How Computer Vision is making Robots smart
Robotic systems have proven to be incredibly adept at selecting, organizing, arranging, and cataloging products on the production line or in retail settings. The field of robotics is expanding its permitted operating space. Robots can now work more quickly on the assembly line and in brand-new settings like supermarkets, hospitals, and restaurants thanks to machine vision systems that combine AI and deep learning. Machine vision system advances are the primary motivator.
Technology’s field of robotics, which deals with actual robots, mixes computer science and engineering. The latter have effectors to communicate with the outside environment and sensors to see and perceive their surroundings. These sensors are crucial to computer vision since it allows robots to “see” and focus on objects of interest.
Robots without visual perception capability are like blind machines developed for repetitive tasks placed in one place. Robots can now observe their environment and move appropriately to carry out a variety of tasks thanks to computer vision.
What is Robotic Vision?
One of the most recent advancements in robotics and automation technologies is robotic vision. It allows machines, including robots, to see in a larger sense. It is composed of algorithms, cameras, and any other hardware that supports the development of visual insights in robots. This enables machines to perform difficult visual tasks, such as picking up an object placed on the board using a robot arm that has been taught to do so. In this instance, it will carry out the work using sensors, cameras, and vision algorithms. Using a 3D stereo camera to direct a robot to put wheels on a moving vehicle would be a more complicated example.
Robot Vision is the general term for the application of camera gear and computer algorithms to enable robots to process visual data from the environment. Your robot is virtually blind if it doesn’t have Robot Vision. For many robotic tasks, this is not an issue, but for some, Robot Vision is helpful or even necessary. The adventures of robots outside of factories are also made possible by these improved visual systems. Robots will need to recognize people, buildings, street signs, animals, and a variety of other impediments as they enter public settings in order to function.
Types of tasks performed by Robots with Computer vision
There are a number of applications of machine vision in robotics that are currently being used, and also many are still being worked on in the lab or are still in the concept phases.
Inspection
Robots and machine vision can be used to do inspection duties. Checks for visual components like surface finish, dimensions, possible labeling mistakes, the existence of holes, and other elements are made using machine vision. Because machine vision can complete these activities more quickly and accurately than humans, production increases in speed and profitability.
Identification
Robotics can use machine vision to detect things, allowing for the simultaneous identification and classification of a large number of items. To effectively identify an item, machine vision searches for the “variable” part of the object, the feature that makes it unique. This can speed up production, assist robots in warehouses in swiftly locating the proper item, and improve the effectiveness of retail procedures.
Navigation
Robots need to be able to move safely and autonomously in a changing environment, and machine vision is used to improve and rectify data that is obtained from other sources. Other data collection methods, such as accelerometers, and encoders, can detect minute inaccuracies that accumulate over time. The robots’ ability to see better allows them to maneuver with greater precision. Numerous industries, including manufacturing, mining, and even autonomous vehicles, are affected by this capability.
Quality Control
Machine vision may be utilized with confidence in quality control applications thanks to its inspection and recognition capabilities. In order to determine if items pass various quality control checks, inspection and identification techniques of machine vision are used. Production will become more effective and efficient as a result.
Assembling
Machine vision can be combined with robotic systems to create pick-and-place capabilities, according to research. Together, the system can precisely choose the necessary assembly components from the storage station, place them in the proper assembly locations, and fix them to the required components. This opens up the prospect of using robots with machine vision to automate assembly lines.
Locating Parts
A robot with machine vision may choose the necessary parts by classifying them according to their distinct visual characteristics using inspection and identification.
Due to the ability of manufacturing equipment to automatically locate and identify products, production procedures can be completed more quickly and with less labor.
Transporting Parts
A data processing system that aims to be able to interpret the floor within a scene is currently being developed. Machine vision is used to process and interpret environmental data in order to provide the robot with feedback on movement commands.
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.
Industries implementing Robotic Vision
Visual feedback is essential for image and vision-guided robots. Their power of sight is one of the elements that make them widely used across different disciplines. By and large, the applications of CV in robotics include but are far not limited to the following:
Industrial robotics
Any task that currently requires human involvement can be partially or completely automated within a few years. Therefore, it is not surprising that the development of industrial robots places a high value on Computer vision. A robot arm is no longer the only industrial task that a robot can perform nowadays. Here we have shared a list of industrial tasks performed by AI robots:
1: Processing
2: Cutting and shaping
3: Inspection and sorting
4: Palletization and primary packaging
5: Secondary packaging
6: Warehouse order picking
Medical robotics
The analysis of 3D medical images by a CV aids in diagnosis and therapy, but there are other medical uses for a CV as well. In operating rooms, robots are particularly useful for three types of tasks: pre-op analytics, intra-op direction, and intra-op verification. To be more precise, they can perform the following tasks using vision algorithms:
1: Sort surgery tools
2: Stitch tissues
3: Plan surgeries
4: Assist diagnosis
Military robotics
With CV integration, robots may now help with a wider variety of duties to support military operations. The integration of Computer vision into military robots adds unquestionable value. Robotics advanced from a luxury to a necessity, enabling the following with CV-embedded robot operations:
1: Military robot path planning
2: Rescue robots
3: Tank-based military robots
4: Mine detection and destruction
Final thoughts
Robotics does not cease to revolutionize the world around us. It has penetrated through almost every field one may think of. With similar control over human operations and activity in the world, it becomes almost essential to have some kind of automation or human substitutes to assist in daily tasks. These are impossible without visual feedback and ultimate CV integration into robot-guided interventions.
Such machines work automatically while carrying out a variety of activities employing several important sectors thanks to AI in robotics. Robotics is used in a variety of industries, including manufacturing, healthcare, and agriculture, for cost-effective and increased productivity. Better efficiency also enables humans to take benefit of AI’s advantages in these industries. For businesses creating AI robots for diverse industries, TagX offers the intelligence and high-quality training data sets necessary to enable the application of AI in robotics.