Robotic systems are becoming more popular and widespread in many industrial manufacturing settings, so the need for reliable operation with the least possible amount of downtime is a common, expected demand. Significant advantages can be realized when these robots are coupled with vision systems.
Most current vision systems require extensive support from trained experts and are less reliable due to their complexity. Our company made a fundamental step change to simplify the programming and mechanical complexity of robotic guidance applications.
As our company learned through extensive installations, an innovative vision scheme is only half the battle. Mechanical reliability also plays a big role.
Comau, a worldwide integrator of automation systems headquartered in Southfield, Mich., develops turnkey automated assembly systems and produces robots, weld guns, conveyors, recognition systems and other critical components of automation.
Comau ranks among the largest integrators in the world, with 34 locations in 18 countries and has worked with most of the major automotive manufacturers, first-tier suppliers and industrial/consumer manufacturing companies around the world.
During 2008, engineers at Comau’s North American headquarters looked to develop a robotic guidance system that was an improvement over what they were purchasing from outside suppliers. The goal was to provide a robust system with lower acquisition and operating costs. As part of this improvement initiative, Comau developed its new RecogniSense software, which was introduced in January.
RecogniSense is, in our view, a groundbreaking visual recognition and guidance package. It functions very similarly to the human visual process. “This means it can learn a large number of objects and recognize any of the learned objects regardless of its orientation in the visual field of the camera,” says Mark Anderson, robotic product development engineer at Comau.
RecogniSense uses a conventional 2D camera but it provides three-dimensional data. It provides the coordinate offsets from teach position with six degrees of freedom, X, Y, Z, Rx, Ry and Rz. These coordinates guide industrial robots effortlessly.
A Robot’s Viewpoint
“A traditional robot is programmed to pick up a part from the exact same location every time,” says Anderson. “If the part is even slightly out of place, the robot will fail to pick that part. The RecogniSense system is used to adjust the coordinates from where the robot expected to find the object to where it actually is located with only a single camera (Figure 1). The camera, computer and software work together with the robot to adjust the robot’s position, allowing retrieval of the part.”
To work effectively, adds Anderson, “current software programs require each robot to be equipped with more than one camera to ‘see’ all six degrees of freedom, or external aids such as structured lights must be incorporated into the vision system’s design.” Structured light, says Anderson, is a laser line or cross-hair that is used to find the degrees of freedom the part moved, which a traditional camera can’t see on its own.
RecogniSense software reliably positions a robot using only one camera. The software will work with any GigE camera and any robot available on the market and effectively reduces the number of cameras required per robot, reducing total solution costs for the end user.
“RecogniSense provides our robots true visual recognition,” continues Anderson. “The software emulates the visual cortex of the human brain, and teaches the system to recognize an object in the same way you would teach an infant. We teach the system an object by taking a picture of the object and naming it. All information pertaining to that object is stored in the system’s memory, which allows the system to recognize the target part from a 2D picture.” When the camera sees the object, the system recognizes it regardless of its orientation. The system, adds Anderson, then senses the relationship of the camera to the object and guides the robot to the taught orientation.
When Vision Is Not Enough
To make our robotic guidance systems as reliable and cost-effective as possible, we needed to take our design one step further.
“Not only did we need to reduce the number of cameras in our systems, we wanted to reduce the chances of system failure associated with cabling,” explains Tony Ventura, robotics and vision product line manager at Comau. “The more cables located on a robot, the higher the risk of failure."
Comau was mounting standard GigE cameras with external power on the robots in its systems. Standard GigE cameras require two cables—one for communications and one for power. Two cables meant two times the opportunity for failure in a single-camera application. “With hundreds of cameras mounted on robots throughout an automated assembly line, cable related chances of failure and the associated downtime represented too big a gamble,” states Ventura. “Further, if you have an application for which you need an external trigger, now three cables are involved, with three times the chance of a failure in the cabling.”