ProtoAct: Turning Wet-Lab Protocols into Embodied Robotic Actions
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Abstract (arXiv)
Biological wet-lab protocols are written for trained researchers and often leave routine operations, state-dependent conditions, and contextual parameters implicit, making them difficult to translate into robot-executable actions. We present ProtoAct, a structured protocol-grounding framework that converts free-form biological procedures into state-aware, embodiment-ready action sequences. ProtoAct uses ProtoRAG to retrieve manually annotated examples for context-sensitive parsing, employs RefineChecker to detect and revise missing or inconsistent steps, and applies ActSchema to map the refined procedure into constrained JSON function sequences. We further introduce BioP2E, for which we manually annotate 22 cell-culture protocols into 258 monitoring conditions, 910 executable subtasks, and 962 grounded action calls. Evaluation across seven large language models demonstrates that ProtoAct can be effectively instantiated with different backbones. Ablations confirm that retrieval, posterior checking, and schema constraints make complementary contributions. The parsed subtasks further support demonstration collection and VLA model training, enabling successful execution in both simulation and real-robot settings. ProtoAct thus provides a practical interface between biological protocol understanding and embodied robotic execution.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 11 of its 17 references that are in the map. First posted on arXiv 3 Aug 2026.
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11 of 17 references.
References · 11
- 2024OpenVLA: An Open-Source Vision-Language-Action Modelcited by 2,777
- 2023G-Eval: NLG Evaluation using GPT-4 with Better Human Alignmentcited by 2,205
- 2023LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learningcited by 1,338
- 2022Code as Policies: Language Model Programs for Embodied Controlcited by 1,172
- 2025SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Roboticscited by 507
- 2023BioPlanner: Automatic Evaluation of LLMs on Protocol Planning in Biologycited by 42
- 2025AutoBio: A Simulation and Benchmark for Robotic Automation in Digital Biology Laboratorycited by 12
- 2025BioMARS: A Multi-Agent Robotic System for Autonomous Biological Experimentscited by 6
- 2024ProtoMed-LLM: An Automatic Evaluation Framework for Large Language Models in Medical Protocol Formulationcited by 4
- 2026BioProVLA-Agent: An Affordable, Protocol-Driven, Vision-Enhanced VLA-Enabled Embodied Multi-Agent System with Closed-Loop-Capable Reasoning for Biological Laboratory Manipulationcited by 3
- 2026Pipette: An Embodied Simulation Platform, Benchmark, and Data-Efficient Augmentation Framework for Wet-Lab Roboticscited by 3
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Citing papers per year: 2026: 1.
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- 2026SciHorizon-eLab: An Agentic Protocol-to-Task Compiler for Scalable Benchmarking of Scientific Embodied Agents
- 2026BenchBench-Protocol: Evaluating Real-World Wet-Lab Protocol Reasoning and Modification
- 2025BioProBench: A Corpus and Benchmark for Biological Protocol Reasoning in Autonomous Science
- 2025Unleashing Scientific Reasoning for Bio-experimental Protocol Generation via Structured Component-based Reward Mechanism
- 2026AtomBridge: Agentic VLA Inference Plugin for Long-Horizon Tasks in Scientific Experiments
- 2026Dual-Agent Framework for Cross-Model Verified Translation of Natural-Language Protocols into Robotic Laboratory Platform