Dexmal原力灵机开源Dexbotic，基于PyTorch的一站式VLA代码库

Core Insights - Dexbotic is an open-source visual-language-action (VLA) model toolkit developed by Dexmal, aimed at researchers in the field of embodied intelligence, featuring a modular architecture with three core components: Data, Experiment, and Model [3][7][9]. Group 1: Need for a Unified VLA Development Platform - The VLA models serve as a crucial technology hub connecting perception, cognition, and action, but face challenges such as severe decentralization in research, cumbersome development processes, and fairness issues in algorithm comparison [5][7]. - The introduction of Dexbotic addresses these pain points by providing a standardized, modular, and high-performance research infrastructure, moving the field from "reinventing the wheel" to "collaborative innovation" [7][9]. Group 2: Dexbotic Architecture - The overall architecture of Dexbotic consists of three main layers: Data Layer, Model Layer, and Experiment Layer, with the Data Layer optimizing storage and integrating multi-source data [9][11]. - The Model Layer includes the foundational model DexboticVLM, which supports various VLA strategies and allows users to customize new VLA models easily [9][11]. - The Experiment Layer introduces an innovative script mechanism for conducting experiments, enabling users to modify configurations with minimal changes while ensuring system stability [11][12]. Group 3: Key Features - Dexbotic offers a unified modular VLA framework compatible with mainstream large language models, integrating embodied operation and navigation functionalities [13]. - High-performance pre-trained models are available for major VLA algorithms, significantly enhancing performance in various simulation environments and real-world tasks [13]. - The experimental framework is designed for flexibility and extensibility, allowing users to easily modify configurations and switch models or tasks [13][14]. Group 4: Open Source Hardware - Dexmal has launched its first open-source hardware product, Dexbotic Open Source - W1 (DOS-W1), featuring a fully open design that lowers barriers for use and maintenance [16][17]. - The hardware design includes modular components and ergonomic features to enhance user comfort and data collection efficiency [17]. Group 5: Future Outlook - Dexmal plans to expand its offerings with more advanced VLM base models and open-source hardware, integrating simulation-to-real-world transfer learning tools and establishing a community-driven model contribution mechanism [19]. - Collaboration with RoboChallenge aims to create a comprehensive technical loop for development, training, inference, and evaluation, ensuring transparency and fairness in performance validation [20].