# Benchmarking Generalizable Bimanual Manipulation: RoboTwin Dual-Arm Collaboration Challenge at CVPR 2025 MEIS Workshop arXiv: https://arxiv.org/abs/2506.23351 · HTML: https://mlsanity.com/paper/2506.23351/ ## Key facts - Cited by 8 papers in the map (data through 14 Oct 2026). - Builds on 28 of its 29 references that are in the map. - First posted on arXiv 29 Jun 2025. ## Builds on (most cited first, 28 of 28) - [RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control](https://mlsanity.com/paper/2307.15818/) (2023) - [OpenVLA: An Open-Source Vision-Language-Action Model](https://mlsanity.com/paper/2406.09246/) (2024) - [Diffusion Policy: Visuomotor Policy Learning via Action Diffusion](https://mlsanity.com/paper/2303.04137/) (2023) - [π0: A Vision-Language-Action Flow Model for General Robot Control](https://mlsanity.com/paper/2410.24164/) (2024) - [RT-1: Robotics Transformer for Real-World Control at Scale](https://mlsanity.com/paper/2212.06817/) (2022) - [Octo: An Open-Source Generalist Robot Policy](https://mlsanity.com/paper/2405.12213/) (2024) - [Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success](https://mlsanity.com/paper/2502.19645/) (2025) - [RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation](https://mlsanity.com/paper/2410.07864/) (2024) - [RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation](https://mlsanity.com/paper/2506.18088/) (2025) - [CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulation](https://mlsanity.com/paper/2411.19650/) (2024) - [Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation](https://mlsanity.com/paper/2401.02117/) (2024) - [TinyVLA: Towards Fast, Data-Efficient Vision-Language-Action Models for Robotic Manipulation](https://mlsanity.com/paper/2409.12514/) (2024) - [Latent Action Pretraining from Videos](https://mlsanity.com/paper/2410.11758/) (2024) - [3D Diffuser Actor: Policy Diffusion with 3D Scene Representations](https://mlsanity.com/paper/2402.10885/) (2024) - [DexVLA: Vision-Language Model with Plug-In Diffusion Expert for General Robot Control](https://mlsanity.com/paper/2502.05855/) (2025) - [AdaptDiffuser: Diffusion Models as Adaptive Self-evolving Planners](https://mlsanity.com/paper/2302.01877/) (2023) - [RoboTwin: Dual-Arm Robot Benchmark with Generative Digital Twins](https://mlsanity.com/paper/2504.13059/) (2025) - [3D Diffusion Policy: Generalizable Visuomotor Policy Learning via Simple 3D Representations](https://mlsanity.com/paper/2403.03954/) (2024) - [SkillDiffuser: Interpretable Hierarchical Planning via Skill Abstractions in Diffusion-Based Task Execution](https://mlsanity.com/paper/2312.11598/) (2023) - [RoboTwin: Dual-Arm Robot Benchmark with Generative Digital Twins (early version)](https://mlsanity.com/paper/2409.02920/) (2024) - [ManiCM: Real-time 3D Diffusion Policy via Consistency Model for Robotic Manipulation](https://mlsanity.com/paper/2406.01586/) (2024) - [RISE: 3D Perception Makes Real-World Robot Imitation Simple and Effective](https://mlsanity.com/paper/2404.12281/) (2024) - [G3Flow: Generative 3D Semantic Flow for Pose-aware and Generalizable Object Manipulation](https://mlsanity.com/paper/2411.18369/) (2024) - [DexHandDiff: Interaction-aware Diffusion Planning for Adaptive Dexterous Manipulation](https://mlsanity.com/paper/2411.18562/) (2024) - [SEM: Enhancing Spatial Understanding for Robust Robot Manipulation](https://mlsanity.com/paper/2505.16196/) (2025) - [AnchorDP3: 3D Affordance Guided Sparse Diffusion Policy for Robotic Manipulation](https://mlsanity.com/paper/2506.19269/) (2025) - [ManiSkill-ViTac 2025: Challenge on Manipulation Skill Learning With Vision and Tactile Sensing](https://mlsanity.com/paper/2411.12503/) (2024) - [AVR: Active Vision-Driven Precise Robot Manipulation with Viewpoint and Focal Length Optimization](https://mlsanity.com/paper/2503.01439/) (2025) ## Built on by (most cited first, 8 of 8) - [RoboDojo: A Unified Sim-and-Real Benchmark for Comprehensive Evaluation of Generalist Robot Manipulation Policies](https://mlsanity.com/paper/2607.04434/) (2026) - [chi0: Resource-Aware Robust Manipulation via Taming Distributional Inconsistencies](https://mlsanity.com/paper/2602.09021/) (2026) - [ManiTwin: Scaling Data-Generation-Ready Digital Object Dataset to 100K](https://mlsanity.com/paper/2603.16866/) (2026) - [FieldGen: From Teleoperated Pre-Manipulation Trajectories to Field-Guided Data Generation](https://mlsanity.com/paper/2510.20774/) (2025) - [HyCodePolicy: Hybrid Language Controllers for Multimodal Monitoring and Decision in Embodied Agents](https://mlsanity.com/paper/2508.02629/) (2025) - [GarmentPile++: Affordance-Driven Cluttered Garments Retrieval with Vision-Language Reasoning](https://mlsanity.com/paper/2603.04158/) (2026) - [RoboWits: Unexpected Challenges for Robotic Creative Problem Solving](https://mlsanity.com/paper/2605.30326/) (2026) - [Bimanual Manipulation Within an 8 GB Budget: Zero-Copy Sensing and Quantized ACT on an Entry-Level Jetson](https://mlsanity.com/paper/2608.03938/) (2026) ## Abstract (arXiv) Embodied Artificial Intelligence (Embodied AI) is an emerging frontier in robotics, driven by the need for autonomous systems that can perceive, reason, and act in complex physical environments. While single-arm systems have shown strong task performance, collaborative dual-arm systems are essential for handling more intricate tasks involving rigid, deformable, and tactile-sensitive objects. To advance this goal, we launched the RoboTwin Dual-Arm Collaboration Challenge at the 2nd MEIS Workshop, CVPR 2025. Built on the RoboTwin Simulation platform (1.0 and 2.0) and the AgileX COBOT-Magic Robot platform, the competition consisted of three stages: Simulation Round 1, Simulation Round 2, and a final Real-World Round. Participants totally tackled 17 dual-arm manipulation tasks, covering rigid, deformable, and tactile-based scenarios. The challenge attracted 64 global teams and over 400 participants, producing top-performing solutions like SEM and AnchorDP3 and generating valuable insights into generalizable bimanual policy learning. This report outlines the competition setup, task design, evaluation methodology, key findings and future direction, aiming to support future research on robust and generalizable bimanual manipulation policies. The Challenge Webpage is available at https://robotwin-benchmark.github.io/cvpr-2025-challenge/.