Robotics In Modern Gadgets: From Assistants To Companions

Robotics In Modern Gadgets: From Assistants To Companions – The robotics industry has come a long way since the 1960s and has played a major role in the growth of the manufacturing industry. Let’s go through its most important use cases.

The robotics industry has come a long way since the 1960s and has played a major role in the growth of the manufacturing industry.

Robotics In Modern Gadgets: From Assistants To Companions

Today, nearly 3 million industrial robots power numerous industries worldwide, with approximately 400,000 new robots entering the market each year. Their main use cases include the manufacturing industry for assembling vehicles, electronics and military equipment.

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AI in Robotics aims to create an intelligent environment in the robotics industry for better automation. It uses computer vision techniques, intelligent programming and reinforcement learning to teach robots to make human-like decisions and perform tasks in dynamic conditions.

Both robotics and artificial intelligence are era-defining technologies, and the fusion of the two is nothing short of revolutionary.

AI in robotics has seen widespread success in many industries and has gained significant market share over the past few years. The AI ​​robotics market was valued at US$6.9 billion in 2021 and is expected to reach US$35.5 billion by 2026 at a CAGR of 38.6%.

The global pandemic has forced workers to find ways to work remotely, giving way to intelligent robots that can be programmed and controlled from anywhere.

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Many organizations integrate AI robots into their routine procedures for greater productivity, efficiency and better customer experience. Dominating tech and non-tech industries, robots can be seen greeting customers in stores, waiting tables in restaurants, harvesting crops or lifting heavy loads in manufacturing plants. In industrial settings, AI-enabled robots can keep workers safe by operating in shared spaces. They autonomously perform complex tasks such as cutting, grinding, welding and inspection. A research study concluded that the introduction of 1.34 robots per 1000 workers (one standard deviation) reduced workplace injuries by approximately 1.2 injuries per worker.

The agricultural sector utilizes modern technology to improve process efficiency and increase crop yield. AI in agriculture helps farmers understand weather conditions and advises on use of fertilizer, water and harvesting time. Furthermore, robots help farmers automate manual labor, improving efficiency and saving time. Let’s look at some common use cases of AI robots in agriculture.

Farmers spend several hours in the fields every day, and the process of harvesting entire fields takes several weeks or months. According to 2017 census data, it takes a worker 500 hours to pick apples from a 38,000-acre field and 1250 hours to pick strawberries.

Robots can be programmed using machine learning and computer vision to identify specific fruits and pick them.

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For example, the Dexterous Hand by Shadow Robot is an advanced robotic arm trained using reinforcement learning to perform specific tasks. The dexterous jar is a nimble piece of hardware that is ideal for picking fruit without crushing it.

Another AI company, Tevel, has developed AI drones attached to robotic arms. These drones use machine vision to identify which fruits are ripe and pick them using an integrated arm. They have partnered with farms in Israel, the USA and Italy, where their robots work 24/7, saving several hundred hours of manual labor.

AI also determines whether the crop is ripe and ready for harvest. This information is essential for farmers who use it to identify crops ready for harvest using a smartphone app instead of manually monitoring the field.

Agrobot E-series robots use an onboard short-range integrated color and depth sensor to evaluate fruit ripeness. It then uses its robotic arms to pluck and collect the fruit. Researchers at the University of Cambridge have developed the AI-assisted robot Vezbot to harvest iceberg lettuce, a particularly challenging crop. It uses a series of cameras to track the lettuce, determine its health status and guide a robotic arm to make a precise cut.

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Crop weeding is another time consuming task that bothers farmers. Wild plants eventually develop resistance to herbicides, rendering the method useless and requiring manual weeding. Carbon Robotics’ LaserWeeder uses computer vision to identify wild plantations among crops with sub-millimeter accuracy. It then uses thermal energy to eliminate wild growth. The all-weather robot works 24/7, cutting weed control costs by 80%.

Robots have been used in the manufacturing industry for decades. They perform tasks like assembly, welding, packaging and shipping with high precision and efficiency. Recent developments in AI in manufacturing have introduced intelligent robots that can assess situations and perform dynamic actions in real time.

