Autonomous navigation means quicker deployment, maximum flexibility, and worker safety.
In the pursuit of flexible automation and less conveyor, many companies consider automated guided vehicles (AGV) as a solution. There are AGVs available for nearly any industrial purpose – whether you need to shuttle heavy assemblies around a factory or pallets through a warehouse. Large and awkward payloads travelling in a linear path are an obvious use case for AGV robotics, but how can you optimize aisles of case and each picking or non-linear travel paths? That’s the huge gap autonomous mobile robots (AMR) are trying to fill.
Large and awkward payloads travelling in a linear path are an obvious use case for AGV robotics, but how can you optimize aisles of case and each picking or non-linear travel paths? That’s the huge gap autonomous mobile robots (AMR) are trying to fill.
What makes AMR robotics better suited for collaboration with human workers?
To understand the navigational capabilities of AGVs, think about car safety systems that can keep the vehicle in its highway lane and maintain a safe distance from other vehicles. These systems can save a lot of time and effort but are not truly autonomous. AGVs use laser reflectors, floor stickers, magnets to navigate through linear paths – if they have clear markers to follow. Complexities like intersections, human collaboration, and non-linear paths present challenges.
AMRs use navigational tech more like self-driving cars such as computer vision and LIDAR to map a facility’s open areas, racking, and aisles with no physical changes and then dynamically navigate any route in real-time. By utilizing advanced computer vision and radar, AMRs ensure complete safety for humans in busy facilities through advanced traffic management. This approach enables rapid deployment (as little as one day of setup) for additional volume, flexibility for process changes or new use cases, and even building transfers.
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