AI in Robotics: 6 Groundbreaking Applications

AI in Robotics: Overview

Robotics and artificial intelligence have both been era-defining technologies, and the fusion of both was nothing short of a revolution.

AI in robotics has seen vast success across multiple industries and gained a significant market over the last few years. The AI robotics market stood at US $6.9 Billion in 2021 and is forecasted to reach US $35.5 Billion by 2026 at a CAGR of 38.6%.

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

Many organizations integrate AI robots into their routine procedures for increased productivity, efficiency, and better customer experience. Dominating both tech and non-tech industries, robots can be seen greeting customers at stores, waiting tables at restaurants, harvesting crops, or lifting heavy loads at manufacturing plants. In industrial settings, AI-enabled robots keep workers safe by operating in shared spaces. They also perform complex tasks such as cutting, grinding, welding, and inspection autonomously. 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.

Now, let's discuss some industries currently using AI robots.

Agriculture

The agriculture sector utilizes modern technology to improve process efficiency and increase crop yields. AI in agriculture helps farmers understand weather conditions and advises them on using fertilizer, water, and the time to harvest. 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.

Robot picking

Farmers spend several hours in the field daily, and the process of harvesting entire fields takes up to several weeks or even months. According to 2017 census data, it would take 500 hours for a worker to pick apples from a 38,000-acre field, and the work goes up to 1250 hours for strawberry picking.

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

For example, the Dexterous Hand by Shadow Robot is an advanced robotic arm trained using reinforced learning to perform specific tasks. The Dexterous Jand is an agile piece of hardware, perfect for fruit picking 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 ripened and pluck 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.

Crop harvesting/wedding

AI can also determine whether the crop is ripened and ready for harvesting. This information is vital for farmers who use it to identify ready-to-harvest crops using a smartphone application rather than manually monitoring the field.

The Agrobot E-Series robots use an onboard short-range integrated color and depth sensor to evaluate the ripeness of fruit. It then uses its robotic arms to pluck and store the berries. Researchers from Cambridge University have developed the Vegebot, an AI-assisted robot for harvesting Iceberg lettuce which is a particularly challenging crop. It uses a series of cameras to locate the lettuce, determine its health state, and guide a robotic arm to make a precise cut.

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

Manufacturing

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

Damage control and quick maintenance

Robots armed with computer vision technologies inspect machinery and infrastructures for damages or inconsistencies. The robots identify and assess the damages and report to relevant authorities for timely action.

Abyss Solutions is an engineering firm that delivers 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 time from months to weeks.

To make sure their models operate 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.

Read more: How Abyss Uses V7 to Advance Critical Infrastructure Inspections

Quality inspection has become a vital application of AI robots in manufacturing. Another company, Naska.AI, delivers AI solutions that inspect construction elements for structural integrity and progress tracking. The autonomous robot moves through construction sites, generating scans for analysis of quality issues and progress monitoring.

Automatic control

Companies have started implementing integrated control solutions, creating a single access point for process 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 procedures like design engineering, manufacturing, and supply chain.

Nuclear waste management

When a nuclear plant is decommissioned, its remnants must be collected and disposed of safely. This is a dangerous job for humans as any items left over are riddled with radioactive  waste and must be handled cautiously. Moreover, the preparation and cleaning process could take months to complete.

In 2020, the Manufacturing Technology Centre partnered with robotic 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 identify and grip objects of interest. Moreover, they used V7’s image annotation tool to speed up the labeling process ten times.

Read more: How MTC is Using V7 to Build AI for Sorting and Segregating Nuclear Waste

Assembly line quality inspection

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

AI robots can perform the same task with increased accuracy and precision. Computer vision algorithms look for any irregularities in the assembly and prompt the robotic arm to remove the defective items. With computer vision models achieving ground-breaking accuracies, this methodology is less prone to error and can operate without disruptions.

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