Podcast: Sensors Revolutionizing Automated Material Movement

Are you ready to dive into the future of material handling and logistics? In our latest podcast episode, we explore the fascinating world of fully automated material movement and the pivotal role of sensors in this revolution.

Join us as we sit down with industry experts Mark Longacre from JBT and Brian Sellars from Sick Inc. These seasoned professionals bring a wealth of knowledge to the table, discussing the surge in automated guided vehicles (AGVs) and autonomous mobile robots (AMRs) powered by advanced sensor technologies.

Discover the types of sensors that drive navigation, obstacle detection, and load handling in these intelligent vehicles. Explore the nuances in sensor applications between AGVs and AMRs, uncovering how they navigate pre-defined paths or autonomously adapt to dynamic environments.

Safety is paramount, and the podcast delves into the safety standards adhered to in this field, making it a must-listen for those concerned with industrial safety protocols.

Looking ahead, the discussion also touches on the challenges and exciting future developments in sensor technologies. To stay informed and inspired, tune in to this enlightening podcast episode, and be sure to subscribe for more industry insights. Your journey into the future of material handling begins here.

HOW TO LISTEN TO EPISODE

Mobile Automation Group (MAG) members are the Industry’s leading suppliers of automatic guided vehicle systems. They supply systems worldwide and in virtually every major manufacturing and distribution sector.

Both Automatic Guided Vehicles (AGVs) and Autonomous Mobile Robots (AMRs) are computer-controlled wheel-based load carriers (normally battery powered) that run on a plant or warehouse floor (or, if outdoors, on a paved surface). The main difference between AGVs and AMRs is how the path they follow is determined.

Most AGVs follow predefined paths, although there may be areas of the plant or warehouse where they have more freedom.
AMRs can determine their own path, although they will attempt to follow suggested paths if they exist.

This difference leads to differing methodologies for ensuring safe operation for the two types of vehicle.