When It Comes to Robotics, Why Is Artificial Intelligence so Important?

Robotics is an eclectic arena, encompassing knowledge and skills from various fields like computer science, engineering, mechanical design, electrical design, and programmable electronic components. Despite widespread belief that robotics and Artificial Intelligence (AI) are synonymous, they differ in their scope and usage. In fact, the ascent of robotics technology is largely attributed to AI’s ability to allow for swift, precise, and efficient growth. To understand the correlation between AI and robotics, competence in both fields is required. The purpose of this article is to delve deeper into their relationship.

The Difference between Robotics and Artificial Intelligence

Artificial Intelligence (AI) is a computer science and engineering subfield focused on programming devices that replicate human intelligence. Through AI, a device’s ability to perceive, understand, regulate, and recollect information can be improved. AI can be categorised into four main types, namely reactive machines, limited memory, theory of mind, and self-awareness. We will unpack each of these categories in the upcoming sections in great detail.

Robotics is an engineering subfield that centres on constructing tools with pre-defined functions. Since these tasks are repetitive and do not necessitate cognitive abilities, the use of Artificial Intelligence (AI) is not needed. Nevertheless, when robots are charged with carrying out intricate operations, AI is implemented. In reality, AI is commonly utilised in robotics nowadays.

What is the role of AI-powered robots in the realm of robotics technology?

Upon concluding the experimentation or training phase, an artificially intelligent robot can operate independently and make autonomous decisions without human intervention. With the incorporation of machine learning capacities, the robot can acquire new proficiencies, enhance its capability to navigate new scenarios, broadens its comprehension of ideas, and can reason and act in response to visual stimuli.

Despite the limited level of complexity in many robots, there’s an escalating appetite for intelligent automation in the business world. The manufacturing and production industry is adopting more mobile and autonomous robots that can examine, evaluate, and process data to arrive at the best possible conclusion. The proficiency to simply lift heavy payloads is no longer the sole criterion for a robot’s effectiveness.

The ingenuity of robotics technology is exemplified by its ability to autonomously reason; this is where artificial intelligence and robotics overlap. As more and more corporations strive to enhance productivity, they are increasingly entrusting robots to undertake intricate and sophisticated duties that go beyond mere automation.

Artificial intelligence (AI) can provide robots with a plethora of benefits, like better navigation abilities, accurate object recognition skills, and even the potential to aid humans in tasks such as drywall construction, brick laying, and performing robotic surgery.

How are robots and AI linked to each other?

Ever since its inception by John McCarthy in 1956, the phrase “artificial intelligence” has been a contentious and contested topic of discussion. Some skeptics of artificial intelligence raise various concerns, including the possibility of prejudice or violation of privacy, among other issues. Despite such misgivings, it’s undeniable that artificial intelligence has made a profound impact on modern society.

The integration of computer vision into Artificial Intelligence (AI) has empowered robots with navigation, evaluation, and decision-making capabilities. Machine Learning (ML), a segment of both AI and computer science, is a potent resource that allows robots to emulate and learn from human work styles and techniques. Through ML, robots can boost their efficiency, productivity, and proficiency in performing tasks.

Differentiating Between Types of AI

Based on the objectives and operations to be conducted, a vast array of Artificial Intelligence (AI) systems can be utilised. These systems range from those with rudimentary or responsive reasoning to those possessing self-awareness. As of now, only the former two are put into practical use, with the latter two existing merely as hypothetical concepts. Nonetheless, with the swift and continuous progress of AI, it seems that these potentialities could be realized in the not-too-distant future.


Robots that can react to environmental stimuli are known as reactive robots. These robots don’t possess the ability to learn, recall, or employ past experiences to address present demands. Despite their basic nature, these robots find extensive usage in a variety of applications, including spam filters as a prime example.

The ability to recall is lacking

Even machines with restricted memory capacity can perform reactive functions similar to machines with more memory, and can also learn and benefit from past experiences. This class of Artificial Intelligence (AI) is used extensively in everyday applications, such as self-driving cars and humanoid robots that can perceive and react to their surroundings.

Theory of Mind-Body Connection

Despite considerable progress in artificial intelligence, we haven’t achieved the level of complexity required for a theory of mind. In essence, this means that robots aren’t yet capable of making decisions equivalent to those made by humans. By achieving this, robots would be able to comprehend human emotions and behaviour.


Incredible strides have been made in the realm of artificial intelligence, empowering machines to attain human-like levels of intelligence. These machines possess the ability for introspection and conceptual reasoning, challenging our differentiation of them from us due to their corresponding cognitive abilities.

The Significance of Artificial Intelligence in Robotics

The ensuing examples demonstrate the application of AI in modern robots.

Hardware and Software for Vision Systems

Earlier, we touched upon the application of computer vision technology, a subset of artificial intelligence, for empowering robots to comprehend visual input. This technology equips robots to recognise and analyse images and videos by identifying patterns and responding to the information received. Computer vision finds utility across diverse fields, such as medicine and entertainment, to name a few.

