{"id":35835,"date":"2026-03-27T09:41:16","date_gmt":"2026-03-27T08:41:16","guid":{"rendered":"https:\/\/efa-controls.com\/?p=35835"},"modified":"2026-03-27T10:00:35","modified_gmt":"2026-03-27T09:00:35","slug":"glossary-of-vision-and-autonomous-navigation","status":"publish","type":"post","link":"https:\/\/efa-controls.com\/en\/glossary-of-vision-and-autonomous-navigation\/","title":{"rendered":"Glossary of Vision and Autonomous Navigation"},"content":{"rendered":"<p>[et_pb_section fb_built=&#8221;1&#8243; _builder_version=&#8221;4.16&#8243; custom_padding=&#8221;0px||6px|||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_row _builder_version=&#8221;4.27.4&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.27.4&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.27.6&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;0px|||||&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p>In many industries today, machines no longer simply carry out commands. They \u2018see\u2019, analyse, make decisions\u2026 and sometimes even move around on their own. Behind these capabilities lie two technological pillars: machine vision and <a href=\"https:\/\/efa-controls.com\/en\/our-solutions\/detection-navigation\/autonomous-navigation\/\">autonomous navigation<\/a>.<\/p>\n<p>These are topics we explore on a daily basis in our <a href=\"https:\/\/efa-controls.com\/en\/who-are-we\/engineering-department\/\">design office<\/a>, and one thing often comes up: the terminology is quite technical. So here is a simple, practical glossary to bring a bit of clarity to it all.<\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;4.27.6&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.27.6&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_image src=&#8221;https:\/\/efa-controls.com\/wp-content\/uploads\/2025\/09\/AGV-efa-navigation-autonome.jpg&#8221; alt=&#8221;AGV-efa-navigation-autonome&#8221; title_text=&#8221;AGV-efa-navigation-autonome&#8221; _builder_version=&#8221;4.27.6&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][\/et_pb_image][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;4.27.6&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.27.6&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion open_toggle_text_color=&#8221;#0C71C3&#8243; _builder_version=&#8221;4.27.6&#8243; _module_preset=&#8221;default&#8221; toggle_text_color=&#8221;#0C71C3&#8243; toggle_font=&#8221;|700|||||||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_accordion_item title=&#8221;Autonomous navigation: moving without direct intervention&#8221; open=&#8221;on&#8221; _builder_version=&#8221;4.27.6&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p>Autonomous navigation refers to a system\u2019s ability to move around on its own within a given environment.<br \/>Contrary to popular belief, it is not a single technology, but a coherent set of components:<\/p>\n<ul>\n<li>sensors (cameras, lidar, radar, GPS, etc.)<\/li>\n<li>software capable of understanding the environment<\/li>\n<li>algorithms that determine the route to follow<\/li>\n<li>systems that physically control the vehicle<\/li>\n<\/ul>\n<p>It is this combination that now enables logistics robots to move around warehouses, or industrial machinery to assist operators with their manoeuvres.<\/p>\n<p>[\/et_pb_accordion_item][et_pb_accordion_item title=&#8221;Insight: making sense of data&#8221; title_last_edited=&#8221;off|desktop&#8221; _builder_version=&#8221;4.27.6&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221; open=&#8221;off&#8221;]<\/p>\n<p>Perception is often the first building block of the system.<br \/>In practical terms, this is the moment when the machine transforms raw data into actionable insights. An image becomes an obstacle, a shape becomes a person, an area becomes passable or impassable.<br \/>This is a crucial step: without reliable perception, all subsequent decisions are fragile.<\/p>\n<p>[\/et_pb_accordion_item][et_pb_accordion_item title=&#8221;Location: knowing exactly where you are&#8221; _builder_version=&#8221;4.27.6&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221; open=&#8221;off&#8221;]<\/p>\n<p>An autonomous machine must know where it is at all times.<br \/>To achieve this, several technologies can be combined:<\/p>\n<ul>\n<li>GPS or GNSS for global positioning<\/li>\n<li>inertial sensors to track movement<\/li>\n<li>cameras or lidar to orientate itself within the environment<\/li>\n<li>odometry to measure displacement<\/li>\n<\/ul>\n<p>In industrial environments, reliance on a single sensor is generally avoided. Redundancy is essential to ensure accuracy and robustness.<\/p>\n<p>[\/et_pb_accordion_item][et_pb_accordion_item title=&#8221;Machine vision: when machines learn to see&#8221; _builder_version=&#8221;4.27.6&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221; open=&#8221;off&#8221;]<\/p>\n<p>Machine vision encompasses all the technologies that enable a machine to interpret what is happening around it using visual sensors, most commonly cameras.