A Foreword to Artificial Intelligence (AI) and Robotics
Robotics is a field of engineering and computer science that involves designing, constructing, and operating machines capable of performing programmed tasks without additional human involvement. At its core, robotics aims to use technology to automate tasks, making them more efficient and safer. Robotics is a technology branch concerned with physical robots, which are programmable machines that usually carry out a series of actions autonomously or semi-autonomously.
The convergence of robotics and artificial intelligence (AI) is rapidly driving the creation of new industries, cutting-edge technologies, and increased productivity and efficiency in existing sectors. With AI in robotics advancing, its real-world applications are becoming increasingly apparent.
Confluence of AI & Robotics
Artificial Intelligence (AI) involves developing systems that can perform tasks typically requiring human intelligence, such as learning, problem-solving, and decision-making. These systems can work independently, without constant instructions, as they are programmed to learn and adapt on their own. On the other hand, Robotics involves developing robots that can carry out specific physical tasks. These robots can be programmed to perform simple, repetitive actions, like sorting items or assembling small parts.
Although AI and robotics are distinct fields, they complement each other and can work in tandem to bring about a wide range of benefits and advancements in various applications. AI algorithms are necessary when aiming to enable the robot to perform more complex tasks. Companies are employing AI-powered robots to bridge the gap between humans and technology, solve problems, and transform their business models to meet evolving demands.
Four Key Functions: AI & Robotics
AI is teaching robots four key functions to achieve human-like intelligence.
- Vision: AI uses algorithms to improve a robot’s ability to interpret and understand what it sees by detecting unfamiliar patterns.
- Grasping: AI enables robots to learn how to grasp objects based on distance and orientation information provided by vision.
- Motion Control: AI utilizes various technologies, including vision, space detection, and edge detection, to provide precise motion control to robots.
- Data: AI facilitates robots in becoming self-reliant through strong data processing and analysis capabilities.
Robotics Control Algorithms
Robots require specific control algorithms depending on their type and tasks. These algorithms include motion control, computer vision, and other functionalities such as controlling robotic arms, drones, obstacle avoidance, and grasping. Here are some of the recognized algorithms.
Motion Control
These algorithms determine how a robot moves and navigate its environment. Different algorithms are needed for tasks like path following, obstacle avoidance, and localization, depending on the robot’s mobility. Path Planning algorithms involve finding the best path for a robot to reach its destination while avoiding obstacles. Simultaneous Localization and Mapping (SLAM) algorithms enable a robot to create a map of its environment while simultaneously locating itself within that map. These are crucial for autonomous navigation in unknown or dynamic environments.
Computer Vision
This is a fundamental aspect of a robot’s perception, involving processing visual data from cameras to understand the robot’s surroundings. Object detection algorithms identify and locate objects within an image or video stream. This capability is essential for tasks such as identifying obstacles or recognizing specific objects. Image processing techniques enhance the quality of visual data and extract meaningful information. Commonly used techniques include image filtering, edge detection, and feature extraction.
Archetypes: Types of Robots
With the rise of industrial robots in manufacturing settings, there is a growing need for various types of industrial robots that can be tailored to specific applications and industries. These include Cartesian, SCARA, Articulated, Cylindrical, Delta, Polar, and Collaborative Robots. The most common types of AI-powered robots include.
Autonomous Mobile Robots (AMRs)
An Autonomous Mobile Robot (AMR) is a robot that can understand and move through its environment without direct oversight by an operator. AMRs are equipped with sophisticated sensors that enable them to interpret their environment and navigate around obstacles. One of the key applications of AMRs in warehousing and logistics is inventory management. They can autonomously scan and track inventory levels in real time, reducing the need for manual inventory checks and minimizing the risk of human error.
Articulated Robots (Robotic Arms)
Articulated robots are highly versatile industrial robots used in various industries to perform a wide range of tasks. These robots are designed with a series of interconnected segments, known as links, which are attached through movable joints. They are used to perform repetitive and dangerous tasks that are often too difficult or hazardous for humans to undertake. Typical applications for Articulated Robots include assembly, arc welding, material handling, machine tending, and packaging.
