{"id":541198,"date":"2025-07-14T14:11:17","date_gmt":"2025-07-14T14:11:17","guid":{"rendered":"https:\/\/www.capgemini.com\/co-es\/?p=541198&#038;preview=true&#038;preview_id=541198"},"modified":"2025-07-14T14:13:24","modified_gmt":"2025-07-14T14:13:24","slug":"computer-vision-and-robotics-teaching-machines-to-see-and-act","status":"publish","type":"post","link":"https:\/\/www.capgemini.com\/co-es\/insights\/expert-perspectives\/computer-vision-and-robotics-teaching-machines-to-see-and-act\/","title":{"rendered":"Computer vision and robotics: Teaching machines to see and act\u00a0"},"content":{"rendered":"\n<header class=\"wp-block-cg-blocks-hero-blogs header-hero-blogs\"><div class=\"container\"><div class=\"hero-blogs\"><div class=\"hero-blogs-content-wrapper\"><div class=\"row\"><div class=\"col-12\"><div class=\"header-title\"><h1>Computer vision and robotics: Teaching machines to see and act\u00a0<\/h1><\/div><\/div><\/div><\/div><div class=\"hero-blogs-bottom\"><div class=\"header-author\"><div class=\"author-img\"><img decoding=\"async\" src=\"https:\/\/www.capgemini.com\/co-es\/wp-content\/uploads\/sites\/25\/2025\/07\/Mark-Blanchon.jpg?w=200&amp;quality=10\" alt=\"Marc Blanchon\" loading=\"lazy\"\/><\/div><div class=\"author-name-date\"><h5 class=\"author-name\">Marc Blanchon<\/h5><h5 class=\"blog-date\">Jul 10, 2025<\/h5><\/div><\/div><div class=\"brand-image\"> <\/div><\/div><\/div><\/div><\/header>\n\n\n\n<section class=\"wp-block-cg-blocks-group undefined section section--article-content\"><div class=\"article-main-content\"><div class=\"container\"><div class=\"row\"><div class=\"col-12 col-md-1\"><nav class=\"article-social\"><ul class=\"social-nav\"><li class=\"ip-order-fb\"><a href=\"https:\/\/www.facebook.com\/sharer\/sharer.php?u=https:\/\/www.capgemini.com\/?p=1143533\" target=\"_blank\" rel=\"noopener noreferrer\" title=\"abrir en una nueva ventana\"><i aria-hidden=\"true\" class=\"icon-fb\"><\/i><span class=\"sr-only\">Facebook<\/span><\/a><\/li><li class=\"ip-order-li\"><a href=\"https:\/\/www.linkedin.com\/shareArticle?url=https:\/\/www.capgemini.com\/?p=1143533\" target=\"_blank\" rel=\"noopener noreferrer\" title=\"abrir en una nueva ventana\"><i aria-hidden=\"true\" class=\"icon-li\"><\/i><span class=\"sr-only\">Linkedin<\/span><\/a><\/li><\/ul><\/nav><\/div><div class=\"col-12 col-md-11 col-lg-10\"><div class=\"article-text article-quote-text\">\n<h2 class=\"wp-block-heading\" id=\"h-robotics-and-computer-vision-are-two-complex-fields-that-have-existed-for-decades-yet-in-the-past-ten-years-things-have-shifted-and-continue-to-evolve-rapidly\">Robotics and computer vision are two complex fields that have existed for decades. Yet in the past ten years, things have shifted &#8211; and continue to evolve rapidly. <\/h2>\n\n\n\n<p>Robotics, once limited to basic automation and repeatable motions in isolated environments, is now expanding to address broader challenges. Traditional industrial robots operated at a safe distance, executing predefined tasks in static environments.&nbsp;<\/p>\n\n\n\n<p>Meanwhile, computer vision, once fragmented into subdomains like image processing, geometry, and optics, has undergone a transformation. The rise of artificial intelligence has unified these domains and propelled computer vision to the forefront of innovation.&nbsp;<\/p>\n\n\n\n<p>Today, a new convergence is taking shape \u2014 one that merges perception, reasoning, and physical action into integrated systems. This is the promise of Physical AI: the ability for machines not only to process information intelligently, but to act upon it in the real world. And at the heart of this evolution lies the rise of Vision-Language-Action (VLA) models \u2014 architectures that combine what a robot sees, what it understands through language, and how it decides to move or manipulate its environment accordingly.&nbsp;<\/p>\n\n\n\n<p>We\u2019re already seeing early signs of this shift. For example, new-generation robots can now interpret a voice command like \u201cpick up the red cable next to the panel,\u201d visually locate the object in context, and perform the action \u2014 all thanks to VLA architectures that connect perception to natural language and motor execution.&nbsp;<\/p>\n\n\n\n<p>In industrial settings, robots once confined to repetitive welding behind safety cages are now operating side by side with humans \u2014 navigating busy factory floors, identifying parts, adapting to shifting workflows, and contributing dynamically to production without the need for constant reprogramming.