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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Xiran Su (2024) studied this question.
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