Synthetic Data Generation for Robotics

Follow this topic Ask about this topic

Momentum

40 papers in the last four weeks, up 567% on the four weeks before. 0.4% of all new papers.

Jul 13Week of Sep 28

Latest papers 196

All topics

IOI: Decoupling Kinematics and Physics for Interactive World Models
Jun 22, 2026Chengyu Bai, Peidong Jia, Tiecheng Guo +11Action-Conditioned Video Generation World Models for Robotics
1Beijing Innovation Center of Humanoid Robotics · 2Peking University
Humanoid-OmniOcc: Stereo-Based Full-View Occupancy Dataset for Embodied AI
Jun 22, 2026Xianda Guo, Bohao Zhang, Chenwei Huang +6Sim-to-Real Transfer Synthetic Data Generation for Robotics
School of Computer Science, Wuhan University · †Work was done during an internship at D-Robotics. · D-Robotics +2
HERCULES: An Open-Source Simulation Framework for Heterogeneous Multi-Robot SLAM, Collaborative Perception, and Exploration
Jun 22, 2026Sandilya Sai Garimella, Daniel Chase Butterfield, Sean Wilson +1Simultaneous Localization and Mapping Multi-Robot Systems
Georgia Institute of Technology, USA · Georgia Tech Research Institute, USA · Georgia Institute of Technology, Atlanta, GA, USA
The Power of Light: Improving Synthetic-to-Real Domain Adaptation through Physically-Based Indirect Illumination
Jun 21, 2026Hooman Tavakoli Ghinani, Tatjana Legler, Martin RuskowskiSynthetic-to-Real Domain Adaptation Synthetic Data Generation for Robotics
German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany · RPTU Kaiserslautern-Landau, Kaiserslautern, Germany
Scalable Multi-Task Data Generation via Reinforcement Learning for Language-Conditioned Bimanual Dexterous Manipulation
Jun 21, 2026Zechu Li, Yufeng Jin, Puze Liu +2RL for Robotics Dexterous Manipulation
Department of Computer Science, TU Darmstadt, Germany. · Honda Research Institute Europe GmbH, Offenbach, Germany. · DFKI, Research Department SAIROL, Darmstadt, Germany. +2
Reference-Free Assessment of Physical Consistency in World Model-based Video Generation
Jun 21, 2026Yun Oh, Sukmin YunPhysical Consistency in Video Generation Synthetic Data Generation for Robotics
Hanyang University ERICA
Wh0: Generative World Models as Scalable Sources of Egocentric Human Hand Manipulation Data
Jun 20, 2026Yangtao Chen, Zixuan Chen, Peiyang Wang +4HOI Generation Generalization in Robotic Manipulation
Shanghai Innovation Institute · Nanjing University · Shanghai Jiaotong University
DeformX: A Versatile Co-Simulation Framework for Deformable Linear Objects
Jun 20, 2026Yi Yang, Xiang Fei, Lehong Wang +5Robotics Simulation Sim-to-Real Transfer
The Robotics Institute, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213 USA. · School of Ocean and Civil Engineering, Shanghai Jiao Tong University, 800 Dongchuan Rd, Minhang District, Shanghai, China. · Zhiyuan College, Shanghai Jiao Tong University, 800 Dongchuan Rd, Minhang District, Shanghai, China. +2
Efficiently Linking Real Scenes with Synthetic Data Generation for AI-based Cognitive Robotics and Computer Vision Applications
Jun 18, 2026Paul Koch, Vivek Chavan, André Sers +4Synthetic-to-Real Domain Adaptation Synthetic Data Generation for Robotics
Fraunhofer IPK, Berlin, Germany. · TU Berlin, Germany
Pose6DAug: Physically Plausible Multi-view Object Swapping for Robot Data Augmentation
Jun 18, 2026Jonghoon Lee, Seong Hyeon Park, Byungwoo Jeon +2Multi-View Consistency Data Augmentation
1KAIST · 2Korea University · 3RLWRLD
One Demo is Worth a Thousand Trajectories: Action-View Augmentation for Visuomotor Policies
Jun 17, 2026Chuer Pan, Litian Liang, Dominik Bauer +4Data Augmentation Generalization in Robotic Manipulation
Stanford University · Columbia University · Toyota Research Institute
Do as I Do: Dexterous Manipulation Data from Everyday Human Videos
Jun 17, 2026Bhawna Paliwal, Haritheja Etukuru, William Liang +3Robotic Data Collection Cross-Embodiment Robot Learning
UC Berkeley
ROBOSHACKLES: A Safety Dataset for Human-Injury Prevention in Embodied Foundation Models
Jun 17, 2026Zhuowen Yin, Chongyang Liu, Wenzhang Yang +2Robot Foundation Models Synthetic Data Generation for Robotics
Institute of Al for Industries, Chinese Academy of Sciences, Nanjing, Jiangsu, China · University of Science and Technology of China, Hefei, Anhui, China
GASE: Gaussian Splatting-Based Automated System for Reconstructing Embodied-Simulation Environments
Jun 16, 2026Jiawei Zhang, Yiming Yan, Chao Liang +83D Gaussian Splatting 3D Reconstruction