&nbsp;<\/p>\n\n\n\n<p>Though often treated as separate disciplines, robotics and vision are deeply intertwined. Today\u2019s robotics is no longer just about repetition \u2014 it&#8217;s about adaptability in dynamic, unpredictable environments and what better way to enable intelligent action than through perception? After all, around 80% of the information processed by the human brain comes from visual cognition. It\u2019s only logical to equip robots with powerful vision systems if we want them to act meaningfully in the world.&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-when-vision-meets-movement-nbsp\"><strong>When vision meets movement<\/strong>&nbsp;<\/h2>\n\n\n\n<p><em>The fusion of sight and motion is redefining how robots interact with the world around them.<\/em>&nbsp;<\/p>\n\n\n\n<p>A robot that interacts intelligently and adapts to its environment relies primarily on its ability to perceive, interpret, and understand the world around it. Much like humans reconstruct their environment from limited focal information, vision systems must extract meaning from incomplete, noisy, and ambiguous data.&nbsp;<\/p>\n\n\n\n<p>In both humans and machines, vision is not passive \u2014 it\u2019s an active process of interpretation, selection, and decision-making. And this principle applies directly to robotics. An efficient humanoid robot must incorporate biomimetic principles, enabling it to understand and act upon its surroundings as humans do.&nbsp;<\/p>\n\n\n\n<p>That\u2019s why giving robots the ability to \u201csee\u201d is not just an enhancement \u2014 it\u2019s a requirement for safe navigation, interaction, and decision-making. In collaborative environments, such as modern industrial settings where humans and robots coexist, real-time perception is essential to avoid collisions and adapt to changing conditions.&nbsp;<\/p>\n\n\n\n<p>We are moving from conventional robotics and siloed vision systems to intelligent robotics powered by integrated perception. Where traditional robots acted blindly within controlled environments, AI-driven robotics must now interpret complex scenes and operate in the real world \u2014 fluid, noisy, and often unpredictable.&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-applications-across-industries-nbsp\"><strong>Applications across industries<\/strong>&nbsp;<\/h2>\n\n\n\n<p><em>From factories to farms, vision-powered robots are reshaping work across every sector.<\/em>&nbsp;<\/p>\n\n\n\n<p>Thanks to breakthroughs in both robotics and computer vision, it&#8217;s increasingly plausible to anticipate radical changes in how we design, manufacture, and operate across countless industries.&nbsp;<\/p>\n\n\n\n<p>Many tasks that are still carried out manually \u2014 repetitive, sometimes non-standard, and often labor-intensive \u2014 could be augmented or replaced by intelligent robots. For instance, repetitive part handling is physically demanding and costly. Delegating such tasks to machines allows humans to focus on less exhausting, more meaningful work.&nbsp;<\/p>\n\n\n\n<p>A more complex case is visual inspection. Today, for each inspection station, there&#8217;s a dedicated process \u2014 sometimes manual, sometimes automated, often a mix of both. But with computer vision and robotics, we can envision versatile, autonomous visual inspection systems capable of adapting across product types and conditions.&nbsp;<\/p>\n\n\n\n<p>And these examples extend well beyond quality control in operations: think of hazardous operations, where robotic systems can prevent human exposure to danger, or required round-the-clock tasks, where robots can operate continuously without fatigue avoiding dangerous error.&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-from-perception-to-autonomy-nbsp\"><strong>From perception to autonomy<\/strong>&nbsp;<\/h2>\n\n\n\n<p><em>Seeing is just the beginning \u2013 true autonomy emerges when machines understand what they see.<\/em>&nbsp;<\/p>\n\n\n\n<p>Attaching cameras to a robot and detecting a few objects doesn&#8217;t make it autonomous. While the progress in computer vision is undeniable, real autonomy lies in the transition from raw detection to contextual scene understanding.&nbsp;<\/p>\n\n\n\n<p>Detection allows a system to identify known elements \u2014 objects, markers, obstacles \u2014 typically in controlled environments. But the real world is rarely so clean. In industrial settings, in cities, or in natural environments, robots face variability, ambiguity, and noise. That\u2019s where true autonomy begins: not just recognizing what\u2019s in front of them, but understanding what it means, how it changes, and what to do about it.