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TechWaTch September 2025


The Rise of Collaborative Robots: Technical and Commercial Insights


By the Staff of IDTechEx


projected to grow from $1.2 billion in 2023 to $29.8 billion by 2035, at a CAGR of 34.5% based on IDTechEx’s analysis. Unlike tra- ditional industrial robots, which operate in isolated, caged environ- ments for safety, cobots work alongside humans, enhancing flexibility and reducing downtime. This shift aligns with Indus-


C


try 5.0, emphasizing human-ma- chine synergy, personalization, and smart factory ecosystems driven by artificial intelligence


ollaborative robots (cobots) have transformed manufac- turing, with their market


(AI), machine vision, and reshor - ing trends (a movement favoured by the Trump administration). IDTechEx’s research report “Col- laborative Robots 2025-2045: Technologies, Players, and Mar- kets” details the technical, com- mercial and regulatory factors and barriers on cobotics.


Industry 5.0 and Cobot Integration


Industry 5.0 prioritizes hu-


man-robot collaboration, moving beyond Industry 4.0’s automa- tion focus. Cobots enable this by performing tasks requiring pre-


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cision and speed while humans handle decision-making and cus- tomization. In automotive manu- facturing, companies like BMW and Ford have integrated cobots into assembly lines, reducing cy- cle times by up to 20% and cut- ting operational costs by 15%. Beyond automotive, electronics (e.g., microchip assembly, wafer transportation), food and bever- age (e.g., packaging), and health- care (e.g., lab automation) sec- tors are adopting cobots, with over 60% of global cobot deploy- ments occurring in these indus- tries. This versatility drives cobot demand, with 73,000 units shipped globally in 2025, a 31% increase from 2024.


Machine Vision Machine vision is critical to


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cobot functionality, enabling re- al-time object recognition and environmental adaptation. High- resolution RGB and time-of- flight (ToF) cameras, like those in TM Robot’s cobots, capture 2D and 3D data, achieving object recognition accuracy of 95% and depth measurement errors below 10%. In electronics, cobots with vision systems inspect mi- crochips, reducing defect rates by 30% compared to human inspec- tion. ToF sensors create detailed depth maps, enabling complex tasks like 3D surface defect de- tection and collision avoidance. For mobile cobots, vision systems integrate with lidar and ultra- sonic sensors, ensuring safe nav- igation in dynamic environ- ments, with obstacle detection response times under 100 ms.


Intelligence and Adaptability AI enhances cobots’ deci-


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sion-making and interaction ca- pabilities. Deep learning algo- rithms, trained on datasets of 10,000+ images, enable cobots to recognize diverse objects with 98% accuracy, critical for ware- house automation where occlu- sion challenges arise (e.g., over- lapping items in bins). Natural language processing (NLP) al-


lows cobots to process verbal commands, though ambient noise reduces accuracy by 15% in factory settings.


AI enhances cobots’ deci- sion-making and interac- tion capabilities. Deep learning algorithms, trained on datasets of 10,000+ images, enable


cobots to recognize diverse objects with 98% accuracy.


Advanced AI models, like


those on Nvidia’s Jetson plat- form, process 1 TB/s of sensor da- ta, enabling real-time adaptive workflows and predictive main- tenance, which cuts downtime by 25%. Universal Robots’ Poly- Scope X platform, leveraging Nvidia’s Isaac libraries, supports complex tasks like autonomous path planning, with a 40% im- provement in task efficiency.


Hardware and Software Innovations


Cobot advancements stem


from modular hardware and soft- ware upgrades rather than new physical designs. Sensor arrays (cameras, ToF, lidar) cost $500 to $2,000 per unit, while Nvidia Jetson modules ($400 to $1,200) provide the computational power for AI tasks. Modular end-of-arm tooling (EoAT), priced at $1,000 to $5,000, allows task-specific customization, such as precision grippers for healthcare applica- tions like medical device assem- bly. Software platforms, like Universal Robots’ PolyScope, op- timize data processing, reducing latency by 30% for real-time ap- plications. These innovations en- able cobots to integrate seam- lessly into existing production lines, with setup times reduced to 2-4 hours.


Commercial Insights The cobot market’s growth


is driven by cost savings and flexibility. A single cobot, priced


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