AutoLab, SAI, Shanghai Jiao Tong University · AIM3 Lab, School of Information, Renmin University of China · Research Lab, Anyverse Dynamics
MagicSim: A Unified Infrastructure for Executable Embodied Interaction
Jun 16, 2026Haoran Lu, Songling Liu, Yue Chen +15Robotics Simulation Synthetic Data Generation for Robotics
1Northwestern University · 2Peking University · 4ShanghaiTech University +1
AnnotateAnything: Automatic Annotation of 3D Assets for Robot Manipulation
Jun 16, 2026Haoran Lu, Mutian Shen, Shuyang Yu +9Robotic Data Collection Robotics Simulation
Northwestern University · Peking University
EgoInfinity: A Web-Scale 4D Hand-Object Interaction Data Engine for Any-View Robot Retargeting and Video-to-Action Robot Learning
Jun 16, 2026Gaotian Wang, Kejia Ren, Andrew Morgan +4Robotic Data Collection Cross-Embodiment Robot Learning
Rice University · Robotics and AI Institute
JoyAI-Sim: A Simulation-Enabled Interconversion Toolchain for the Embodied Data Pyramid
Jun 15, 2026Peidong Liu, Yongce Liu, Songyan Guo +34Robotic Data Collection Robotics Simulation
Joy Future Academy, JD Group
SimWeaver: Zero-Shot RGB Sim-to-Real for Deformable Manipulation
Jun 13, 2026Wenkang Hu, Haoran Wang, Yitong Li +10Zero-Shot Robotic Manipulation Robot Skill Learning
1Shanghai Jiao Tong University · 2Horizon Robotics · 3Style3D Research
Kine2Go: Kinematic dataset for the Unitree Go2 robot with diverse gaits and motions
Jun 12, 2026Władysław Pałucki, Paweł Siwak, Krzysztof Ciebiera +1Robotic Data Collection Synthetic Data Generation for Robotics
University of Warsaw
LabVLA: Grounding Vision-Language-Action Models in Scientific Laboratories
Jun 11, 2026Baochang Ren, Xinjie Liu, Xi Chen +15AI for Science Robot Skill Learning
Zhejiang University · Shanghai AI Laboratory · Harbin Institute of Technology
EgoEngine: From Egocentric Human Videos to High-Fidelity Dexterous Robot Demonstrations
Jun 10, 2026Yangcen Liu, Shuo Cheng, Xinchen Yin +6Zero-Shot Robotic Manipulation Robot Skill Learning
Georgia Institute of Technology · Tsinghua University
Traceable Virtual Sea Trials in the Marine Robotics Unity Simulator for Manoeuvring Assessment of Unmanned Surface Vehicles
Jun 10, 2026Paria RezayanRobotics Simulation Mobile Robotics
School of Engineering and Built Environment, Sheffield Hallam University, UK
From Simulation to the Real-World: An In-Field 6D Pose Dataset and Baseline for Robotic Strawberry Harvesting
Jun 9, 2026Woojung Son, Won Suk Lee, Zijing Huang +4Sim-to-Real Transfer Object Pose Estimation
Department of Agricultural and Biological Engineering, University of Florida · Department of Electrical and Computer Engineering, University of Florida · Edwardson School of Industrial Engineering, Purdue University +1
Task Robustness via Re-Labelling Vision-Action Robot Data
Jun 9, 2026Artur Kuramshin, Özgür Aslan, Cyrus Neary +1Language-Conditioned Robot Manipulation Synthetic Data Generation for Robotics
1Mila — Quebec AI Institute · 2Université de Montréal · 3The University of British Columbia
Synthetic-to-Real Pipeline for Safe Landing Zone Detection
Jun 9, 2026Shrikant Banerjee, Reza FaieghiSynthetic-to-Real Domain Adaptation UAV Navigation
Department of Aerospace Engineering Toronto Metropolitan University Toronto, Canada
SynManDex: Synthesizing Human-like Dexterous Grasps from Synthetic Human Pre-Grasps
Jun 8, 2026Yanming Shao, Zanxin Chen, Wenwei Lin +5Robotic Grasping Dexterous Manipulation
1Shanghai AI Lab · 2Shanghai Jiaotong University · 3Shenzhen University +3
OASIS: From Simulation Data Collection to Real-World Humanoid Loco-Manipulation
Jun 7, 2026Zehao Yu, Jiakun Zheng, Weiji Xie +4Humanoid Loco-Manipulation Sim-to-Real Transfer
Institute of Artificial Intelligence (TeleAI), China Telecom · Fudan University · East China University of Science and Technology +1
SynthICL: Scalable In-context Imitation Learning with Synthetic Data
Jun 6, 2026Cheng Qian, Ruomeng Fan, Yifei Ren +2ICL for Robotics Robot Skill Learning
The Robot Learning Lab Imperial College London
Simulation-Driven Imitation Learning for Biosignals-Free Shared-Autonomy Prosthetic Grasping
Jun 5, 2026Kaijie Shi, Wanglong Lu, Huiling Chen +4Robotic Grasping Robotics Simulation
Department of Computer Science, Memorial University of Newfoundland, St. John’s, NL A1B 3X5, Canada · College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, 325000, China · Department of Mechanical and Mechatronics Engineering, Memorial University of Newfoundland, St. John’s, NL A1B 3X5, Canada

