Bi-VLA：基于视觉-语言-动作模型的双臂机器人灵巧操作系统
Bi-VLA: Vision-Language-Action Model-Based System for Bimanual Robotic Dexterous Manipulations
AI总结：
本研究提出面向双臂机器人灵巧操作的Bi-VLA系统，整合视觉、语言与动作能力，经家庭沙拉制作任务实验验证，语言模块代码生成准确率100%，视觉模块食材检测准确率96.06%，整体任务成功率83.4%。
摘要：
本研究提出了Bi-VLA（视觉-语言-动作）模型，这是一款专为双臂机器人灵巧操作设计的新型系统，可无缝整合用于场景理解的视觉能力、用于将人类指令转化为可执行代码的语言理解能力，以及物理动作生成能力。我们通过一系列家庭任务评估了该系统的功能，包括根据人类需求制作指定沙拉。Bi-VLA展现出解读复杂人类指令、感知并理解食材视觉上下文，以及执行精准双臂动作来制作所需沙拉的能力。我们通过一系列实验，从准确率、效率以及对不同沙拉食谱和人类偏好的适应性方面评估了系统性能。结果显示，语言模块生成正确可执行代码的成功率为100%，视觉模块检测特定食材的成功率为96.06%，系统正确执行用户请求任务的整体成功率为83.4%。
英文摘要：
This research introduces the Bi-VLA (Vision-Language-Action) model, a novel system designed for bimanual robotic dexterous manipulation that seamlessly integrates vision for scene understanding, language comprehension for translating human instructions into executable code, and physical action generation. We evaluated the system's functionality through a series of household tasks, including the preparation of a desired salad upon human request. Bi-VLA demonstrates the ability to interpret complex human instructions, perceive and understand the visual context of ingredients, and execute precise bimanual actions to prepare the requested salad. We assessed the system's performance in terms of accuracy, efficiency, and adaptability to different salad recipes and human preferences through a series of experiments. Our results show a 100% success rate in generating the correct executable code by the Language Module, a 96.06% success rate in detecting specific ingredients by the Vision Module, and an overall success rate of 83.4% in correctly executing user-requested tasks.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
