing Hou, Hong Chang +2Human Motion Prediction Robotic Manipulation
Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, China · University of Chinese Academy of Sciences, China
WAM-OPD: Joint Video-Action Supervision for World Action Model Post-Training with On-Policy Distillation
Aug 23, 2026Liuhaichen Yang, Zhengyang Zhong, Hanshang Zhu +13World Action Models Action-Conditioned World Models
University College London · Shanghai Jiao Tong University · The University of Manchester +3
Beyond Instance Slots: Semantically Rich World Models for Physical Interaction Planning
Aug 23, 2026Juntao Cheng, Jingkai Wang, Yijun Shen +2World Model-Based Planning Action-Conditioned World Models
Beijing Academy of Artificial Intelligence (BAAI) · Shanghai Jiao Tong University
DELE-w0.5: Inferring Action from Future Latent State for Robotic Manipulation
Aug 22, 2026Fenghao Lei, Zhixiong Huang, Long Yang +5Long-Horizon Robotic Manipulation World Models for Robotics
DeepLeap Research, Shenzhen, China
CIDER: Continual Interactive Distillation for Embodied Reinforcement Learning
Aug 22, 2026Houlin Li, Minghui Xu, Guo Xu +8Continual Robot Learning Continual RL
AgiBot · Shanghai Jiao Tong University
Vision Guided Target Conditioned Control for Autonomous Excavation
Aug 22, 2026Shuai Zhao, Ji-An Pan, Junwei Li +5Robotic Excavation Goal-Conditioned Robotic Manipulation
Liaoning University, Shenyang, China · Northeastern University, Shenyang, China · Tsinghua University, Beijing, China
GOLEM: Modular Humanoid Autonomy Towards Electric Vehicle Battery Disassembly
Aug 21, 2026Max Conway, William Xie, Allen Devaraj +14Modular Robotics Humanoid Robot Control
Department of Computer Science, University of Colorado Boulder, USA. · Department of Aerospace and Mechanical Engineering, University of Notre Dame, USA.
Beyond Imitation: Self-Improving Robot Policies via Off-Policy Q-Planning
Aug 21, 2026Varun Giridhar, Anant Khandelwal, Jeremy A. Collins +2Robot Policy Adaptation Robotic RL
Georgia Institute of Technology
PhysCaP: Grounding Code-as-Policy Agent with Physics-Informed Exploration
Aug 21, 2026Chen-Yu Lin, Jing-Wen Chen, Hsueh-En Chang +8Physical Reasoning Active Vision for Robot Manipulation
National Taiwan University · NVIDIA Research · National Yang Ming Chiao Tung University
Koala Gripper: Co-designing Robotic Grippers and Data-Capture Devices for Scaling Dexterous Manipulation Learning
Aug 20, 2026Amar Hajj-Ahmad, Zubin Kremer Guha, Tim Fofonoff +8Robotic Gripper Design Robotic Manipulation
* These authors contributed equally to this work.
RoMAN-Flow: Taming Autoregressive Normalizing Flows for Offline Reinforcement Learning in Robotic Manipulation
Aug 20, 2026Shaoxuan Wang, Guangting Zheng, Rui Huang +4Robotic RL Offline RL
University of Science and Technology of China · The Chinese University of Hong Kong
What Matters for Latent Actions in Robot Learning
Aug 20, 2026Xizhou Bu, Qingda Hu, Lei Zhou +13Latent Action Learning Robot Learning
College of Intelligent Robotics and Advanced Manufacturing, Fudan University, Shanghai, 200433, China · Xiaomi EV, Beijing, 100085, China · Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China +3

Aug 26, 2026J/K move · Enter open · S save

Zero-WAM: In-Context World-Action Modeling from Human Videos for Open-Ended Task Generalization

Jiaming Zhou, Qihang Zhang, Gangwei Xu, Cunxin Fan+8

Robbyant · HKUST (GZ) · HKUST

Zero-Shot Robotic Manipulation Generalization in Robotic Manipulation Robotic Manipulation ICL for Robotics

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Zero-shot cross-task generalization, where a policy must execute manipulation tasks never seen during training, remains a central challenge in robot learning. In large language models, a novel task can be performed simply by specifying it in the context, without any parameter update. This form of in-context learning (ICL) turns generalization into a problem of task specification. To achieve cross-task generalization, we bring this paradigm to robotic manipulation, and argue that the natural task specification for manipulation is a human video: unlike language, it provides rich visual cues about the intended task evolution. We present Zero-WAM, a causal video-action model that executes unseen tasks by following in-context human video guidance. To address the scarcity of task-rich paired human-robot data, we propose an automatic pipeline that converts task-sampled robot trajectories into semantically matched human videos, yielding HumanGen, a dataset of 74.2K human-robot ICL pairs across 8.6K tasks. For model training, we further introduce an in-context future chunk prediction (IFP) objective that suppresses shortcuts learned from seen tasks and forces the policy to draw task information from the video prompt. On seven unseen tasks in RoboTwin 2.0 simulation, Zero-WAM achieves a 47.0% average success rate, an absolute improvement of 29.5 percentage points over the strongest video-action baseline. In real-world evaluations, it follows human video guidance to generalize to unseen task configurations involving multi-object scenes, long-horizon manipulation, and fine-grained insertion.