Cobots
A Cobot, or Collaborative Robot, is a robot designed to work alongside humans. They are often designed to take on menial, repetitive tasks, freeing up humans to focus on more important work. Tech companies use cobots for repetitive tasks that require high precision, such as dispensing, labeling, or insertion. Cobot arms are lightweight and easily programmable, allowing them to be assigned to different processes as per organizational needs. Small and mid-sized electronics manufacturers using collaborative robots often see a return on investment in under a year.
Industry Practices: AI & Robotics
A warehousing robot may use a pathfinding algorithm to navigate around the warehouse. A drone may utilize autonomous navigation to return home when it is about to run out of battery. A self-driving car may use a combination of AI algorithms to detect and avoid potential hazards on the road. These examples depict artificially intelligent robots, and AI has proven to be a valuable asset in various industries. Let’s examine some key areas where AI is being used alongside robotics today.
Warehousing & Logistics
Autonomous Mobile Robots (AMRs) are revolutionizing the warehousing and logistics industry by offering efficient and adaptable solutions for material handling and transportation tasks. These advanced robotic systems are equipped with sensors, cameras, and algorithms that enable them to navigate warehouse environments, pick and pack items, and transport goods with precision and accuracy. Moreover, articulated robots are extensively used in manufacturing industries for tasks such as assembly, welding, painting, packaging, and material handling. These robots can accomplish these tasks with high precision and speed, leading to improved productivity and efficiency.
Automobiles
AI in robotics was initially developed to meet the needs of the automobile sector. There are AI-controlled RC cars, dirt bikes, and go-carts used for entertainment, as well as AI-controlled trucks and heavy-duty vehicles for transporting materials. In automobile manufacturing hubs, various tasks such as assembly, screwing, and fitting are executed by AI-controlled robots. The built-in safety features of Cobots enable them to navigate human workspaces safely without causing harm.
Picking & Delivery Robots
Picking robots streamlines human-led order fulfillment, delivering items to workers when they’re needed, thereby enhancing productivity and efficiency. Delivery robots, which may include drones or compact vehicles with secure compartments, are commonly utilized for last-mile delivery or curbside pickup of items such as food orders, groceries, and packages.
Drones
Drones, or unmanned aerial vehicles (UAVs), excel in tasks requiring aerial mobility and remote sensing. They function as autonomous mobile robots for tasks such as inspecting hard-to-reach areas, conducting surveillance, or aiding in search and rescue operations. Additionally, drones are employed in agriculture, aerial photography, search and rescue operations, and various other applications.
Summing up: AI & Robotics
In the next decade, half of cloud data centers will incorporate advanced robots with artificial intelligence (AI) and machine learning (ML) capabilities, resulting in a 30% increase in operating efficiency1. Much of the work carried out in data centers, such as capacity planning, rightsizing virtual machine and container environments, and ensuring efficient resource utilization to avoid “cloud waste,” is tedious, complex, and repetitive. Therefore, integrating robots and AI in data centers can create a more secure, precise, and efficient environment that requires less human intervention.
While the initial integration of artificial intelligence into an existing business model may seem daunting, the benefits typically outweigh the challenges. There is a noticeable increase in productivity and efficiency when AI robots handle repetitive or time-consuming tasks, such as inventory checks and alerting on out-of-stock or misplaced items in retail environments. Furthermore, AI robots can improve quality and accuracy by seeing and understanding their environments, enabling them to complete complex tasks like quality control inspections. Additionally, AI robots contribute to enhanced workplace safety, as AI-enabled robots can learn from human gestures and speech and continuously improve their task performance while working safely alongside employees.
AI is playing a crucial role in transforming various industries, from self-driving cars, and customer service to industrial and service robots, thereby enhancing daily life. This growth presents an opportunity for workforce retraining, reskilling, and investing in knowledge that aligns with the latest technologies. Automating these processes with Artificial Intelligence and Robotics allows organizations to focus on more strategic tasks.
Blog by Neha Mendon 