MHI Solutions Improving Supply Chain Performance
A crew chief monitoring several different screens—the top left is a dashboard of metrics of robots, the top right is data being tagged for future AI model training, the bottom left is a live feed to six robots, and the bottom right shows that there are currently no robots in need of human interference. PHOTOS PROVIDED BY PLUS ONE ROBOTICS
AI‑driven robotic solutions have played a pivotal role in expanding use cases far beyond the original manufacturing applications for robots that started more than 50 years ago, said Gil Leyba, director strategic accounts, industries robotics for MHI member ABB. The increased autonomy and decision‑making capabilities of AI have allowed robotics to thrive in entirely new sectors—including logistics.
“For example, AI vision and sensing systems with edge detection and grasping point planning software enable robots to take on the dull, dirty and dangerous jobs in a warehouse,” Leyba said. “Things like repetitive piece picking or strenuous box lifting can be handled by the automation, while human operators are empowered to tackle higher value‑add planning tasks and supervisory roles.”
Enhancements to navigation capabilities and location accuracy of autonomous mobile robots have increased reliability, such that AI‑equipped AMRs can now function in dynamic, high‑traffic environments that would have been “unthinkable” not that long ago, he said. Visual simultaneous localization and mapping software can automatically map and navigate surroundings with little to no human intervention required beyond initial setup and mission planning.
AI tools have also made programming and deployment of robotics much easier, Leyba said. Advances in natural language and block‑based coding, coupled with robotic lead‑through movement tracking—i.e., a human manually moving and recording a collaborative robot’s mission path—have resulted in more efficient operator training and faster robotic configuration and deployment times.
“While demographic labor availability—or a lack thereof—has challenged a variety of industries, robotics coupled with robust AI capabilities will ensure operations can keep pace with market demands while increasing efficiencies and fostering productive human-machine collaborations, now and in the future,” he said.
Leveraging the robotics systems that utilize machine intelligence is critical to the business stability of all robotics users, but even more advantages exist for these types of systems within the material handling world, said Josh Cloer, vice president, sales and marketing for MHI member Mujin Corp.
In material handling, the tasks and actions for robot systems are typically not a straightforward “if this, then that” determination, Cloer said. There is usually a wide variety of goals for robotics systems introduced through SKU complexity and changing business needs relative to the products being handled and the needs of the downstream supply chain.
“Having a model‑based approach allows for quick adoption of new SKUs that can be added to the model simply and managed appropriately,” he said. “This can reduce downtime and keep critical business systems relevant as things change for a distribution or fulfillment operation.”