The past few years have posed new challenges for machine vision experts in the aspect of motion, particularly random motion. This is due to the increased need to equip robots with vision technology that allows them to have a 3D view of the world and all its dynamics. The process of making this possible is not an easy task.
Industrial applications nowadays require robots to be able to see, comprehend, and react to the three-dimensional space that surrounds them in order to make better decisions. A combination of 3D vision and AI enables robots to identify multiple object types, navigate to them, sort them based on certain criteria, and pick them up. However, certain applications can be more demanding than others.
The task becomes more challenging if the robot needs to handle moving objects randomly and unpredictably. This type of application is becoming increasingly popular. For instance, imagine a facility that requires the sorting of freshly caught fish of different types placed on moving conveyors. The vision-guided robot’s task is to recognize each fish type and sort it out based on 3D data and color information. The fish’s erratic motion on the conveyor and their slimy bodies may pose a significant challenge.
In the wood industry, large and heavy logs need to be milled and cut into identical planks and smaller pieces. Conveyors are vital in automating a sawmill process. Logs are placed on moving conveyors to be transported to a 3D vision-guided robot equipped with a chainsaw or other wood processing tools. Logs need to be 3D scanned first, so the robot knows where and how to cut based on the X, Y, and Z coordinates provided by the machine vision system.
3D vision technology can also be used to scan the human body and create a detailed 3D model. 3D scans of specific body parts or the whole body can be useful for high-precision surgery and sports activity analysis. However, standard area-scan 3D vision technologies fall short in providing satisfactory 3D data if the scanned object moves.
The challenge of getting high-resolution and submillimeter-accuracy 3D data and capturing random motion poses a limitation to standard area-scan 3D vision technologies. The same challenge occurs when taking a picture of a moving scene where a camera struggles with motion blur, a visual distortion of an image that occurs when the captured scene changes during the recording of a single exposure.
Fortunately, Slovakia-based Photoneo offers a novel technology solution that enables 3D scanning of areas with submillimetre resolution and accuracy with no matter if the scene is static or in random motion. The patented technology named Parallel Structured Light is integrated into the area-scan 3D camera MotionCam-3D. Photoneo released a colour version of the camera in 2022, which is the only device on the market that provides high-quality 3D data, colour information, and the ability to scan random movement.
The camera’s AI performance value lies in the data it provides by enabling object recognition, classification, and visualization. AI solutions that inspect objects and make decisions based on the data received from MotionCam-3D, such as whether fruit is ripe or if a food product is burnt or undercooked, are in high demand. Photoneo’s innovative technology opens limitless possibilities, making customers achieve unprecedented efficiency and throughput. Object vibrations caused by a moving conveyor belt and other factors will not affect data quality.
Photoneo’s 3D Instant Meshing software enables users to create real-time 3D models of objects in motion with their shape, texture, and colour. The RGB image registered with 3D data having a 1:1 pixel correspondence enables creating 3D models of objects ranging from the size of an orange to that of a large shipping container.
If you require a free feasibility study for your project or talk to Photoneo’s sales team, please don’t hesitate to contact them.