1. [Publications](/index.php/publications) 2. TWIN: Two-handed Intelligent Benchmark for Bimanual Manipulation # TWIN: Two-handed Intelligent Benchmark for Bimanual Manipulation ![](/sites/default/files/styles/wide/public/publications/teaser_21.png?itok=r0QgU1zN) Bimanual manipulation is challenging due to precise spatial and temporal coordination required between two arms. While there exist several real-world bimanual systems, there is a lack of simulated benchmarks with a large task diversity for systematically studying bimanual capabilities across a wide range of tabletop tasks. This paper addresses the gap by presenting a benchmark for bimanual manipulation. A key functionality is the ability to autonomously generate training data without the necessity of human demonstrations to the robot. We open-source our code and benchmark, which comprises 13 new tasks with 23 unique task variations, each requiring a high degree of coordination and adaptability. To initiate the benchmark, we extended multiple state-of-the-art techniques to the domain of bimanual manipulation. The project website with code is available at: . ## Authors Markus Grotz (University of Washington) Mohit Shridhar (University of Washington) [Yu-Wei Chao](/index.php/person/yu-wei-chao) Tamim Asfour (Karlsruhe Institute of Technology) Dieter Fox (University of Washington, NVIDIA) ## Publication Date Monday, May 19, 2025 ## Published in [IEEE International Conference on Robotics and Automation (ICRA) 2025](https://2025.ieee-icra.org) ## Research Area [Physical AI](/index.php/research-area/physical-ai) [Robotics](/index.php/research-area/robotics) ## External Links [Paper, Data, Code, Video](https://bimanual.github.io) ## Copyright This material is posted here with permission of the IEEE. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to .