This is the third of seven articles in the Automation and Robotics series. The others include What is Industrial Automation Technology?, our Robot End Effector Guide, Autonomous Mobile Robots, Programming Robots, Lights-Out Manufacturing, and Commercial Off-the-Shelf Software for Robotics. The history of robotics in industrial applications starts with autonomous mobile robots and robotic arms in the mid-20th century and ends with the AI-enabled robots developing now as robots continue to gain new abilities. A helpful framework is to think of this evolution of robotics in five generations, which we’ll be getting into below. History of Robotics: The Five Generations The industrial robotics timeline is generally divided into five stages. First-generation robots (1950-1967) operated on simple logic without feedback, while second-generation robots (1968-1977) are more programmable. Third-generation robots (1978-1999) can self-program and do tasks that interact with parts. Fourth-generation robots (2000-2019) are capable of advanced computing, while today’s fifth-generation robots are tapping into the power of artificial intelligence. First-Generation Robots (1950-1967) These early entries in the evolution of robots, such as the Unimate, operate on fixed sequences of movements using simple logic and hydraulic or electric actuators without servo controllers. Still popular today – even though their systems do not include sensors or real-time feedback – they are commonly used for performing tasks like material handling and loading or unloading. Second-Generation Robots (1968-1977) Second-generation robots are programmable and controlled by programmable logic controllers. Robots began integrating feedback systems, enabling them to adapt to variable conditions. This advancement made them more precise and usable in complex manufacturing scenarios, including quality inspection and flexible assembly lines. However, they still are too inflexible to adapt to multiple tasks, and they don’t provide diagnostic feedback beyond indicator lights when issues arise. Third-Generation Robots (1978-1999) Featuring self-programming capabilities, these robots interact with operators and the environment. They can be programmed to move along continuous paths or from point to point, and they use programming languages that enable them to interact with computers. These machines work well for “intelligent” tasks where they may need to adjust interactions with the part, like adaptive welding, freehand machining, and assembly. They can also give the operator clear directions on where errors occur. Fourth-Generation Robots (2000-2019) These robots can do advanced computing, logic, and learning. Some are used to work collaboratively alongside humans as cobots (Gasparetto). Fifth-Generation Robots (2020-Today) These last robots in the robotics timeline are still mostly theoretical at this point; they represent fully autonomous robots. These robots depend on AI large language models and deep learning (Benavente). Evolution of Robots: From Simple to Complex While the history of robots stretches over the past century, many forms of robots from each generation remain in use. Simple robotic arms still perform machine unloading and spot welding. Today’s autonomous mobile robots (AMRs) began as two light-sensitive robots with only two vacuum tubes’ worth of processing power. Cobots are designed to work alongside humans to avoid the risk of injury, and adaptive robots use AI to interact and change tasks. Robotic Arms The first step in industrial robot evolution was a robot arm called the Unimate, a hydraulically actuated arm weighing 3.000 lbs created by George Devol in the late 1950s. In 1961, he partnered with Joseph Engelberger, now known as the father of modern robotics, to found Unimation, the first modern robotic startup (Augmentus). The Unimate was based on Devol’s 1954 patent of his Programmed Article Transfer machine. By 1963, the Unimate and Engelberger were featured on “The Tonight Show” with Johnny Carson. The giant machine played golf, poured a beer, and ended the show by leading the band. It took 19 years and more than 35 rejections for Unimation to turn a profit. However, the company was able to start piloting the robot in its first partnership with General Motors, where it started out extracting die-cast parts from machines in Trenton, New Jersey, and graduated to spot welding and workpiece holding in Ohio. However, the company found true success overseas with a partnership between Unimation and Kawasaki Aircraft in 1968. This provided the funding to commercialize the robot arm (Gasperetto). The Unimate was the first industrial-grade robot, and today a typical automobile assembly plant contains hundreds of industrial robots working on automated production lines. While the automotive industry is still the largest user of these robots, representing about 30% of the market (One Million), industrial robots are used for many applications throughout manufacturing, including palletizing, packaging, assembly, disassembly, pick and