DETROIT, May 30, 2023 /PRNewswire/ — Mech-Mind Robotics, a leading provider of industrial 3D sensors and AI-powered software for intelligent robotics, impressed the visitors at the highly anticipated Automate Show 2023 in Detroit, USA, from May 22 to 25. During the event, Mech-Mind showcased the capabilities of 3D vision through multiple applications, presenting high-performance 3D sensors as well as advanced algorithms optimized for the unique needs of the automation industry.
Mech-Mind at the Automate Show 2023
3D Vision-Guided Random Picking of Round Parts
3D Vision-Guided Piece Picking
Since the debut of Mech-Mind’s first 3D vision solution at Automate–a leading exhibition dedicated to showcasing the latest in robotics, AI, and vision technology–Mech-Mind’s 3D vision products and services have had a remarkable impact on the automation industry. Focusing on providing easy-to-use and proven 3D vision sensors and advanced robotics technologies to its partners and system integrators, Mech-Mind enables its customers to effectively solve complex automation challenges, such as random bin picking, depalletizing, piece picking, assembly, and quality inspection.
At the event, attendees had the opportunity to explore the latest innovations in 3D vision, motion planning, and automated picking of random items. They were also introduced to the leading-edge 3D camera technology for robot guidance and the newly launched 4K resolution 3D laser profilers for industrial inspection and measurement.
Random Picking of Round Parts with Optimal Results
Automating the random picking of items from deep bins has always been a challenge. In a wide range of industries, such as automotive and construction machinery, it is critical to accurately identify and distinguish items from their surroundings.
At Automate 2023, Mech-Mind presented the application of this challenging task – the 3D vision-guided random bin picking of round parts. Using a Mech-Eye LSR L industrial 3D camera, the system can guide a robot to pick up shiny, reflective parts from a disorganized bin, even if they’re located in hard-to-reach corners, and place them in a desired location.
“Random bin-picking robotic systems often have difficulty clearing the deep material bins,” said Cloris Xu, Mech-Mind’s Vice President of Marketing. “By incorporating Mech-Mind’s 3D vision capability, the bin can be cleared effectively and safely without collision with the bin or work cell.”
Automated Piece Picking: Handling of Proliferating SKUs
Visitors to the Mech-Mind booth gained valuable insights into their cutting-edge 3D vision-guided piece picking technology, which utilizes advanced algorithms to handle an increasing proliferation of SKUs and pick new items – with no previous registration required. This versatile solution is ideal for various sectors, including health and beauty stores, e-commerce companies, and grocery stores.
In today’s fast-paced market, organizations dealing with warehousing and logistics must be able to pick items accurately and efficiently from an extensive range of SKUs. Mech-Mind’s 3D vision system enables robots to perform multi-SKU picking, even under challenging conditions, such as items in tight spaces or near bin walls, which is crucial for success in the industry.
“We are thrilled to showcase our innovative 3D vision and AI technologies and newly updated 3D vision sensors at Automate 2023,” said Cloris Xu. “We clearly see that the world of automation and 3D vision technology are mutually beneficial, and our goal is to enable partners and system integrators to solve complex automation tasks in automotive, logistics, construction machinery, consumer electronics, etc.”
Mech-Mind is dedicated to advancing industrial automation and making the world a better place. Trusted in the most demanding applications, Mech-Mind has deployed 3000+ vision solutions for 1000+ customers around the globe. For more information, please reach out to [email protected] for business-related questions or [email protected] for marketing and promotional inquiries.
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SOURCE Mech-Mind Robotics
