Autonomous Navigation and Obstacle Avoidance for Intelligent Warehouse Mobile Robots (AGVAMR)

Scenario Requirements and Pain Points:
In modern e-commerce warehouses or flexible manufacturing workshops, logistics paths are complex and ever-changing. Traditional navigation methods using magnetic strips or QR codes—while effective in simpler environments—are cumbersome to install and offer rigid routing, making them no longer suitable for the demands of “flexible production.” The next-generation mobile robots must be equipped with SLAM-based natural navigation capabilities, enabling them to autonomously localize themselves and plan paths in environments without any auxiliary markers. At the same time, given the mixed human-robot flow within warehouses and the dynamic nature of goods placement, robots must possess highly sensitive, autonomous obstacle-avoidance capabilities to prevent collisions with shelves or personnel and ensure continuous, efficient operations.

Application Logic:
Install an F30 / F50 / F60 / N70 navigation and obstacle-avoidance laser radar at the front (or diagonally opposite) end of the AGV/AMR vehicle body. During vehicle operation, the radar continuously scans the surrounding environment in a two-dimensional plane.

Navigation and Positioning: Via the Ethernet interface, high-precision contour point cloud data is output in real time to the onboard controller, assisting the SLAM algorithm in building an environmental map and continuously correcting the vehicle’s coordinates, thereby achieving centimeter-level positioning.
Safe obstacle avoidance: At the same time, leveraging the radar’s built-in area evaluation function, multiple-level collision-avoidance zones (deceleration zones/stop zones) can be configured. When an obstacle is detected in the vehicle’s path, the vehicle will directly trigger deceleration or emergency stop via I/O signals.

Technological Advantages:
The F30/F50/F60/N70 series achieves “dual functionality in one device”—a single sensor simultaneously performs high-precision mapping and navigation as well as safety protection, eliminating the need to install separate navigation radar and obstacle-avoidance radar. This significantly reduces hardware costs and integration space. With a high scanning frequency of 15 Hz and an angular resolution of 0.25°, the sensor can clearly detect even tiny shelf legs or complex environmental features. Coupled with its exceptional resistance to ambient light interference, this sensor ensures stable robot operation whether positioned near bright windows or under varying lighting conditions, making it the core engine for building cost-effective smart logistics systems.

Keywords:

Category:

Mobile robot

Logistics

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