The Swish Activation and Efficient Net-Based Imaging with Adaptive Optics: Revolutionizing Order Picking and Placing in Robotic Automation

Robotic Automation

Abstract

Background Information: The rise of automation in warehouses has introduced advanced robotic systems for efficient order picking and placing. Technologies like Swish Activation, EfficientNet-based imaging, and Adaptive Optics have emerged to enhance the accuracy and speed of these operations, minimizing errors and improving overall warehouse logistics and efficiency.

Objectives: The primary objective is to integrate Swish Activation, EfficientNet, and Adaptive Optics to improve the accuracy, speed, and precision of robotic order picking systems. The study also aims to reduce error rates and optimize resource consumption in dynamic warehouse environments.

Methods: A robotic system was designed using Swish Activation for efficient learning, EfficientNet for accurate image processing, and Adaptive Optics to correct visual distortions. These components were tested in various configurations through ablation studies to measure their impact on performance metrics like accuracy and speed.

Results: The full model demonstrated 97% accuracy, with the lowest error rate (2%) and optimal energy consumption, proving its superiority in comparison to individual or partial configurations.

Conclusion: The study confirmed that combining Swish Activation, EfficientNet, and Adaptive Optics greatly enhances robotic order picking. Future work can explore incorporating reinforcement learning and quantum computing to further optimize system performance and adaptability in varied industrial settings.