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.

Latest papers

1,699 papers341 papers in the last four weeks, up 29% on the four weeks before. 2.0% of all new papers.

StellaVLA: In-Context Structured Demonstration for Generalizable Vision-Language-Action Models
Aug 12, 2026Siyu Xu, Yunke Wang, Zijian Wang +6Reasoning for VLA Models Continual Learning for VLA Models
StellarEdge AI Technical Team
Keep the Future, Drop the Rollout: RIFT for World Action Models
Aug 12, 2026Chushan Zhang, Jinguang Tong, Xuesong Li +2Efficient VLA Model Inference Efficient Inference for World Action Models
Australian National University
Aerial Layouting: Design and Control of a Compliant and Actuated End-Effector for Precise In-flight Marking on Ceilings
Aug 11, 2026Christian Lanegger, Marco Ruggia, Marco Tognon +2Robotic Construction Robotic Manipulation
Autonomous Systems Lab, ETH Zurich, Switzerland
Flex- $π$ : A Multi-Stream World-Action Model with Compute Flexibility
Aug 11, 2026Ge Yan, Jinghao Liu, Yuzhi Fan +4World Models World Model-Based Planning
University of Washington · Allen Institute for AI
StageWAM: Joint-Embedding Stage Prediction for World-Action Models in Robot Manipulation
Aug 11, 2026Xiao Liu, Yuguang Yang, Xi Wang +6World Models for Robotics Joint-Embedding Predictive Architecture
Institute for AI Industry Research (AIR), Tsinghua University · School of Electronic Information Engineering, Beihang University · AIR Wuxi Innovation Center, Tsinghua University +3
TCAM for Autonomous Deformable Manipulation: The RMC2 Champion System for WBCD 2026 Track 4
Aug 11, 2026Guangrui Shen, Zhili He, Shigang Wang +2Deformable Object Manipulation Robotic Manipulation
TermiTech, Shenzhen, China
FACT: Failure-Aware Causal Training for World-Action Models
Aug 10, 2026Quanquan Peng, Yutong Liang, Rui Yan +2Causal World Models Action-Conditioned World Models
University of California San Diego
RoboSeg: Online Part-Level Semantic Reconstruction for Robotic Manipulation via a Single Eye-in-Hand Camera
Aug 10, 2026Zhaochen Lan, Mengxiang LinRobotic Grasping 3D Semantic Mapping
School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China
Efficient Real-World Online Reinforcement Learning for Robot Manipulation via Centralized Training and Critic Decomposition
Aug 10, 2026Changhao Li, Yifang Zhang, Heng Zhang +6Reinforcement Learning Robotic RL
HHCM, Istituto Italiano di Tecnologia, Genoa, Italy · DIBRIS, University of Genova, Genova, Italy · Human-Robot Interfaces and Interaction Lab, Istituto Italiano di Tecnologia, Genova, Italy +1
TAMS: Task-Aware Multi-View Adaptive Streaming for Wireless Telerobotic Manipulation
Aug 10, 2026Zexin Deng, Zhenhui Yuan, Lu Tian +2Robot Teleoperation Robotic Manipulation
School of Engineering University of Warwick Coventry, United Kingdom · Pengcheng Laboratory & Southern Univ. of Sci. & Tech. Shenzhen, China
Robotic Fabric Alignment System for Sewing Using Global Local Weighted ICP
Aug 10, 2026Wenbo Dong, Dipankar Bhattacharya Member, Kai Tang +5Object Pose Estimation Robotic Manipulation
JC STEM Lab of Robotics for Soft Materials, Department of Electrical and Computer Engineering, Faculty of Engineering, The University of Hong Kong, Hong Kong SAR, China · Dyson School of Design Engineering, Imperial College London, London, United Kingdom · Unprecedented-scale Data Analytics Center, Tohoku University, Sendai 980-0845, Japan +4
Skills in Weights, Memory in Code: Hybrid Learning for Memory-Dependent Robot Manipulation
Aug 10, 2026Yunhao Zhao, Zhenyang Ni, Haoyang Chen +2Long-Horizon Robotic Manipulation Robot Skill Learning
Northwestern University · University of Minnesota · Stanford University
JEPA-WAM: Learning Vision-Language-Action Policies with Joint-Embedding World Modeling
Aug 10, 2026Yihan Lin, Jiawei He, Shifeng Bao +6Joint-Embedding Predictive Architecture Robotic Manipulation
School of Information, Renmin University of China, Beijing, China · XYZ Embodied AI, Beijing, China · Key Laboratory of Data Engineering and Knowledge Engineering, Beijing, China +3
SAFE-CHEM: Uncertainty-Aware Policy Switching for Robust Robotic Chemistry
Aug 10, 2026Laura Jones, Shazil Shahzad, Ayesha Sana +1Robotic Control Robot Safety
School of Computer Science & Informatics, University of Liverpool, UK. · Department of Chemistry, University of Liverpool, UK.
SpeedTuning: Speeding Up Policy Execution with Lightweight Reinforcement Learning