Tasks Performed by Computer Vision

Outlined below are some of the crucial operations executed by computer vision systems.

  • OCR:

    Optical Character Recognition (OCR) is a software tool that can convert a scanned document into an editable format.
  • Facial Recognition:

    It is beneficial for detecting and identifying people in digital photos.
  • Object Recognition:

    As a subset of computer vision, artificial intelligence (AI), and machine learning (ML), this field of study intends to leverage AI models to recognise and label the most notable elements present in a given digital image or video with great accuracy. Utilising the potential of AI and ML, this research undertakes to deliver an automated system for object recognition and identification.
  • Pose Estimation:

    It can be deployed to anticipate the future position of a person or object and trail its movement over time.

Technology for Language Comprehension (NLP)

Natural Language Processing (NLP) is a subset of artificial intelligence (AI) that empowers robots to engage with humans. This technique equips robots to understand and mimic human speech patterns. Utilising NLP, humans can issue vocal commands to AI robots, which the robots execute accurately. Siri and Alexa, both voice assistants, are popular illustrations of natural language processing technology.

Peripheral Computing

Owing to the substantial data and computing prerequisites of Artificial Intelligence (AI) applications, Edge Computing proves to be an efficacious solution to address these demands. By overcoming the technical challenges confronted by AI-based applications, Edge Computing has emerged as the foremost approach to combat the ensuing problems:

  1. Firstly, less data is sent to the primary cloud.

    The usage of machine learning algorithms warrants a considerable volume of data to accurately recognise standard patterns and deliver relevant guidance. In contrast to the cloud, the edge precinct is utilised to conduct more processing, lowering the backhauling cost, which is particularly crucial for applications demanding intricate video analysis. Such applications usually entail a considerable bandwidth to be dispatched to the cloud.
  2. Real-time Decision-making

    When employing machine learning for instant actions, promptitude with minimal latency is indispensable. Instead of transmitting all the raw data to a distant cloud for processing, edge computing facilitates making decisions at the very origin of the data and triggering the ensuing actions immediately on the edge.
  3. Localised Data Storage and Processing

    Compared to cloud computing, edge computing furnishes an opening to save sensitive information like a customer’s location locally. Running machine learning and artificial intelligence precisely on-site enables only pertinent data and discernments to be relayed to the cloud, while the remaining can be retained locally.

Scenarios for Utilising AI-based Robots

Given their precision and effectiveness, robots are now ubiquitous across virtually every industry.

Robotics in Medicine

Robotic technology is bringing about a dramatic shift in the healthcare sector. Robots hold the potential for a vast spectrum of medical and therapeutic applications – from assisting surgeons during intricate procedures to acting as prosthetic limbs and supporting patients in rehabilitation programs. The possibilities are virtually boundless. An instance of such technology in use is the da Vinci surgical system, which translates the surgeon’s control panel hand movements into precise actions that requires negligible incision. This system has found use in diverse surgeries, including cardiac, neural and other bodily ones.

Agricultural Robotics

Planting, weeding, and harvesting crops can all be arduous and time-consuming activities in agriculture. Luckily, recent technological milestones are making it feasible for robots to handle such tasks more effectively. The ecoRobotix, for example, is a solar energy-powered robotic weed-whacker that features a camera system that accurately detects and sprays only the weeds. In addition, robots can be employed for other aspects of agricultural processes, such as crop harvesting, applying pesticides, and plant health assessment. Ultimately, inclusion of artificial intelligence robots on farms is aiding in streamlining and enhancing the agricultural process.

Leveraging Robots to Enhance the Automotive Production Process

For over half a century, the automotive industry has integrated robots into the assembly process. Nowadays, the industry is dedicating significant resources to delve into the capabilities of robots in domains including assembly, welding, removal, transportation, and machine tending.

Robotics in Warehouses

Warehouses require considerable manual labour to manage the immense inventory necessary to fulfil the requirements of e-commerce businesses. While this has conventionally been a labour-intensive task, robots have substantially reduced the time and effort required for activities such as order selection, restocking, and stock cancellation. By training these robots to maintain inventories precisely and move items safely between locations, the need for human labour in such routine assignments has drastically decreased.

Robots in Military Operations

The military is increasingly resorting to robots for myriad purposes, including surveillance and weaponisation. Two noteworthy examples of such robots are the Modular Advanced Armed Robotic System (MAARS) and the Tactical Combat Robot (DOGO). MAARS has a tank-like appearance and is outfitted with a range of features, such as tear gas, laser dazzlers, aural deterrents, motion detectors, and more. Meanwhile, DOGO is equipped with a 9 mm Glock, eight video cameras, and a remotely operated pepper spray module.

This post has underscored the significant role of Artificial Intelligence (AI) in robotics. From healthcare to the military, exploration, entertainment, business, and customer service, robots are increasingly utilised to provide hi-tech solutions to an array of industries. As robots continue to progress and advance, they offer a thrilling prospect for the future of these sectors and can be employed to produce even more efficient and effective outcomes.

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