place, labeling, welding, painting, product inspection, and testing. Today, Asia is the largest industrial robot market, with over 405,000 units installed in 2022 (International Federation of Robotics). One of the largest industrial robotics players in the world, FANUC (Fuji Automatic Numerical Control), is Japanese. AMRs: The First Autonomous Mobile Robots The first autonomous mobile robots were built by W. Grey Walter, a neuroscientist, in the 1940s. Walter’s simple robot “tortoises” are the ancestors of the Roomba and nearly all industrial AMRs. Considered his greatest contribution to the field, these robots were prototyped by Walter in the late 1940s and improved in 1951 with the help of electrical engineer W. J. “Bunny” Warren. Walter gave them the names Elmer and Elsie, a somewhat convoluted acronym of electro-mechanical robots, light sensitive, with internal and external stability. He also gave them a species name of Machina Speculatrix and treated them as a mechanical offshoot of the tortoise family due to their protective, shell-like covers. According to Walter, two vacuum tubes functioned as the two neurons of each robot’s simplified brain. The robot had primitive vision via a rotating photoelectric cell that sought out light sources. A set of three wheels moved it around, and a dome connected to contact switches gave it protection and a means of avoiding obstacles. Elmer and Elsie even docked themselves back into their charging stations when their batteries were low (Tortoise). Unlike automated guided vehicles (AGVs), AMRs navigate the world by responding to their environment without direct guidance. This trait began with Walter’s tortoises and continues to be passed down to robot vacuums and all other AMRs. This begs the question: Just how big has the family of AMRs grown? The global autonomous mobile robots market is expected to reach more than $14 billion by 2033 (Market Demand Forecast), with the global robotic vacuum cleaner market expected to grow to $50.65 billion by 2028 (Fortune Business Insights). Find out more about what today’s AMRs look like in our article on autonomous mobile robots. Collaborative Robots (Cobots) Collaborative robots, or cobots, have been used in manufacturing since the 1990s. Specifically designed to interact with humans in a shared workspace and therefore minimize the risk of accidents or injuries, cobots are equipped with sensors to avoid collisions and ensure passive compliance in the event of unplanned contact. Cobots are relatively lightweight compared to industrial robots and usually portable. Advances in sensors, artificial intelligence, machine vision, and light detection and ranging (LiDAR), among other technologies, are making cobots easier to program, less expensive to deploy, and increasingly flexible in the types of tasks they can safely perform. As of 2023, they accounted for 11% of the robotics market, according to the International Federation for Robotics (Paleit). There are three main safety assurance categories in cobot systems: Speed limits Force feedback External sensing ISO/TS 15066, first introduced in 2006, ensures that all machines classified as cobots include at least one safety feature, such as a safety-rated monitored stop, hand guiding, speed and separation monitoring, or power and force limiting. ISO/TS 15066, published in 2016, specifically addresses the new field of safety requirements for cobots in much more detail. Under TS 15066, the force and speed monitoring of the cobot is set based on application data, human contact area, and workspace hazards. Cobots are often allowed to operate at higher speeds when people are not in the collaborative workspace or hazard zone. Unlike industrial robots, cobots are relatively easy to program, even by workers with no knowledge of programming. Most use hand guiding, also called teaching by demonstration, in which the cobot learns while being guided through the sequence of movements needed to perform a task (Francis). Adaptive Robots In 2019, Flexiv Ltd. launched an adaptive robot, spun out of Stanford University. Named Rizon, the adaptive robotic arm features machine learning (ML) integrated with proprietary force-sensing technology and AI-based computer vision. These provide it with advanced perception and enable real-time adaptiveness that allows it to work in flexible or “uncertain” environments. Unlike other robots, Rizon tolerates position variance, and its “transferable intelligence” allows it to be deployed between similar product lines or tasks. Rizon can be programmed to perform a wide range of industrial tasks, including polishing, parts assembling, precision insertion, and force-based quality testing. Its integrated AI learning system enables it to learn both individual tasks and to combine them to perform more complex ones. Proof-of-concept trials are currently underway in the manufacturing industry, and Flexiv reports that the first applications will include plugging and assembling, curved-surface processing, and flexible picking and sorting (Flexiv). Coding: An Evolution of Robots The