{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Manufacturing Hub","title":"Ep. 222 - Pick AI Pro with Kevin Wu | Faster Picking, Higher Reliability, Digital Twin and Vision AI","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/4d034bc0\"></iframe>","width":"100%","height":180,"duration":1000,"description":"Modern robotic picking is moving beyond neat rows and perfect lighting conditions. In this Automate 2025 conversation, Vlad and Dave sit down with Kevin Wu from Siemens to explore how Simatic Robot Pick AI Pro is tackling the messy reality of warehouses and factories. They discuss how the new edge architecture with the Simatic IPC BX 59 A and an NVIDIA GPU lifts pick rates to well over one thousand picks per hour, why multiple suction patterns matter for stability on large or flexible items, how camera agnostic support opens the door to new vision hardware, and why transparent objects are no longer a limitation in many applications.This episode also dives into digital thread and digital twin workflows using Siemens Process Simulate. These tools allow teams to test new products and layouts virtually before any hardware changes are made, helping reduce commissioning risk and shorten the path to production. The discussion highlights an on-booth demonstration that combines a robot with a secondary camera and a vision language model to identify products and read packaging details such as expiration dates. It is a clear example of how multimodal AI can complement traditional industrial vision systems.A major theme throughout this conversation is resilience. In real operations, products are rarely placed perfectly. Pallets shift, orientations vary, and lighting changes throughout the day. Traditional rules-based vision systems often struggle when small variances accumulate. Kevin explains how model-free 3D picking localizes unknown objects in clutter, selects stable suction patterns based on measured dimensions, and keeps production moving without forcing operators to maintain perfect alignment.For manufacturers in consumer packaged goods and medical devices, this is a meaningful advancement. It enables greater product variety and frequent SKU changes while maintaining engineering control. The difference is that the picking logic adapts to what the system sees rather...","thumbnail_url":"https://img.transistorcdn.com/yoKAvzBXZ3YjQTekFk7KFGXeuwJ29WgXvop3dVEfhLs/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9zaG93/LzE3MjEzLzE2MDk0/MzA1OTgtYXJ0d29y/ay5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}