Multimodal intelligent logistics robot combining 3D CNN, LSTM, and visual SLAM for path planning and control

This research contributes to enhancing the practicality of logistics robots in complex environments, thereby fostering increased efficiency and safety within the logistics industry. By combining object recognition, spatio-temporal modeling, and optimized path planning, the proposed method enables logistics robots to navigate intricate scenarios with higher precision and reliability, ultimately advancing the capabilities of autonomous logistics operations.