Regardless of the distinction, both AGVs and AMRs emphasize the importance of navigation. It's precisely because of the differences in navigation and path planning methods that various variations have emerged. The industry, unlike academia, often summarizes and generalizes concepts after the product has been developed; concepts following market trends are commonplace.
However, the importance of navigation technology for autonomous vehicles is a consensus in the industry. Although it uses a similar drive platform to AGVs, AMRs employ advanced navigation technologies such as SLAM, enabling them to autonomously avoid obstacles and plan routes, thereby improving efficiency and responding more flexibly to changing environments.
There's no need to argue about the precise definitions of AGVs and AMRs now, just like debating whether sweet or savory rice dumplings are better. The key is to use the right AGVs and AMRs in the right scenarios.
In the image above, Kiva has a clearly visible location QR code in front of it.
Because KIVA uses QR codes as a positioning basis, the flexibility of its switching scheme is somewhat limited. Therefore, this type of automated vehicle that uses QR codes is generally classified as an AGV, and its overall scheduling relies more on the central controller.
P+F QR code positioning system
Robotic vacuum cleaners, by adopting SLAM technology, rely more on their onboard systems to build maps of their surroundings and autonomously design their routes, making the classification as AMR (Autonomous Mobile Robot) more appropriate. SLAM technology can be broadly categorized into two main methods: laser-based and natural light-based.
Ouster LiDAR for driver assistance systems
Here, AMR has further integrated with automotive driver assistance systems. The rise of electric vehicles has greatly promoted the application of LiDAR, millimeter-wave radar, and vision sensors. AMR is riding the wave of the automotive industry's growth, rapidly iterating its technology.
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