How to Use Robots for Nonrepetitive Tasks

From Teledyne DALSA

Editor’s Note: This article is adapted from the white paper, “A Close Look at Vision Guided Robotics (VGR).” Download the full white paper that describes ideal manufacturing environments and applications for VGR in industries such as medical device, pharmaceutical, food packaging and agriculture; explains how machine vision and robotics combine using hardware and algorithms to create VGR; and provides a real-world case study.

We’ve all seen videos of robots rapidly assembling cars with little or no human intervention. Industrial robots like these have increased productivity in almost every manufacturing sector, but they have one shortcoming: they can’t “see.”

Programmed to repeat exactly the same motions over and over again, they can’t detect and maneuver objects of different shapes, sizes and colors, or objects that touch and overlap. So, if a product changes or is added to the production line, the robots must be reprogrammed. And if product components are delivered to the line by traditional hoppers and shake tables, bowl feeders must be retooled.

Beyond Repetitive Tasks

A new generation of robots guided by advanced machine vision is taking robots beyond repetitive tasks. Fueled by smaller, more powerful and less expensive machine vision cameras and other vision sensors, increasingly sophisticated robotic algorithms and processors with machine vision-specific hardware accelerators, these vision guided robot (VGR) systems are transforming manufacturing and fulfillment processes.

VGR makes robots highly adaptable and easier to implement for industries in which new products are introduced frequently and production runs are short, including medical device and pharmaceutical manufacturing, food packaging, agricultural applications, life sciences and more.

What About 3D Vision?

Often, VGR systems use more than one type of sensor to build 3D images. For example, a robot with a 3D area sensor locates and picks randomly positioned parts in a bin. Then a 2D camera detects the orientation of each part on the fly, so that the robot can correctly place them on a conveyor.

By combining laser 3D Time-of-Flight (ToF) scanning and snapshot 3D image capture, some VGR systems gain the resolution to work with a wider spectrum of objects than with a scanning system alone, but without needing to move the camera as with traditional snapshot camera systems.

ToF scanning, which measures the time it takes light from a laser to travel between the camera and an object’s surfaces to determine its depth, has the advantage of working in any lighting condition.

Robust Hardware and Algorithms

These advanced vision systems can process large amounts of data by using hardware accelerators such as field-programmable gate arrays (FPGAs) and application-specific integrated circuits (ASICs). This gives them the capability to handle thousands of SKUs on production lines and in order fulfillment applications.

A critical component of advanced VGR systems is algorithms that prevent the robot and its end-of-arm gripping tool from colliding with the sides of the bin or other objects. This interference avoidance software must be exceptionally robust because every pick from the bin requires a different path plan, and parts are often intertwined.

VGR use is now approaching 50% of robotics in consumer electronics (above the circuit-board level) and other light assembly in Asia. And as random bin-picking technology fast becomes a flexible, easy-to-understand and interchangeable commodity, it’s within the reach of small and medium-sized companies looking to reduce manual intervention, improve safety and quality and increase productivity.

Teledyne DALSA, based in Billerica, Massachusetts, is a participating Encompass™ Product Partner in the Rockwell Automation PartnerNetwork™ program. The company provides machine vision components and solutions including image sensors, cameras, acquisition boards, sophisticated vision software and intelligent vision systems.

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