&nbsp;<\/p>\n\n\n\n<p>This shift requires a deeper integration of perception, cognition, and action. For example, in a fulfillment center scenario, a robot must move from:&nbsp;<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Identifying a box to understanding that it\u2019s fragile and just fell off a conveyor belt&nbsp;<\/li>\n\n\n\n<li>Seeing a person to predicting their trajectory and adjusting behavior safely&nbsp;<\/li>\n\n\n\n<li>Detecting a machine to interpreting that it\u2019s idle and requires assistance&nbsp;<\/li>\n<\/ul>\n\n\n\n<p>It\u2019s about reasoning, prioritizing, and reacting in real time, based on complex visual input. And this isn&#8217;t just a matter of better algorithms \u2014 it requires:&nbsp;<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Multi-modal fusion (combining vision with sound, touch, or contextual data)&nbsp;<\/li>\n\n\n\n<li>Learning on the edge (to adapt quickly to new situations without retraining centrally)&nbsp;<\/li>\n\n\n\n<li>Generalization (being able to apply learned behaviors to unseen environments)&nbsp;<\/li>\n<\/ul>\n\n\n\n<p>In other words, we move from reactive systems to proactive agents capable of operating in the unknown. This is especially vital in dynamic or high-stakes environments \u2014 from co-working with humans on factory floors to exploring disaster zones or navigating crowded streets.&nbsp;<\/p>\n\n\n\n<p>Autonomy is not binary \u2014 it\u2019s a spectrum. And the closer we get to human-like understanding of space, intent, and consequence, the more fluid, intelligent, and reliable robotic behavior becomes.&nbsp;<\/p>\n\n\n\n<p>Ultimately, perception is the lens but autonomy is the leap.&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-from-seeing-to-thinking-and-doing-the-rise-of-physical-ai-nbsp\"><strong>From seeing to thinking and doing: The rise of physical AI<\/strong>&nbsp;<\/h2>\n\n\n\n<p><em>Perception alone is not enough \u2014 intelligent robots must connect vision, language, and action into one seamless cognitive loop.<\/em>&nbsp;<\/p>\n\n\n\n<p>A new wave of intelligent robotics is taking shape \u2014 one where vision alone isn\u2019t enough. The frontier is now Physical AI: systems that combine what a robot sees, what it understands, and what it does.&nbsp;At the heart of this evolution are Vision-Language-Action (VLA) models, which merge visual perception, natural language understanding, and physical execution into one unified architecture. This enables robots to go beyond detecting objects \u2014 they can now follow instructions, understand goals, and adapt their actions accordingly.&nbsp;<\/p>\n\n\n\n<p>These models open the door to more intuitive, adaptive robotics in factories, hospitals, and homes \u2014 creating machines that collaborate, learn, and act in complex environments. While still an emerging field, Physical AI is rapidly becoming the foundation of truly intelligent autonomy.&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-challenges-in-the-loop-nbsp\"><strong>Challenges in the loop<\/strong>&nbsp;<\/h2>\n\n\n\n<p><em>More intelligence means more complexity \u2013 and a greater need for safety, ethics, and control.<\/em>&nbsp;<\/p>\n\n\n\n<p>With increasing perceptual capabilities come significant challenges. One key issue is robustness: computer vision systems can be vulnerable to variations in lighting, background, and unexpected events.&nbsp;<\/p>\n\n\n\n<p>There\u2019s also the challenge of trust and explainability. When robots make decisions based on complex visual input, humans must understand why and how those decisions are made \u2014 especially in safety-critical environments.&nbsp;<\/p>\n\n\n\n<p>Additionally, there&#8217;s a computational burden: processing high-resolution video streams in real time, running deep models at the edge, and doing so efficiently and sustainably is still an ongoing technical frontier.&nbsp;<\/p>\n\n\n\n<p>Moreover, and perhaps most importantly from an ethical perspective, we must ask: What tasks should we delegate to machines? How do we ensure that intelligent robots augment human work in responsible ways?&nbsp;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-shaping-the-future-together-nbsp\"><strong>Shaping the future together<\/strong>&nbsp;<\/h2>\n\n\n\n<p><em>Empowering the next generation of robots starts with the choices we make today.<\/em>&nbsp;<\/p>\n\n\n\n<p>The fusion of computer vision and robotics is one of the most promising frontiers in technological innovation. It offers a glimpse into a future where machines are not just tools but perceptive collaborators.