<br \/>But capturing an image is not enough. The real challenge lies in the processing. Algorithms analyse these images to extract useful information:<\/p>\n<ul>\n<li>detecting an obstacle in a path<\/li>\n<li>identifying an object or piece of equipment<\/li>\n<li>estimating a distance<\/li>\n<li>detecting a human presence<\/li>\n<\/ul>\n<p>In practice, this is what enables, for example, a robot to avoid collisions, or a machine to position a load precisely.<br \/>Beyond performance, it is also a major driver for improving safety and automating tasks that were previously dependent on human intervention.<\/p>\n<p>[\/et_pb_accordion_item][et_pb_accordion_item title=&#8221;Mapping: constructing a representation of the world&#8221; _builder_version=&#8221;4.27.6&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221; open=&#8221;off&#8221;]<\/p>\n<p>Before a machine can navigate intelligently, it must first understand its surroundings.<br \/>Mapping involves creating a digital representation of the environment:<\/p>\n<ul>\n<li>accessible areas<\/li>\n<li>fixed obstacles<\/li>\n<li>waypoints<\/li>\n<\/ul>\n<p>Depending on the situation, this map may be prepared in advance (static) or updated continuously (dynamic).<br \/>It is on this basis that the machine will be able to plan its movements.<\/p>\n<p>[\/et_pb_accordion_item][et_pb_accordion_item title=&#8221;Sensor fusion: combining data for greater reliability&#8221; _builder_version=&#8221;4.27.6&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221; open=&#8221;off&#8221;]<\/p>\n<p>No sensor is perfect.<br \/>A camera can be affected by light conditions, a lidar by certain surfaces, and a GPS by the environment.<br \/>Sensor fusion involves combining multiple sources to achieve a more reliable and comprehensive view. For example:<\/p>\n<ul>\n<li>combining a camera and lidar to better detect obstacles<\/li>\n<li>cross-referencing GPS and inertial data to stabilise positioning<\/li>\n<\/ul>\n<p>This is often what makes the difference between a system that works \u2018in the lab\u2019 and one that is truly robust in the field.<\/p>\n<p>[\/et_pb_accordion_item][et_pb_accordion_item title=&#8221;SLAM: finding your way whilst exploring&#8221; _builder_version=&#8221;4.27.6&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221; open=&#8221;off&#8221;]<\/p>\n<p>SLAM (Simultaneous Localisation and Mapping) is a particularly interesting approach.<br \/>The idea is simple in theory: the machine builds its map whilst simultaneously determining its own position within it.<br \/>This is essential in environments that are:<\/p>\n<ul>\n<li>unknown<\/li>\n<li>changing<\/li>\n<li>unstructured<\/li>\n<\/ul>\n<p>This technology is used in many practical applications, ranging from mobile robots and drones to certain types of industrial equipment.<\/p>\n<p>[\/et_pb_accordion_item][et_pb_accordion_item title=&#8221;Path planning: choosing the right route&#8221; _builder_version=&#8221;4.27.6&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221; open=&#8221;off&#8221;]<\/p>\n<p>Once the machine has mapped its environment and knows where it is, the next step is to decide how to move.<br \/>Path planning involves calculating the optimal route, taking into account:<\/p>\n<ul>\n<li>obstacles<\/li>\n<li>the map<\/li>\n<li>vehicle constraints (speed, turning radius, stability, etc.)<\/li>\n<\/ul>\n<p>It is not just a question of efficiency. It is also a matter of safety and the smooth running of operations.<\/p>\n<p>[\/et_pb_accordion_item][et_pb_accordion_item title=&#8221;Remote working: keeping people in the loop&#8221; _builder_version=&#8221;4.27.6&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221; open=&#8221;off&#8221;]<\/p>\n<p>Full autonomy is not always desirable, nor even possible.<br \/>Teleoperation allows an operator to take control remotely, using video feedback and dedicated interfaces.<br \/>This is particularly useful in:<\/p>\n<ul>\n<li>hazardous environments<\/li>\n<li>complex situations<\/li>\n<li>transitional phases towards greater autonomy<\/li>\n<\/ul>\n<p>In practice, many systems combine autonomy with human supervision.