Jun 22, 2026, cs.ROJ/K move · Enter open · S save

IOI: Decoupling Kinematics and Physics for Interactive World Models

Chengyu Bai, Peidong Jia, Tiecheng Guo, Yukai Wang+10

1Beijing Innovation Center of Humanoid Robotics · 2Peking University

Action-Conditioned Video Generation World Models for Robotics Robotic Policy Evaluation Synthetic Data Generation for Robotics Robotics Interactive World Models

Open paper AskPDF arXiv

Developing generalist embodied agents requires interactive environments providing visually realistic feedback and accurate action-conditioned dynamics. Interactive world models address this by simulating such complex dynamics. However, purely data-driven methods struggle to ensure precise control alignment and physically plausible visual feedback due to a lack of explicit structural constraints. To address this, we propose IOI, a hybrid interactive world model integrating analytical kinematic priors with learned physical dynamics. Unlike data-driven approaches prone to spatiotemporal drift, IOI introduces explicit kinematic guidance, computing forward kinematics from action sequences for accurate motion trajectories. These trajectories are rendered into synchronized front, side, and top orthographic projections, eliminating the need for extrinsic camera calibration. A Multi-view Kinematic Aggregation and Injection module fuses these geometric cues and injects them into the video generator, providing geometry-consistent guidance. Conditioning video generation on these deterministic trajectories establishes a synergy between the analytical simulator and the world model. Decoupling deterministic motion into the kinematic prior frees the generator to model stochastic physical interactions. Experiments on the RoboTwin benchmark validate IOI across kinematic fidelity, out-of-distribution (OOD) generalization, and policy evaluation. IOI achieves state-of-the-art simulation performance and robust zero-shot generalization to unseen OOD tasks. Furthermore, IOI serves as a reliable policy evaluator, yielding success rates closely aligning with ground-truth physics simulators. On real-world platforms, policies trained on IOI-synthesized data match those trained on teleoperation demonstrations, solidifying its practical value for embodied policy learning.

Momentum

Related topics

Latest papers 196