Aug 10, 2026David D. Yuan, Tony Z. Zhao, Kaylee Burns +1Robot Policy Learning Robot Skill Learning
Stanford University
PEEL: Parallel Extraction for Long-Horizon Disassembly Planning via Scale-Invariant Sampling
Aug 9, 2026Servet B. Bayraktar, Andreas Orthey, Zachary Kingston +1Long-Horizon Robotic Manipulation Robotic Manipulation
TEMPO: Semantic-Action Decoupled RL Post-Training for Vision-Language-Action Models
Aug 7, 2026Ziheng Liu, Quantao YangRobotic Manipulation Vision-Language-Action Models
School of Computer Science and Technology, Zhejiang Gongshang University, Hangzhou 310018, China. · Department of Robotics, Perception, and Learning, KTH Royal Institute of Technology, Sweden.
Representation Handoffs for OpenArm-Based Laboratory Mobile Manipulation
Aug 7, 2026Yang Shen, Chonghao Cheng, Ziyi Zhao +6Language-Conditioned Robot Manipulation Mobile Manipulation
University of Technology Sydney · Southern University of Science and Technology
C2Dex: Contact-Consistent Reconstruction and Retargeting for Dexterous Manipulation from Monocular Video
Aug 7, 2026Jie Ren, Zhehao Jiang, Yinhong Yang +9Contact-Rich Robotic Manipulation 3D Reconstruction
1Nanjing University, Nanjing, China. · 2China Mobile Research Institute, Beijing, China.
Real-time Whole-Body Motion Planning for Mobile Manipulators Carrying Arbitrarily Shaped Payloads via Kinematically-Coupled SVSDF
Aug 7, 2026Yisheng Li, Longji Yin, Tingrui Zhang +6Signed Distance Functions Mobile Manipulation
Department of Mechanical Engineering, University of Hong Kong · Institute for Interdisciplinary Information Sciences, Tsinghua University
Decoupling Intention from Trajectory: A Representational Deduction Framework for World Action Models
Aug 7, 2026Xiangkai Ma, Yue Ma, Junjie Wang +6Robot Motion Generation Robotic Manipulation
1NJU · 2HKUST · 3CUHK-SZ +4
GWM-VLA: Geometry-Aware Latent World Modeling for Vision-Language-Action Learning
Aug 7, 2026Yanping Zhao, Hang Yu, Yiwei Wang +8World Model Learning Robotic Manipulation
Tongji University
DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation
Aug 6, 2026Junfeng Li, Junjie He, Zhide Zhong +12Cross-Embodiment Robot Learning Robotics
1The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China · 2COCO Matrix, Shanghai, China
GeniWorld: A Generalizable Interactive World Model for Robotic Manipulation via Visual Actions
Aug 6, 2026Chenghao Gu, Hanyang Yu, Jingbo Zhang +7Action-Conditioned World Models Robotic Policy Evaluation
Shenzhen International Graduate School, Tsinghua University · Tencent Robotics X · The Hong Kong University of Science and Technology +1
Coordinated Multi-Robot Disassembly for Makespan Optimization of Large-Scale Assemblies
Aug 6, 2026Niklas Hargus, Andreas Orthey, Marc ToussaintMulti-Robot Motion Planning Multi-Robot Systems
Technical University of Berlin, Germany · Robotics Institute Germany (RIG)
In-Context VLA: Endowing Vision-Language-Action Models with Language via In-Context Post-Training and Agentic Tool Use
Aug 6, 2026Jiarui Yang, Wen Huang, Jiale Zhang +2Reasoning for VLA Models ICL for Robotics
Nankai University · Tsinghua University · Swiss Federal Institute of Technology in Lausanne (EPFL)
LIRA: Local Cross-Layer Information Routing for Vision-Language-Action Decoding
Aug 6, 2026Zhewei Zhang, Puyue Wang, Guanren Qiao +10Robotic Manipulation Vision-Language-Action Models
World-to-Wrist: Task-Conditioned Future Wrist Modeling for Fine-Grained Robot Manipulation
Aug 5, 2026Yuhao Pan, Haosong Peng, Zhengshen Zhang +8Language-Conditioned Robot Manipulation Contact-Rich Robotic Manipulation
1The Hong Kong University of Science and Technology · 2National University of Singapore · 3Nanyang Technological University +4
BridgeVLA++: A Data-Efficient, Generalizable, and Memory-Augmented Vision-Language-Action Framework for 3D Manipulation
Aug 5, 2026Peiyan Li, Yuze Zhu, Yixiang Chen +10Memory-Augmented VLMs Generalization in Robotic Manipulation
New Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, Beijing, China · School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China · FiveAges, Beijing, China +1
DreamWAM: Beyond RGB Future Prediction for World Action Models
Aug 5, 2026Shanglin Yuan, Weiheng Zhao, Xin Shi +6World Model Learning Action-Conditioned World Models
Huazhong University of Science and Technology · D-Robotics · Wuhan University +1

