Robomotive and other humanoid robots equipped with 3D vision sensors are playing an increasing role in industrial automation, including in smaller binpicking set-ups where parts are constantly changing.
BitFlow’s Neon-CLB PCIe frame grabber is now an essential component of the 3D structured-light imaging system deployed in the Robomotive™ humanoid robot, jointly developed by Yaskawa Motoman, Beltech, and Robotiq.
Equipped with human-like arms and grippers, the Robomotive can lift up to 44 lbs per arm. Because of its 3D vision system, the two arms work independently or in concordance. In addition, a 7-axis design provides the flexibility to handle objects of different sizes. The technology has been cost-effectively deployed in the automation of small patch processes with large mixes of parts, including in automobile manufacturing.
Because the Robomotive is flexible with advanced imaging capabilities and adaptive grippers, multiple product-specific grippers and jigs are unnecessary. Users do not need to change the hardware environment with Robomotive; it can be placed in a workstation and trained to do the task that a human would do.
With conventional robots, time and money is wasted while switching over from different product batches. The Robomotive allows the user to load a large number of programs, depending on the product being assembled. Tasks can be switched easily and quickly.
The 3D vision system is based upon laser triangulation, a scanning method that is insensitive to the reflective surface of materials often found in production, such as copper, brass, zinc plating, aluminium, or stainless steel, as well as shiny, oily surfaces. Laser triangulation is not disrupted by lighting variations or reflections.
The Robomotive uses a filter on the camera to eliminate extraneous light apart from the laser wavelength. A Peak Detector, built inside the camera, detects the laser maximum intensity point, resulting in 10x better detection and sharper surface details than can be achieved with a typical Center of Gravity.
The steps for robot guidance begin with gathering a 3D point cloud, which has to be processed to locate the object and its orientation. Only then can Robomotive use the gripper to pick it up. The 3D image must be interrogated to ensure that there are no other objects blocking the gripper’s path; software defines the gripper of the robot and its landing zone.
The landing zone of the gripper can be a cylinder of the diameter of the gripper or a 3D model of the gripper. 3D coordinates, as well as the angle and the plane of the object, define the zone, but care has to be taken to avoid collisions between the gripper and its surroundings. For the system to work, communication between robot and vision must be calibrated based on the same coordinates.
The BitFlow frame grabber mitigates the Robomotive’s vision system complexities. Using the Neon-CLB (Camera Link Base cameras only) on a half-sized PCIe x4 interface, the demands and costs on motherboard choice are significantly reduced. The device is built on top of BitFlow’s FlowThru technology, which provides zero latency access to data, low CPU usage, and unlimited DMA destination size. The Neon-CL product set reduces both the system cost and the hardware footprint by its ability to acquire from up to four cameras.
Neon-CLB PCIe frame grabber
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