Robots armed with computer vision technologies inspect machinery and infrastructure for damage or anomalies. The robots identify and assess the damage and report it to the concerned authorities for timely action.

Abyss Solutions is an engineering firm that provides infrastructure inspection solutions for land, air and sea. It combines the power of computer vision and robotics to remotely inspect areas that would otherwise require several workers and hours, reducing inspection times from months to weeks.

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To ensure that their models perform at maximum accuracy, Abyss Solutions trains them on giant datasets. Without the right tools, annotation can be challenging. Abyss Solutions uses V7’s image annotation tool to label more than two terabytes of data.

Quality inspection is a major application of AI robots in manufacturing. Another company, Naska.AI, offers AI solutions that inspect construction elements for structural integrity and progress tracking. An autonomous robot moves through construction sites, producing scans for analysis of quality issues and progress monitoring.

For example, General Electric (GE) uses its Brilliant Manufacturing Suite to track several manufacturing process metrics across its 500 factories globally. The Brilliant Manufacturing Suite creates a scalable and intelligent system that integrates processes such as design engineering, manufacturing and supply chain.

When a nuclear plant is decommissioned, its remains must be collected and safely disposed of. This is dangerous work for humans as any remaining material is radioactive waste and must be handled with care. Moreover, the preparation and cleaning process can take months to complete.

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In 2020, the Manufacturing Technology Center partnered with robotics firms and the Nuclear Decommissioning Authority to build an AI solution involving robots to clean up nuclear waste. They developed a cloud-based segmentation model using the V7 platform to train robots to recognize and capture objects of interest. Furthermore, they used V7’s image annotation tool to speed up the labeling process ten times.

Quality inspectors monitor assembly lines looking for any defective material or product entering the supply chain. This manual inspection has significant error potential and requires 24/7 monitoring.

AI robots can do the same job with increased accuracy and precision. Computer vision algorithms look for any irregularities in the assembly and prompt a robotic arm to remove the defective material. With computer vision models achieving ground-breaking accuracy, this method is less prone to error and works without interruptions.

Novakura, for example, provides specialized computer vision solutions for assembly line quality assurance. The Novakura Flow solution uses special cameras to monitor assembly line items, collect information and generate notifications. This information can be used to control conveyor belts or robotic arms to take appropriate actions.

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Intelligent robots in healthcare accelerate surgical procedures and patient outcomes. AI robots perform various tasks in hospital premises ranging from delivery of instruments and performing surgical procedures with the assistance of patients.

In 2019, Robert Wood Johnson University Hospital invested in Tru-D. Tru-D is an autonomous robot programmed to scout hospital premises and disinfect all target areas. It emits a measured amount of ultraviolet light to disinfect entire rooms and protect doctors and patients from harmful bacteria.

AI robots can also perform various other administrative tasks. Moxy by Diligent Robotics helps clinical staff with non-patient-facing tasks. The robot can deliver surgical instruments, lab specimens, medications, etc. to staff so doctors can focus on critical issues.

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AI robots can help patients by monitoring key factors in their recovery, dispensing medications and assisting with their needs. Futronics has developed an AI ecosystem for the healthcare industry that manages patient monitoring and care. Being a cloud-based platform, they collect and analyze patient data 24/7 and determine a course of action for better patient outcomes. Their robots help patients with tasks such as speech training, transportation and meal delivery.

Surgical robots are becoming a frontier technology. For example, Stryker’s Mako robot is a surgical assistant that assists surgeons in hip and knee replacements. It combines 3D imaging, smart robotic arms and real-time data collection to reconstruct bone structure and highlight areas of interest. The system has been installed in 35 countries and has completed 1 million+ successful procedures.

One of the most talked about use cases of AI in transportation is self-driving cars. They combine sensor readings and computer vision to steer themselves.

Cruise combines AI with robotics to develop self-driving cars. The company uses 360 cameras and WebViz to create a 3D map of its surroundings, track objects and transmit information to the car’s processing engine. Cruise has recently launched a operation in San Francisco, Austin and Phoenix for a safe, driver.

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