AI in Robotics: 6 Groundbreaking Applications

The robotics industry has come a long way since 1960s, and has played a vital role in the growth of the manufacturing industry. Let's go through its most vital use cases.
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The robotics industry has come a long way since 1960s, and has played a vital role in the growth of the manufacturing industry.

Today, almost 3 million industrial robots power several industries across the globe, with roughly 400,000 new robots entering the market every year. Their main use cases include the manufacturing industry for assembling vehicles, electronics, and military equipment.

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

n this article, we’ll cover the following use cases of AI in robotics:

Better AI for manufacturing & agriculture

Use computer vision and LLMs for quality control automation

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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.


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%.

💡 Pro tip: Learn how V7 can support your agricultural AI use case


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.

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Intelligent robots in healthcare accelerate surgical processes and patient outcomes. AI robots perform various tasks on hospital premises, from the distribution of equipment and patient assistance to performing surgical procedures.

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

AI robots can carry out several other administrative tasks as well. Moxi by Diligent Robotics assists clinical staff in non-patient-facing tasks. The robot can deliver surgical instruments, lab samples, medication, etc., to staff so doctors can focus on critical issues.

AI robots can also assist patients' recovery by monitoring vitals, delivering medication, and tending to their needs. Futronics has developed an AI ecosystem for the healthcare industry that handles patient monitoring and care. Being a cloud-based platform, they collect and analyze patient vitals 24/7 and decide on a course of action for the best patient outcomes. Their robots also help patients with tasks like walk training, transportation, and meal delivery.

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

💡 Pro tip: Learn how V7 can help you build medical AI products


The most talked-about use case of AI in transportation is self-driving cars. They combine sensor readings and computer vision to maneuver themselves.

Cruise combines AI with robotics to develop self-driving cars. The company utilizes 360 cameras to create a 3D map of its surroundings and WebViz to visualize, track objects, and convey information to the car's processing engine. Cruise has recently begun operations in San Francisco, Austin, and Phoenix for a safe, driverless experience.

However, driving is more than just looking out for obstacles. A skilled driver relies on intuition and experience to navigate complicated spaces, and AI must be able to possess the same skill.

Perceptive Automata takes a different approach to self-driving by analyzing pedestrian behavior. Most AI models treat everything in their vision as static objects and learn to navigate according to their real-time position. Perceptive Automata teach AI about pedestrian behavior to predict their movements and make intelligent driving-related decisions like a human would. This makes autonomous vehicles significantly safer for crowded locations.

💡 Pro tip: Check out how V7 can support your automotive AI project

Smart home appliances

AI robots can be used for household purposes such as cleaning, security, or a walking assistant for basic tasks.

Amazon’s Astro bot was released as a virtual home assistant but has found several different use cases since its launch. Astro comes bundled with the Alexa virtual assistant with capabilities such as voice-activated virtual assistance, music control, and intelligent device control. It can also move around your house, providing a remote view for security. You can program it to recognize unknown people and issue alerts upon such activity.

Another use case of AI robots in homes is cleaning. Several organizations have developed smart cleaning robots that map spaces using computer vision. Samsung’s Jet Bot, for example, is powered with a LiDar sensor for precise movement.


AI robots are also widely used in the aerospace industry for space exploration. NASA’s Perseverance rover has specialized cameras and an artificial intelligence unit that helps it better explore Mars's surface. The rover maps the entire ground in its vision and uses object detection to identify any unique elements.

Virtual assistants have also made it to outer space as companies develop robots to help and guide astronauts.

Airbus’ CIMON-2 is a robot companion for astronauts. It can speak, understand, move around, and perform basic daily tasks. CIMON can be asked to move to different positions using voice commands and take pictures. Moreover, it can display information and instructions to astronauts for engineering tasks.

Final words 

AI in robotics has automated several industries using industrial-grade robots combined with artificial intelligence. AI has revolutionized these industries by shifting complex, resource-intensive, and laborious tasks to machines that can operate for long hours and with high precision.

Intelligent robots have entered the manufacturing, healthcare, and aerospace industries. They are trained using machine learning to perform tasks like automotive assembling, powering self-driving cars, quality inspection, and medical assistance. These robots perform tasks quicker and more precisely than humans and can be deployed in dangerous locations.

With advancements in AI technology, the potential benefits of using robots are expanding. Despite the concerns about unemployment, the advantages offered by intelligent robots have revolutionized many industries and improved life in countless ways.

And if you want to learn more about AI applications across other industries, check out these resources:

  1. 7 Job-ready AI Applications in Construction
  2. 7 Practical Applications of AI in Government
  3. 7 Life-Saving AI Use Cases in Healthcare
  4. 6 Innovative Artificial Intelligence Applications in Dentistry
  5. 7 Game-Changing AI Applications in the Sports Industry
  6. 6 Viable AI Use Cases in Insurance
  7. 6 AI Applications Shaping the Future of Retail
  8. 7 Job-ready AI Applications in Construction
  9. AI in Supply Chain and Logistics [20+ Practical Applications]

Haziqa holds an MS degree in Data Science. She has extensive experience in writing technical content for AI and SaaS companies.

“Collecting user feedback and using human-in-the-loop methods for quality control are crucial for improving Al models over time and ensuring their reliability and safety. Capturing data on the inputs, outputs, user actions, and corrections can help filter and refine the dataset for fine-tuning and developing secure ML solutions.”
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