Chemistry3D: Robotic Interaction Benchmark for Chemistry Experiments
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Abstract (arXiv)
The advent of simulation engines has revolutionized learning and operational efficiency for robots, offering cost-effective and swift pipelines. However, the lack of a universal simulation platform tailored for chemical scenarios impedes progress in robotic manipulation and visualization of reaction processes. Addressing this void, we present Chemistry3D, an innovative toolkit that integrates extensive chemical and robotic knowledge. Chemistry3D not only enables robots to perform chemical experiments but also provides real-time visualization of temperature, color, and pH changes during reactions. Built on the NVIDIA Omniverse platform, Chemistry3D offers interfaces for robot operation, visual inspection, and liquid flow control, facilitating the simulation of special objects such as liquids and transparent entities. Leveraging this toolkit, we have devised RL tasks, object detection, and robot operation scenarios. Additionally, to discern disparities between the rendering engine and the real world, we conducted transparent object detection experiments using Sim2Real, validating the toolkit's exceptional simulation performance. The source code is available at https://github.com/huangyan28/Chemistry3D, and a related tutorial can be found at https://www.omni-chemistry.com.
Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). First posted on arXiv 12 Jun 2024.
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Citing papers per year: 2025: 5; 2026: 4.
9 papers.
- 2025AutoBio: A Simulation and Benchmark for Robotic Automation in Digital Biology Laboratorycited by 16
- 2025RoboChemist: Long-Horizon and Safety-Compliant Robotic Chemical Experimentationcited by 9
- 2025Scaling Laws in Scientific Discovery with AI and Robot Scientistscited by 5
- 2026Pipette: An Embodied Simulation Platform, Benchmark, and Data-Efficient Augmentation Framework for Wet-Lab Roboticscited by 3
- 2026LabVLA: Grounding Vision-Language-Action Models in Scientific Laboratoriescited by 3
- 2025Perspective on Utilizing Foundation Models for Laboratory Automation in Materials Researchcited by 2
- 2026Pedagogical Alignment for Vision-Language-Action Models: A Comprehensive Framework for Data, Architecture, and Evaluation in Educationcited by 1
- 2025RM-RL: Role-Model Reinforcement Learning for Precise Robot Manipulationcited by 0
- 2026GRAFT: Grounded and Efficient Online Reinforcement Adaptation for Fine-Grained Robot Manipulationcited by 0
- 2026GRAFT: Grounded and Efficient Online Reinforcement Adaptation for Fine-Grained Robot Manipulation27 Aug 2026
- 2026LabVLA: Grounding Vision-Language-Action Models in Scientific Laboratories11 Jun 2026
- 2026Pipette: An Embodied Simulation Platform, Benchmark, and Data-Efficient Augmentation Framework for Wet-Lab Robotics11 Jun 2026
- 2026Pedagogical Alignment for Vision-Language-Action Models: A Comprehensive Framework for Data, Architecture, and Evaluation in Education20 Jan 2026
- 2025RM-RL: Role-Model Reinforcement Learning for Precise Robot Manipulation16 Oct 2025
- 2025RoboChemist: Long-Horizon and Safety-Compliant Robotic Chemical Experimentation10 Sep 2025
- 2025Perspective on Utilizing Foundation Models for Laboratory Automation in Materials Research14 Jun 2025
- 2025AutoBio: A Simulation and Benchmark for Robotic Automation in Digital Biology Laboratory20 May 2025
- 2025Scaling Laws in Scientific Discovery with AI and Robot Scientists28 Mar 2025