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WAIC robots are converging on industrial settings—so what kind of practical application should smart ports pursue?
Release time:
2026-08-17
At the 2026 World Artificial Intelligence Conference, the trend in the embodied robotics sector has become very clear: showcase‑type products that rely on performance‑oriented features such as fighting and dancing are losing their appeal, while more manufacturers are shifting toward well‑defined real‑world scenarios like industrial assembly lines and standardized workstations. The industry’s focus has now moved to verifying operational Stability and assessing practical value. This shift precisely highlights the core logic behind the deployment of smart ports: rather than striving for universal Intelligent capabilities across all scenarios, selecting highly suitable niche applications is the key to moving from demonstrations to mass production.
For a long time, the smart port sector has been filled with grand narratives about full-stack unmanned systems and versatile operational robots. However, when it comes to real-world Quays, the open environment is complex and operations are highly non-standard, leaving many solutions stuck at the pilot stage and unable to be scaled up. The industry consensus conveyed at this year’s WAIC is precisely this: AI that can be rapidly deployed never seeks to achieve universal capacity covering all scenarios; instead, it focuses on niche segments characterized by high-frequency, essential needs, clear standards, and well-defined task boundaries.
The implementation roadmap for port AI at HIRI FUTURE is a quintessential example of this approach. Faced with scenarios such as mooring and unmooring—operations involving the securing and releasing of mooring lines during vessel berthing and departure—and container handling, which are characterized by complex procedures and high difficulty in standardization, we did not rush to achieve quick results. Instead, we prioritized core processes like straddle carrier positioning, anti-lift protection, Spreader anti-sway, and single‑double container detection—tasks whose workstation boundaries are clear and whose operational rhythms are fixed, making them more suitable for rapid AI verification and deployment.
This choice to start with specific sub‑tasks is not speculative; it stems from the objective demands of industrial settings. Port operations have low fault tolerance and high requirements for safety and efficiency. By focusing on a single workstation, one can quickly verify the technology’s reliability and its return on investment, while also gathering data in real‑world operations to drive continuous improvement. In contrast, open environments with blurred boundaries—characterized by numerous environmental variables and difficulty in establishing uniform acceptance standards—are prone to the predicament of delivering impressive showroom demonstrations that fail in actual field applications.
In fact, the rising popularity of robots for tasks such as stacking, sorting, and packing at this year’s WAIC all follows the same path: first, establish a viable business loop in the most predictable scenarios, then gradually expand outward. For smart ports, true industry competitiveness has never depended on how many use cases are covered, but rather on whether one can secure a solid foothold in specific sub‑segments. Only by identifying the right niche entry point can one unlock the vast market for port intelligence.
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