Overcoming Bin-Picking Challenges With KEYENCE Advanced Vision Systems

In bin-picking, robots select items from a bin and place them in the appropriate location. This process involves 3D cameras, 3D bin-picking software, and advanced algorithms to ensure accurate pick-up and placement. Industries such as automotive manufacturing and order fulfillment use this technology to automate tasks, saving time and reducing costs.

• Precision: Traditional bin-picking systems must identify and locate objects within a designated bin accurately. These systems often struggle to guarantee that the robot can pick the object's exact position, leading to potential mispicks.
• Speed: Traditional systems often suffer from slow data processing, delayed image transfer, and poor lighting conditions, all of which slow down the speed of bin-picking operations.
• Reflective Material Handling: Shiny or metallic objects can confuse older vision systems that struggle to recognize parts due to glare or reflective surfaces.
• System Stability in Harsh Environments: Many traditional vision systems fail to perform well in certain conditions, like extreme lighting or temperature fluctuations, which compromise their accuracy and reliability.

KEYENCE 3D vision systems for industrial bin-picking applications are known for their exceptional accuracy in recognizing target objects.

With high-resolution cameras, such as those in the CV-X Series, robots can make highly precise decisions about where and what to pick, even in complex environments.

The CV-X Series systems use high-speed processors and cameras capable of capturing up to 136 images in a fraction of a second; this reduces processing time and supports faster, more efficient pick-and-place operations. With additional features like pattern projection lighting and automatic path planning, KEYENCE technology eliminates delays caused by poor lighting and slow data transfer, enhancing overall operational speed.

Regarding reflective materials, The RB using 4 angles cameras to collect as many data points as possible from different perspectives and captures from angles light patterns. This means the vision system can collect more data on challenging materials with glare or shiny surfaces than a standard bin picking system.

KEYENCE vision systems thrive in harsh environments and feature high-resolution cameras and advanced image processing algorithms. These systems function even in areas with extreme lighting or temperature changes.

The LumiTrax^TM system, for instance, improves stability by minimizing workpiece variation and reducing environmental interference. Implementing AI-driven vision systems further optimizes production by adapting to environmental changes, ensuring consistent performance.

KEYENCE 3D vision systems, such as those in the CV-X Series, use high-resolution cameras (up to 64 megapixels) and projection technology that allow robots to capture precise, detailed images of objects. This technology captures high-speed images, making sure the system can make accurate decisions in complex picking scenarios.

KEYENCE automatic path planning technology helps the robot arm avoid obstacles and pick up objects without colliding with surrounding items. The system calculates the optimal path for each picking task, keeping the robot focused and on task without disruption.

The CV-X Series systems feature automatic calibration and user-friendly setup processes, allowing manufacturers to integrate the technology quickly without requiring specialized training or technical expertise.

Manufacturers can drastically improve quality control by automating the bin-picking process with KEYENCE vision systems. Accurate part identification and placement reduce errors and maintain consistent product output.

Investing in KEYENCE vision systems for 3D bin-picking can help businesses lower labor costs, minimize scrap, and increase throughput while reducing errors and improving reliability and speed. The automation of bin-picking also results in a better return on investment (ROI) as the system quickly pays for itself through increased operational efficiency and cost savings.