Huge algorithms and datasets go into the process of evolving the robotics potential into a human-like vision.
The technology revolution in twentieth century changed the outlook of world forever. Technology is now accessible to people sitting at homes and not just limited to laboratories and research institutes. The new realms of electronics, telecommunications, automation, and computation are the driving forces, rather than the mechanical systems of the previous century. In the early 1900s there were almost no telephones, but at the dawn of the millennium mobile phones were an everyday sight; computers were almost unheard of one hundred years ago, but have become universal. We are now at the cusp of a new technological shift of equal significance: the Robotics Revolution. This revolution will place the 21st century at a pivotal position in history. More importantly it will irrevocably impact all our lives and the lives of future generations.
When we think of robots, we think of it to be humanoid, to have limbs, to walk, or to talk. But there is a much wider interpretation of what a robot is. Robots are seen increasingly as the interface between AI and humans by the big tech companies. A growing number of businesses worldwide are using transformative capabilities of machine learning, mainly when applied to robotic systems in the place of work. The boundaries between smart materials, artificial intelligence, embodiment, biology, and robotics are blurring. The goal of using artificial intelligence and machine learning for robotics is to produce machines with abilities that go beyond humans.
The effective aggregate of robotics, Artificial Intelligence and Machine Learning is establishing the door to entirely new automation possibilities. The evolution of robotic intelligence shows a wide range of hierarchy since the time it was first created. Introduced to be deployed in factories for industrial use, it isn’t easy to find a sector where robotics is not used today. In the initial days of its advent, robots were merely designed for performing a trained set of repetitive tasks. By then, robotics was operating exclusively on Artificial Intelligence and Machine Learning . The 2000s trace the utilization of Artificial Intelligence in digitally programmed industrial robots. The global scenario has widely changed since then. Skillful integration of Machine Learning (AI) and robotics has been developed to advance the alleged ambit of robotic intelligence, enabling it to attain a sound human vision to detect potent stimuli.
Precise machine learning processes are being used to train robots and improve accuracy. Artificial intelligence teaches functions like spatial relations, grasping objects, computer vision, motion control, etc., in robots to make them understand and work on unseen data and situations.
The current generation of blending machine learning and robotics allegedly seems to be the most powerful combination in the history of technological innovations. A completely new era of automation is set to disrupt every possible institution of human civilization. AI-driven robots are considered more efficient than the ones without this technology. For instance, the industrial sector stands as the biggest consumer of functions like robotics and further automation, saving time and human effort and ensuring validity, accuracy, and minor errors. AI provides robots with adequate computer vision and motion control to better understand the environment and act accordingly.
Similarly, machine learning conditions the robots in such a way that with timely evolution, they learn from their own mistakes, thus preventing constant human intervention and parallel effort. This ensures adaptability in robotics. Along with these implications, AI and ML certainly make manufacturing activities more efficient, especially for big labor-intensive companies; it also improves the available potential of robots.
APPLYING MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE IN ROBOTICS IN VARIOUS SECTORS-
- Health & medicine-
AI robotics is transforming the healthcare market. ML-driven robotics is already a massive part of the healthcare chain, including function testing, surgery, research, data integration, etc. AI robotics is widely used to track patients’ health status, form a continuous supply chain of medication and other essentials around the hospital, and design custom health tasks for patients. AI and robotics are aiding the healthcare sector by providing assisting robots, precise diagnosis, and remote treatment. Robots’ proactive analysis allows them to detect minute and complex patterns in a patient’s health graph. Robots driven by machine learning are actively used in hospitals for micro-surgeries such as unclogging blood vessels. One of the biggest gifts of AI robotics to the healthcare industry is its operation in remote areas. Treatment in remote areas has been a major loophole in the medical sector for a long time. Robots can solitarily undergo several clinical tasks.
Integrating AI, ML, and Robotics provides the farmers with useful insights to help improve their farm productivity. By attaining this information, farmers ensure high yields and low operational costs, thus, stepping towards farm success. The primary fundamental of introducing robotics in farms is cutting down labour efforts by automating farm activities like irrigation, seed distribution, pest control, and harvesting. This renders the growers with much more time to focus on productive tasks. Emphasizing a major advantage of robotics of ensuring precision, it helps mitigate wastage of land potential, thus making a place for effective land use. Robotization of the green economy can help monitor quality enhancement, environmental conservation, and so on. The agricultural colony is gradually shifting towards these technologies, ensuring huge farm success in the wider picture. This creates a need for constant growth in AI-generated robots to improve the global agriculture scenario.
Big companies with even larger warehouses are big consumers of robotics as it cuts operational time and intermediate costs. High-tech sensors allow these automated devices to operate independently in these huge warehouses. The sensors include visual, auditory, thermal sensors. These sensors are the decision-making body of the robots. Automated guided vehicles (AGVs) are utilized for transporting stock from one place to another in a warehouse. The corporate world today works day and night, and therefore the presence of systems like AGSs sustains 24*7 working with similar costs. Aerial drones are another innovation used in warehouses that sustain quick scanning and optimization of the current inventory within no time and with minimal effort. There are some clear benefits of adopting robotics- minimal errors, adaptability, safety, etc. robots are trained human-like figures which operate on acquired algorithms, thus, avoiding mistakes. An example of machine learning involves picking and pl acing over 90,000 different part types in a warehouse. This volume of part types wouldn’t be profitable to automate without machine learning, but now engineers can regularly feed robots images of new parts and the robot can then successfully grasp these part types.
The role of robotics has a whole network of applications in the automotive industry ranging from designing, supply chain, and production activities to an entire set of management activities. Systems like driver assistance, autonomous driving, and driver risk assistance are being implemented in transportation for automobile industries. The automobile industry has been using robotic intelligence for more than 50 years. The only change from then to now is the advancement of AI and ML in this branch, which is a drastic one. The advantages of robotics in automobiles are widespread-
- Robotics provides an accurate vision for locating the required items. Basic errands like installing door panels, fenders, etc., can be easily carried out by robots.
- Assembling machine devices like motors, screws, pumps, etc.
- Robotic arms can be deployed in painting and coating.
- Along with assembling segregated parts, robots can also transfer these parts, including loading and unloading.
The current global scenario shows the widespread prevalence of innovations and suggests the constant requirement for betterment and adequate awareness even in the remotest areas. Advancement in AI and ML robotics is on the massive influx. Artificial intelligence is not a luxury but a necessity that will come forward in the upcoming decades. Robotics aided by artificial intelligence and machine learning is all set to disrupt every sector, from pins to rockets.