Forklift-type AGVs, also known as unmanned forklifts, are a type of Automated Guided Vehicle (AGV). They are intelligent forklifts equipped with automatic navigation systems, enabling unmanned operation. Their core function is to automatically complete logistics tasks such as handling, stacking, and loading/unloading palletized goods, and they are widely used in manufacturing, warehousing, and logistics. These devices typically integrate multiple navigation technologies such as laser SLAM and vision, possessing autonomous path planning and obstacle avoidance capabilities. They effectively improve handling efficiency, reduce labor costs, and adapt to high-intensity or high-risk operating environments, making them a key piece of equipment for intelligent manufacturing and smart logistics.
Traditional unmanned forklifts using Wi-Fi connections suffer from signal interruptions, poor connection quality, inaccurate positioning, and untimely real-time scheduling responses. By leveraging 5G networks, combined with UPF deployment and MEC deployment, AGVs can be provided with ultra-low latency and highly reliable communication, achieving more accurate global positioning, real-time scheduling, and multi-vehicle collaboration, effectively improving operational efficiency and safety. 5G-based intelligent unmanned forklifts replace traditional manual handling.
With the enhancement of embodied intelligence, the environmental perception, route planning, and motion navigation capabilities of unmanned forklifts are significantly improved. Forklifts equipped with advanced embodied intelligence recognition technology can accurately identify goods and predict road conditions, navigating complex environments flexibly and avoiding obstacles with ease, enabling rapid deployment and use.
Overall, forklift-type AGVs are developing towards intelligence and autonomy. In the future, they will integrate AI large-scale models, digital twins, 5G+MEC, and other technologies to achieve more advanced autonomous decision-making, path optimization, predictive maintenance, and large-scale fleet collaborative operations, further breaking down scenario boundaries.