Table of Content
- Key Drivers of Robotic Implementation in Industries
- Top Trends in the Robotics Industry in 2024
- Key Takeaways
- FAQs
Stepping into 2024, the global robotics industry is edging closer to the feat of installing 600,000 units annually worldwide.
This growth isn't just a statistic; it reflects the increasing relevance of robotics across various sectors. From manufacturing to healthcare, robotics is reshaping how we work and live.
The implementation of robotics in different industries is revolutionising operations, streamlining processes, encouraging collaboration, and embracing digitalisation, all to deliver substantial advantages and drive automation further.
Key Drivers of Robotic Implementation in Industries
Simplification, collaboration, and digitalisation are essential factors driving the successful implementation of robotics across various industries.
These drivers play a pivotal role in adapting to changing consumer trends, and diverse product demands, and overcoming challenges posed by trade barriers.
Simplification:
- Programming and installation of robots become much easier.
- How this looks in practice: Digital sensors combined with smart software allow direct teaching methods, so-called “Programming by Demonstration”.
- The task that the robot arm is to perform is first executed by a human: He takes the robot arm and hand-guides it through the movements.
- This data is then transformed by the software into the digital program of the robot arm.
- In the future, machine learning tools will further enable robots to learn by trial-and-error or by video demonstration and self-optimise their movements.
Collaboration:
- The range of collaborative applications offered by robot manufacturers continues to expand.
- Currently, shared workspace applications are the most common. Robots and workers operate alongside each other, completing tasks sequentially.
- Applications in which the human and the robot work at the same time on the same part are even more challenging.
- Research and Development (R&D) focuses on methods to enable robots to respond in real-time. Just like two human workers would collaborate, the R&D teams want them to adjust their motion to their environment, allowing for a true responsive collaboration.
- These solutions include voice, gesture, and recognition of intent from human motion.
- With the technology of today, human-robot collaboration has already a huge potential for companies of all sizes and sectors. Collaborative operations will complement investments in traditional industrial robots.
Digitalisation:
- Industrial robots are the central components of digital and networked production as used in Industry 4.0.
- This makes it all the more important for them to be able to communicate with each other - regardless of the manufacturer. The “OPC Robotics Companion Specification”, which has been developed by a joint working group of the VDMA and the Open Platform Communications Foundation (OPC), defines a standardised generic interface for industrial robots and enables industrial robots to connect to the Industrial Internet of Things (IoT).
- The digital connectivity of robots with e.g. cloud technology is also an enabler for new business models.
- Robot leasing for example - called Robots-as-a-Service - has advantages that might be especially attractive for small and medium-sized enterprises (SMEs): no committed capital, fixed costs, automatic upgrades, and no need for highly qualified robot operators.
- Overall, these drivers enable companies to react to changing requirements and innovate in response to new consumer trends, demand for product variety, and challenges from trade barriers.
- They pave the way for more flexibility in production and contribute to the advancement of smart robotics and automation.
Top Trends in the Robotics Industry in 2024
The robotics industry in 2024 is experiencing significant advancements and trends.
Here’s an overview of the top robotics trends of 2024:
Humanoid Robots:
- Humanoids are sophisticated robots designed to perform tasks in human-like environments, such as logistics and customer service.
- Humanoids are designed to mimic human movements and interactions, with some models capable of recognising emotions through facial expressions, enhancing their suitability for customer service roles.
- Despite challenges, humanoids are increasingly finding applications in healthcare, where they assist with patient care and rehabilitation exercises.
Digital Twin:
- Digital twin technology creates virtual replicas of physical systems, enabling simulations and optimisations without physical trials.
- Digital twins offer real-time insights into the performance of physical robotic systems, enabling predictive maintenance and optimisation strategies that minimise downtime and maximise efficiency.
- Digital twins are also utilised in robotics for scenario planning, allowing engineers to simulate different operating conditions and optimise robot behaviour accordingly.
Mobile Manipulators:
- Mobile manipulators combine the mobility of autonomous robots with the dexterity of robotic arms, ideal for manufacturing and logistics tasks.
- Mobile manipulators are equipped with advanced sensors and actuators that enable them to navigate challenging terrains and environments, such as warehouses and factories, with precision and agility.
- Mobile manipulators are increasingly employed in disaster response scenarios, where they assist in search and rescue missions by navigating hazardous environments and manipulating debris.
Artificial Intelligence:
- AI integration enhances robotic capabilities in sectors like retail and manufacturing, aiding in advanced object recognition, autonomous navigation, and decision-making.
- AI-driven robots are increasingly capable of understanding and responding to natural language commands, enabling more intuitive and seamless interactions with humans in various settings.
- Machine learning algorithms enable robots to continuously improve their performance through data analysis, with some models achieving levels of accuracy and efficiency surpassing human capabilities.
- Machine learning techniques are also being applied in robotics for adaptive grasping, enabling robots to manipulate objects with varying shapes, sizes, and textures.
- AI algorithms are also being applied in robotics for task planning and scheduling, optimising robot movements to maximise efficiency and minimise idle time.
Collaborative Robots (Cobots):
- Cobots work alongside humans, assisting with heavy lifting, repetitive motions, or hazardous tasks, enhancing productivity and safety.
- Increasingly used in manufacturing and logistics, cobots exemplify emerging trends in robotics, emphasising collaborative and synergistic human-robot interaction.
- Collaborative robots are equipped with advanced safety features, such as force sensing and collision avoidance, that enable them to work alongside humans without the need for physical barriers or cages.
- Cobots are also being utilised in healthcare settings, where they assist medical professionals with tasks such as patient lifting and rehabilitation exercises.