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Visual feedback is essential to robots working in industrial applications. Vision can help robots accomplish tasks that require the navigation and identification of objects. Vision also helps robots collaborate with human workers, and to integrate information from visual sources with that coming in from different sensors. This integration can help robots understand their location in space. These benefits have driven the applications of machine vision in robots.
There are a number of applications of machine vision in robotics that are currently being used, and also many still being worked on in the lab or are still in the concept phases.
Inspection tasks can be carried out by integrating machine vision and robots. Machine vision is used to make checks for visual factors such as surface finish, dimensions, potential errors in labeling, and the presence of holes and other elements.
Machine vision can carry out these tasks faster and with fewer errors than humans can, meaning that production becomes faster and more profitable as a result.
Machine vision can be incorporated in robotics, giving them the skills of object detection to allow for identification and the classification of numerous objects simultaneously. Machine vision looks for the “variable” part of the object, the bit that is different and sets it apart, in order to successfully identify it.
This can help robots in warehouses to find the right item quickly, this speeds up production, and can also make retail processes more efficient.
Machine vision is used to enhance and correct data coming in through other sources in order to move robots safely and autonomously in a dynamic environment. Other measures of incoming data, such as accelerometers and encoders, can relay small errors that add up over time.
With the addition of vision, the robots can move more accuracy. This capability has implications for many industries, manufacture, mining and even autonomous vehicles.
Through the capabilities of inspection and identification, machine vision can be reliably used in quality control applications.
The machine vision techniques of inspection and identification are combined in order to assess whether products meet various quality control checks. This has the impact of making production more efficient and cost-effective.
Research has shown that machine vision can be integrated with robotic systems to create pick and place capabilities.
Together, the system can accurately pick the correct assembly parts from the storage station and put them in the right assembly spaces and on the appropriate parts where they need to be fixed. This gives the possibility of automated assembly lines with the use of robots with machine vision.
Using inspection and identification, a robot with machine vision can select required parts by classifying them through their unique visual features.
This allows production equipment to be able to automatically locate and identify items, speeding up production processes and reducing the required manpower.
A data processing framework is currently being developed that seeks to have the capabilities of interpreting the floor within a scene. Machine vision is being used to process the information of the surroundings and analyze it in order to feedback movement instructions to the robot.
These applications are just the beginning of how machine vision will be used in robotics. Many applications are still in the laboratory, and as the development of machine vision increases, so will its applications in robotics. The industries that will benefit from these applications of machine vision in robotics are numerous.
While currently, their uses lie heavily in production, there is an opportunity for mining, construction, autonomous vehicles, retail, and agriculture to benefit from these advancements.