Bin picking, also referred to as random bin picking is a core problem in computer vision and robotics. The goal is to have a robot with sensors and cameras attached to it pick-up known objects with random poses out of a bin using a suction gripper, parallel gripper, or other kind of robot end effector.
Robotic random bin picking is a process used for machine loading and/or separating parts from a bin for production purposes.
Creating robots that could pick specific objects from a random collection was a frontier in robotics and automation that remained unsettled for many years. When success seemed close, further difficulties have arisen. Overlapping parts and lighting variations confused the process. Computers were overwhelmed by the data needed to recognize parts and calculate their orientation and position.
Breakthroughs occurred with advanced software, rapid computer processing and vision systems also the newest options in gripping.
The solution was a robot that could pick random objects from a bin and adapt to the environment. This is the best possible news for companies that are looking to automate limited sequences or diversify product lines, among other things.
Bin-picking automation now accessible to all manufacturers. This allows manufacturers to easily automate their operations without the need for specialized vision systems and software programming.