&nbsp;<\/p>\n\n\n\n<p>To realize this future, organizations must invest not only in algorithms and hardware, but in talent, infrastructure, and governance. It requires cross-disciplinary collaboration \u2014 between engineers, ethicists, designers, and decision-makers.&nbsp;<\/p>\n\n\n\n<p>Those who act now \u2014 by embracing intelligent technologies, fostering experimentation, and building trust \u2014 will <a href=\"https:\/\/www.capgemini.com\/about-us\/who-we-are\/innovation-ecosystem\/ai-robotics-experiences-lab\/\" target=\"_blank\" rel=\"noreferrer noopener\">shape the future of robotics<\/a> not as a distant vision, but as a practical, human-centered reality.&nbsp;<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/section>\n\n\n\n<section class=\"wp-block-cg-blocks-wrapper-people-slider section section--expert-slider wrapper-people-slider undefined\"><div class=\"container\"><div class=\"content-title\"><h2 data-maxlength=\"34\" class=\"people-heading-title\">Meet the author<\/h2><\/div><\/div><div class=\"slider slider-boxed\"><div class=\"container\"><div class=\"slider-window\"><div class=\"slider-list\">\t\t<div class=\"slide\">\n\t\t\t<div class=\"box\">\n\t\t\t\t<div class=\"row\">\n\t\t\t\t\t<div class=\"col-md-6 col-lg-4 box-img-wrapper\">\n\t\t\t\t\t\t<img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/www.capgemini.com\/co-es\/wp-content\/uploads\/sites\/25\/2025\/07\/Mark-Blanchon.jpg\" alt=\"Marc Blanchon\"\/>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"col-md-6 col-lg-8 box-inner\">\n\t\t\t\t\t\t<div class=\"row title-social-media-header\">\n\t\t\t\t\t\t\t<div class=\"col-md-12 col-lg-6 mbl-social-icon\">\n\t\t\t\t\t\t\t\t<ul class=\"social-nav\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"col-md-12 col-lg-6 box-container\">\n\t\t\t\t\t\t\t\t<div class=\"box-title\">\n\t\t\t\t\t\t\t\t\t<h3 class=\"people-profile-title\">Marc Blanchon<\/h3>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span>Computer Vision Specialist<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"col-md-12 col-lg-6 social-box-container dkt-social-icon\">\n\t\t\t\t\t\t\t\t<ul class=\"social-nav\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"people-info\">Marc is a computer vision specialist and pre-sales architect at Hybrid Intelligence, Capgemini Engineering. With 9+ years of experience and a Ph.D., he leads technical teams in designing and industrializing AI-driven Computer Vision solutions across industries. He is passionate about AI and actively contribute to research, offer development, and pre-sales activities to support clients and innovation initiatives.<\/div>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div><\/div><\/div><div class=\"slider-nav\"><button class=\"slider-prev inactive\" aria-label=\"Slider-previous\" tabindex=\"-1\"><\/button><ul class=\"slider-paginator\"><\/ul><button class=\"slider-next\" aria-label=\"Slider-next\"><\/button><\/div><\/div><\/section>\n","protected":false},"excerpt":{"rendered":"<p>Robotics and computer vision are two complex fields that have existed for decades. Yet in the past ten years, things have shifted \u2014 and continue to evolve rapidly.<\/p>\n","protected":false},"author":263,"featured_media":541199,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"cg_dt_proposed_to":[],"cg_seo_hreflang_relations":"[]","cg_seo_canonical_relation":"","cg_seo_hreflang_x_default_relation":"","cg_dt_approved_content":true,"cg_dt_mandatory_content":false,"cg_dt_notes":"","cg_dg_source_changed":true,"cg_dt_link_disabled":false,"_yoast_wpseo_primary_brand":"","_jetpack_memberships_contains_paid_content":false,"footnotes":"","featured_focal_points":""},"categories":[1],"tags":[256,225,288,165],"brand":[],"service":[],"industry":[],"partners":[],"blog-topic":[163],"content-group":[],"class_list":["post-541198","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized","tag-artificial-intelligence","tag-client-story","tag-data","tag-innovation","blog-topic-innovation"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v22.8 (Yoast SEO v22.8) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Computer vision and robotics: Teaching machines to see and act\u00a0 - Capgemini Colombia<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.capgemini.com\/co-es\/insights\/expert-perspectives\/computer-vision-and-robotics-teaching-machines-to-see-and-act\/\" \/>\n<meta property=\"og:locale\" content=\"es_MX\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Computer vision and robotics: Teaching machines to see and act\u00a0\" \/>\n<meta property=\"og:description\" content=\"Robotics and computer vision are two complex fields that have existed for decades. 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