多模态大型模型在机器人控制中的应用研究

Xiran Su
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引用次数: 0

摘要

本研究探讨了多模态大规模模型在机器人控制中的应用。随着人工智能和机器人技术的快速发展,多模态大规模模型作为一种集成多种感知模式的大规模深度学习模型,为复杂环境下的机器人智能控制提供了新的思路和方法。本文首先介绍了多模态大规模模型的基本原理和技术特点,包括其结构、训练方法和应用场景。然后,针对智能家居环境中的具体应用场景,本文设计了一系列实验来评估多模态大型模型在路径规划、任务效果和泛化能力等方面的性能。实验结果表明,多模态大模型能在智能家居环境中实现更准确、高效的路径规划和任务执行,并具有较强的泛化能力,能适应不同环境和任务的需要。最后,本文对多模态大模型在机器人控制中的应用进行了总结和展望,指出了其在智能机器人技术发展中的重要意义和潜在应用前景。
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Research on Application of Multi-modal Large Model in Robot Control
This study discusses the application of multi-modal large model in robot control. With the rapid development of AI and robotics, multi-modal large-scale model, as a large-scale deep learning model integrating multiple sensing modes, provides new ideas and methods for intelligent control of robots in complex environments. Firstly, this paper introduces the basic principle and technical characteristics of multi-modal large-scale model, including its structure, training methods and application scenarios. Then, aiming at the specific application scenarios in smart home environment, this paper designs a series of experiments to evaluate the performance of multi-modal large model in path planning, task effect and generalization ability. The experimental results show that the multi-modal large model can achieve more accurate and efficient path planning and task execution in smart home environment, and has strong generalization ability, which can adapt to the needs of different environments and tasks. Finally, this paper summarizes and looks forward to the application of multi-modal large model in robot control, and points out its important significance and potential application prospect in the development of intelligent robot technology.
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