Aug 12, 2026J/K move · Enter open · S save

StellaVLA: In-Context Structured Demonstration for Generalizable Vision-Language-Action Models

Siyu Xu, Yunke Wang, Zijian Wang, Dihao Zhu+5

StellarEdge AI Technical Team

Reasoning for VLA Models Continual Learning for VLA Models Robotic Manipulation Instruction Generalization in VLA Models Robustness of VLA Models Vision-Language-Action Models+3

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Vision-Language-Action (VLA) models can follow instructions and manipulate objects, but their performance often collapses out of distribution (OOD), when the scene, viewpoint, or object differs from training. Adapting to each new situation typically requires collecting more data and fine-tuning. We present StellaVLA, a framework that instead adapts at test time by conditioning on a single retrieved demonstration. The key idea is to move beyond imitating what an expert did and instead convey why: an automated offline pipeline converts each raw trajectory into a structured demonstration, e.g., a task plan, sub-goal descriptions, and verbalized 3D motion, at zero human-annotation cost. Provided as in-context guidance, this structured demonstration lets the policy reason about the task rather than mimic a pixel trajectory, which also makes it transferable across embodiments (real-robot, human-hand, or XR demonstrations). A parallel dual-training design internalizes this reasoning during training through a joint action-and-language objective, while inference uses the action expert alone, preserving real-time, high-frequency control with no added latency. On the VLA-Arena leaderboard(Aug 1, 2026), StellaVLA ranks first with an overall score of 0.63, versus 0.44 and 0.22 for the strong prior models (

π_{0.5}

and LingBot-VLA), and it further leads on LIBERO with 98.8% average success rate and LIBERO-Plus with 85.1% success rate. Our real-robot benchmark demonstrates that StellaVLA can use both human/robot demos and human-to-robot (XR) demos as in-context structured demonstration to help VLA model adapt to OOD tasks.