Top 5 robot trends for 2024: IFR

The International Federation of Robotics (IFR) has identified five key trends in robotics for 2024.

According to the IFR, the stock of operational robots around the globe has hit a new record of about 3.9 million units, with the demand being driven by a number of technological innovations.

1. Artificial intelligence and machine learning

The trend of using AI in robotics and automation keeps growing, and the emergence of generative AI opens up new solutions. This subset of AI is specialised to create something new from things it’s learned via training, and has been popularised by tools such as ChatGPT. Robot manufacturers are developing generative AI-driven interfaces that allow users to program robots more intuitively by using natural language instead of code. Workers will no longer need specialised programming skills to select and adjust the robot’s actions.

Another example is predictive AI analysing robot performance data to identify the future state of equipment. Predictive maintenance can save manufacturers machine downtime costs. Machine learning algorithms can also analyse data from multiple robots performing the same process for optimisation. In general, the more data a machine learning algorithm is given, the better it performs.

2. Cobots expanding to new applications

Human–robot collaboration continues to be a major trend in robotics. Rapid advances in sensors, vision technologies and smart grippers allow robots to respond in real time to changes in their environment and thus work safely alongside human workers.

Collaborative robot applications offer a new tool for human workers, relieving and supporting them. They can assist with tasks that require heavy lifting, repetitive motions or work in dangerous environments.

A recent market development is the increase of cobot welding applications, driven by a shortage of skilled welders. This demand shows that automation is not causing a labour shortage but rather offers a means to solve it. Collaborative robots will therefore complement — not replace — investments in traditional industrial robots which operate at much faster speeds and will therefore remain important for improving productivity in response to tight product margins.

3. Mobile manipulators

Mobile manipulators — so called ‘MoMas’ — are automating materials handling tasks in industries such as automotive, logistics or aerospace. They combine the mobility of robotic platforms with the dexterity of manipulator arms. This enables them to navigate complex environments and manipulate objects, which is crucial for applications in manufacturing.

4. Digital twins

Digital twin technology is increasingly used as a tool to optimise the performance of a physical system by creating a virtual replica. Since robots are more and more digitally integrated into factories, digital twins can use their real-world operational data to run simulations and predict likely outcomes. Because the twin exists purely as a computer model, it can be stress-tested and modified with no safety implications while saving costs. All experimentation can be checked before the physical world itself is touched.

5. Humanoid robots

Robotics is witnessing significant advancements in humanoids, designed to perform a wide range of tasks in various environments. The human-like design with two arms and two legs allows the robot to be used flexibly in work environments that were actually created for humans. It can therefore be easily integrated, for example, into existing warehouse processes and infrastructure.

The Chinese Ministry of Industry and Information Technology (MIIT) recently published detailed goals for the country’s ambitions to mass-produce humanoids by 2025. The MIIT predicts humanoids are likely to become another disruptive technology — similar to computers or smartphones — that could transform the way we produce goods and the way humans live.

The potential impact of humanoids on various sectors makes them an exciting area of development, but their mass market adoption remains a complex challenge. Costs are a key factor and success will depend on their return on investment competing with well-established robot solutions like mobile manipulators, for example.

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