Unimate didn’t start out with code programming, but later Unimate models did include it. While coding is still commonly practiced in robotics, no-code robots are also coming back. The Unimate was the first no-code robot. It was programmed by manually setting switches, timers, and motion controls at set positions that were saved on a basic memory system. However, Unimation’s acquisition of Stanford startup Vicarm in the 1970s brought in digital code. This was the first Programmable Universal Machine for Assembly, better known today as the PUMA. After the shift to this design methodology, translating software between systems became a consistent pain point for engineers (Gasparetto). To solve the language barriers today, designers lean toward no-code programming. A person with a teach pendant can show a robot arm what to do by physically guiding the end effector, or they can use pre-made code blocks to instruct the robot. If a robot is equipped with a camera and the right software, it can watch human movements to learn what to do (Greenberg). This simplification shows how the robotics industry is closing the skills gap. Moving Forward in Robot Evolution Throughout the history of robotics, robots have steadily gained complexity and autonomy, advancing into more helpful tools that make industrial automation safer, faster, and more accurate. With the development of no code technologies, these machines are also becoming more accessible to new users. Our shared history with robotics may hint at our continued future. Once thought of as products, and then perhaps free agents and even colleague cooperators, robots are becoming more integrated into our everyday lives. The future of robotics holds such opportunities as: No-code robotic arm sequencing, lowering the skills gap needed to implement robots in industrial application. Smarter AMRs that can navigate environments and perform more complicated tasks, all with less human input. Bipedal and quadruped robots that can act – and even think – like us, fulfilling our dreams of true artificial companions. Given the continual advancements in AI, machine learning, and sensing technologies, the Rizon robot is very likely a precursor to more adaptive robots. The next article in our series on automation examines autonomous mobile robots, the descendants of automated guided vehicles. Read the Automation and Robotics Series What is Industrial Automation Technology? Robotic End Effector Guide: End of Arm Tooling Types, Trends, & More Autonomous Mobile Robots Programming Robots Lights-Out Manufacturing or Processes? Commercial Off-the-Shelf Software for Robotics Sources “Flexiv Ushers in 3rd Gen Robot with Launch of Adaptive Robot Arm.” (2019, April 2). PR Newswire. Accessed July 14, 2025. Francis, Sam. “Safety standards and innovations in human-robot collaboration.” (2025, July 11). Robotics and Automation News. Accessed July 11, 2025. Gasparetto, Alessandro, and Lorenzeo Scalera. “From the Unimate to the Delta Robot: The Early Decades of Industrial Robotics: Proceedings of the 2018 HMM IFToMM Symposium on History of Machines and Mechanisms." (2019, January). ResearchGate. Accessed July 11, 2025. “Global Autonomous Mobile Robots Market Size, Share, Trends, & Growth Forecast Report Segmented By Component (Hardware, Software, and Services), Type, Battery Type, Application, Payload Capacity, End Use, and Region (North America, Europe, Asia Pacific, Latin America, and Middle East & Africa), Industry Analysis From 2024 to 2033.” (2025, April). Market Data Forecast. Accessed August 14, 2025. Greenberg, Benjamin. “No-Code Development for Robots.” (2021, August 25.) Southwest Research Institute. Accessed July 11, 2025. “One Million Robots Work in Car Industry Worldwide – New Record." (2023, March 22). International Federation of Robotics. Accessed July 11, 2025. Paleit, Andreas. "March of the Cobots: The Technology Lowering the Barrier to Automation.” (2025, May 27). Financial Times. Accessed July 11, 2025. “Robotic Vacuum Cleaner Market Size, Share & Industry Analysis, By Type (Floor Vacuum Cleaner, Window Vacuum Cleaner, Pool Vacuum Cleaner), By Application (Household and Commercial), By Operation Mode (Self-Drive & Remote Control), By Distribution Channel (Online & Offline), By Price (Below USD 150, USD 150-300, USD 300-500, Above USD 500) and Regional Forecast, 2021-2028.” (2025, July 28). Fortune Business Insights. Accessed August 14, 2025. Rosen, Rebecca J. “Unimate: The Story of George Devol and the First Robotic Arm.” (2011, August 16). The Atlantic. Accessed August 14, 2025. ““Tortoise” Mobile Robot.” Smithsonian Museum. Accessed July 11, 2025. “World Robotics: Industrial Robots 2023.” (2023). International Federation of Robotics. Accessed August 14, 2025.
The two categories of robots used in manufacturing are industrial grade robots and collaborative robots (cobots); adaptive robots were only introduced in 2019. This article looks at how each new generation of robots is more flexible and intelligent than its predecessor.
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