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峻吉机器人“艾德”(AID)—— 基于场景定义的工业具身智能机器人
Junji Robotics “AID” – An Industrial Embodied Intelligence Robot Based on Scenario-Defined Design
产品设计 智能数码 132 0 2026-06-08
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作品简述
本项目是苏州江锦科技旗下峻吉机器人面向工业4.0与智能制造升级需求,在全球首发的轮式双臂人形机器人“艾德”。它并非实验室的概念机型,而是从超过200家头部制造业客户的真实产线需求中“生长”出来的“实战派”解决方案。 项目的核心创新在于其“场景定义技术”的设计哲学。我们摒弃了“技术先行再找场景”的传统路径,确立了“先能用、再好用、后通用”的务实落地路径。基于对工业现场(多为平整地面、坐姿手工作业)的深刻洞察,我们创造性地采用了“轮式底盘+仿生双臂”的形态,放弃了追求“双足人形”的机械执念,从而在特定环境下实现了更优的移动稳定性、空间利用率和作业可靠性,真正践行了“不需要机器人像人,只需要机器人比人好用”的设计目标。 “艾德”机器人集成了高精度力控、自主导航与端侧大模型推理能力,其单臂具备7自由度、6kg负载及±0.05mm的重复定位精度,能够胜任精密装配、物料分拣、故障排查等复杂任务。本项目的更深层壁垒在于将难以量化的老师傅工艺知识转化为机器人可复现的自适应力控模型,例如成功攻克了金属丝穿线打结等依赖“手感”的技艺,这构成了我们无法被简单复制的核心竞争力。
Project Description
This project introduces “Aid,” a wheeled, dual-arm humanoid robot—globally launched by Junji Robotics, a subsidiary of Suzhou Jiangjin Technology—specifically designed to meet the demands of Industry 4.0 and intelligent manufacturing upgrades. Unlike a laboratory concept model, Aid is a “practical, field-tested” solution that has “grown” from the real production-line needs of more than 200 leading manufacturing customers. The core innovation of this project lies in its design philosophy—its “scene-defined technology.” We’ve abandoned the traditional approach of “first developing the technology and then finding a use case,” instead adopting a pragmatic, step-by-step implementation path: “First make it usable, then make it easy to use, and finally make it universally applicable.” Drawing on deep insights into industrial environments—typically characterized by flat surfaces and seated manual operations—we creatively adopted a configuration featuring a wheeled chassis paired with bionic dual arms. By letting go of the mechanical obsession with achieving a bipedal humanoid form, we’ve achieved superior mobility stability, space utilization, and operational reliability in specific environments, truly embodying our design goal: “We don’t need robots to look like humans; we just need them to be more functional than humans.” The “Aide” robot integrates high-precision force control, autonomous navigation, and edge-side large-model inference capabilities. Its single arm boasts 7 degrees of freedom, a payload capacity of 6 kg, and a repeat positioning accuracy of ±0.05 mm, enabling it to handle complex tasks such as precision assembly, material sorting, and fault diagnosis. A deeper, more significant barrier in this project is our ability to transform the hard-to-quantify expertise of master craftsmen into adaptive force-control models that robots can reliably replicate—for instance, we’ve successfully mastered skills that rely heavily on “hand feel,” such as threading and knotting metal wires. This represents our core competitive advantage—a capability that cannot be easily replicated by others.
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