<\/p>\n<p>[\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;4.27.4&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;-20px||||false|false&#8221; custom_padding=&#8221;0px||||false|false&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.27.4&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_video src=&#8221;https:\/\/youtu.be\/JTygdgEMgEg&#8221; _builder_version=&#8221;4.27.6&#8243; _module_preset=&#8221;default&#8221; custom_margin=&#8221;62px||||false|false&#8221; custom_padding=&#8221;||15px||false|false&#8221; global_colors_info=&#8221;{}&#8221;][\/et_pb_video][et_pb_video _builder_version=&#8221;4.27.4&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][\/et_pb_video][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;4.27.6&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;0px||||false|false&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.27.4&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.27.6&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<div class=\"relative basis-auto flex-col -mb-(--composer-overlap-px) pb-(--composer-overlap-px) [--composer-overlap-px:28px] grow flex\">\n<div class=\"flex flex-col text-sm pb-25\">\n<section class=\"text-token-text-primary w-full focus:outline-none [--shadow-height:45px] has-data-writing-block:pointer-events-none has-data-writing-block:-mt-(--shadow-height) has-data-writing-block:pt-(--shadow-height) [&amp;:has([data-writing-block])&gt;*]:pointer-events-auto scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]\" dir=\"auto\" data-turn-id=\"request-WEB:00c60ed5-6b2e-455a-b925-009ff107cef5-0\" data-testid=\"conversation-turn-2\" data-scroll-anchor=\"true\" data-turn=\"assistant\">\n<div class=\"text-base my-auto mx-auto pb-10 [--thread-content-margin:var(--thread-content-margin-xs,calc(var(--spacing)*4))] @w-sm\/main:[--thread-content-margin:var(--thread-content-margin-sm,calc(var(--spacing)*6))] @w-lg\/main:[--thread-content-margin:var(--thread-content-margin-lg,calc(var(--spacing)*16))] px-(--thread-content-margin)\">\n<div class=\"[--thread-content-max-width:40rem] @w-lg\/main:[--thread-content-max-width:48rem] mx-auto max-w-(--thread-content-max-width) flex-1 group\/turn-messages focus-visible:outline-hidden relative flex w-full min-w-0 flex-col agent-turn\">\n<div class=\"flex max-w-full flex-col gap-4 grow\">\n<div class=\"min-h-8 text-message relative flex w-full flex-col items-end gap-2 text-start break-words whitespace-normal outline-none keyboard-focused:focus-ring [.text-message+&amp;]:mt-1\" dir=\"auto\" tabindex=\"0\" data-message-author-role=\"assistant\" data-message-id=\"1b2d3942-c830-499c-b77b-63991e6acc55\" data-message-model-slug=\"gpt-5-3\" data-turn-start-message=\"true\">\n<div class=\"flex w-full flex-col gap-1 empty:hidden\">\n<div class=\"markdown prose dark:prose-invert w-full wrap-break-word light markdown-new-styling\">\n<p><strong>Towards smarter\u2026 and more useful machines<\/strong><\/p>\n<p>What we are seeing today is not merely a technological evolution, but a paradigm shift.<\/p>\n<p>Machines are becoming capable of:<\/p>\n<ul>\n<li>adapting to their environment<\/li>\n<li>assisting operators rather than replacing them<\/li>\n<li>improving safety in practical ways<\/li>\n<li>optimising day-to-day operations<\/li>\n<\/ul>\n<p>Machine vision and autonomous navigation are no longer experimental concepts. They are already at the heart of many projects, and their role will only grow in the years to come.<\/p>\n<p>Understanding these concepts, even at a basic level, already provides a better grasp of the challenges \u2014 and, above all, the opportunities.<\/p>\n<\/div>\n<p><\/div>\n<p><\/div>\n<p><\/div>\n<p><\/div>\n<p><\/div>\n<p><\/section>\n<p><\/div>\n<p><\/div>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In many industries today, machines no longer simply carry out commands. They \u2018see\u2019, analyse, make decisions\u2026 and sometimes even move around on their own. Behind these capabilities lie two technological pillars: machine vision and autonomous navigation. These are topics we explore on a daily basis in our design office, and one thing often comes up: [&hellip;]<\/p>\n","protected":false},"author":13,"featured_media":35859,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","_uf_show_specific_survey":0,"_uf_disable_surveys":false,"footnotes":""},"categories":[271],"tags":[],"class_list":["post-35835","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-standards-and-certifications"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Glossary of Vision and Autonomous Navigation - efa Controls<\/title>\n<meta name=\"description\" content=\"In many industries today, machines no longer simply carry out commands. They \u2018see\u2019, analyse, make decisions\u2026 and sometimes even move around on their own. Underpinning these capabilities are two key technologies: machine vision and autonomous navigation.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/efa-controls.com\/en\/glossary-of-vision-and-autonomous-navigation\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Glossary of Vision and Autonomous Navigation - efa Controls\" \/>\n<meta property=\"og:description\" content=\"In many industries today, machines no longer simply carry out commands. They \u2018see\u2019, analyse, make decisions\u2026 and sometimes even move around on their own. 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