Essential to most manufacturing operations, bin picking is a simple, but tedious task when performed manually. While robotic bin picking has contributed higher levels of efficiency, throughput and accuracy to the job, integrating a robot for autonomous bin picking can be a complex and laborious process. Fortunately, a bin picking system that removes the integration barriers traditionally associated with automated bin picking is available as an all-in-one solution without a third-party AI teaching requirement.
This blog will discuss the advantages of automated bin picking systems, the complexities of integration and how a new solution can ease the burden of robotic bin picking setup.
What is Bin Picking?
Bin picking involves selecting objects from disorganized or cluttered bins and loading them onto a machine or the manufacturing line for further sorting, assembly, kitting or packaging. This task was traditionally accomplished manually, however, it was slow and inefficient.
For this reason, robots have been employed for automated bin picking. Robotic bin picking involves the use of a robot; machine vision technology, which enables the robot to “see” the objects; and specialized software for object recognition and path planning. Together, these components allow a robot to recognize and select randomly placed objects from a bin or container and then load them onto a machine.
Automated bin picking offers several advantages, including:
- Increased productivity and efficiency: Bin picking robots offer high cycle times, making them faster than manual bin picking operations and often eliminating bottlenecks attributed to slow manual bin picking. Additionally, when production demand is high, bin picking robots can work 24/7 without breaks or shift changes, further increasing productivity and throughput.
- Improved safety: Bin picking often requires bending, lifting and twisting, which contributes to repetitive motion injuries in manual workers. Eliminating these activities by automating bin picking tasks reduces injuries and increases facility safety records.
- Reduced labor needs: While bin picking is an essential part of manufacturing operations, it is a simple task for skilled laborers. By automating bin picking processes, skilled workers can be reassigned to more complex tasks that require problem solving and critical thinking skills, which contribute more value to manual labor hours.
- Quality improvements: Robotic bin picking is precise and accurate, so there will be fewer errors, which will improve product quality, while reducing scrap and rework.
- Flexibility: Bin picking robots can be reprogrammed to handle new parts and different bin configurations if production changes with seasonal demands or new products are developed. Robotic bin picking is also more flexible than traditional part feeders, which are designed for specific parts and orientations.
While there are many advantages to automated bin picking, there are also significant challenges when setting up a robotic bin picking system. The robot must identify the part from among the bin’s other contents, which may include a cluttered variety of shapes, sizes and orientations of objects; pick up the product; and then plan a path that does not interfere with other objects in the bin or the area.
Typically, coordinating this activity requires a complex integration process and the use of third-party AI teaching.
An All-in-One Solution for Automated Bin Picking
Fortunately, Photoneo’s Bin Picking Studio is a software suite that provides a complete solution for robotic bin picking. Bin Picking Studio simplifies bin picking integration by providing a user-friendly interface and tools that streamline integration, allowing users to quickly set up and configure their bin picking system without complex programming or third-party AI teaching.
The intuitive interface makes it easy for users to navigate and configure the bin picking system, while teach-pendant integration allows for easy definition of start and end poses for the robot’s movements. The solution supports a large database of robot models, allows users to configure the robot-camera calibration and makes it easier to design, visualize and configure the automated bin picking process via a visual setup wizard that provides feedback on each step within the configuration process to reduce design time.
Users can select up to four different objects and use four scanners within one bin picking scenario. Additionally, Bin Picking Studio offers a specially designed engine for the selection of gripping points in the virtual environment on the model of an object. Using this tool simplifies the process of finding the right point to grasp.
Following the simplified integration process, Photoneo’s bin picking system allows robots to autonomously pick parts from a bin, even when they are disorganized or randomly placed. It combines a 3D bin picking vision system, such as the PhoXi3D scanner, with software that is programmed to locate, grasp and move objects.
This combination of easy integration, set up and teaching along with the bin picking vision system and object localization software allows users to quickly integrate and configure the bin picking robot, define the robot environment, calibrate the scanner and set up part localization without complex programming.
The solution brings everything together so that in use the bin picking vision system captures a point cloud of the bin to provide detailed information about the objects and their position within the bin. The point cloud data is processed by the software’s localization algorithms, which allow the system to accurately determine the position and orientation of each object. The software then calculates the robot’s path to approach and grasp each object.
Contact the experts at HTE to discuss how Photoneo’s Bin Picking Studio enables robots to perform complicated bin picking tasks with more accuracy and speed but without the hassle of complex integration.
