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Service robot
Service robot
Service robot
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Video: A type of service robot which became popular with the rise of the smart home technology is the robotic lawn mower, here applied in a small garden

Service robots assist human beings, typically by performing a job that is dirty, dull, distant, dangerous or repetitive (four Ds of robotization). They typically are autonomous and/or operated by a built-in control system, with manual override options. The term "service robot" does not have a strict technical definition. The International Organization for Standardization defines a “service robot” as a robot “that performs useful tasks for humans or equipment excluding industrial automation applications”.[1]

The first industrial robot arm, "Unimate," was developed by Joseph F. Engelberger, known as the "father of the robot arm," using George Devel.[2]

According to ISO 8373 robots require “a degree of autonomy”, which is the “ability to perform intended tasks based on current state and sensing, without human intervention”. For service robots this ranges from partial autonomy - including human-robot interaction - to full autonomy - without active human robot intervention. The International Federation of Robotics (IFR) statistics for service robots therefore include systems based on some degree of human robot interaction or even full tele-operation as well as fully autonomous systems.

Service robots are categorized according to personal or professional use. They have many forms and structures as well as application areas.

Types

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The possible applications of robots to assist in human chores is widespread. At present there are a few main categories that these robots fall into.

Industrial

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Industrial service robots can be used to carry out simple tasks, such as examining welding, as well as more complex, harsh-environment tasks, such as aiding in the dismantling of nuclear power stations. Industrial robots have been defined by the International Federation of Robotics as "an automatically controlled, reprogrammable, multipurpose manipulator programmable in three or more axes, which may be either fixed in place or mobile for use in industrial automation applications".[3]

Frontline Service Robots

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Service robots are system-based autonomous and adaptable interfaces that interact, communicate and deliver service to an organization's customers.[4]

Domestic

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Main article: Domestic robot
The Roomba vacuum cleaner is one of the most popular domestic service robots.[citation needed]

Domestic robots perform tasks that humans regularly perform in non-industrial environments, like people's homes such as for cleaning floors, mowing the lawn and pool maintenance.[5] People with disabilities, as well as people who are older, may soon be able to use service robots to help them live independently.[6] It is also possible to use certain robots as assistants or butlers[citation needed].

Scientific

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Robotic systems perform many functions such as repetitive tasks performed in research. These range from the multiple repetitive tasks made by gene samplers and sequencers, to systems which can almost replace the scientist in designing and running experiments, analysing data and even forming hypotheses. The ADAM at the University of Aberystwyth in Wales can "[make] logical assumptions based on information programmed into it about yeast metabolism and the way proteins and genes work in other species. It then set about proving that its predictions were correct."[7]

Autonomous scientific robots perform tasks which humans would find difficult or impossible, from the deep sea to outer space. The Woods Hole Sentry can descend to 4,500 metres and allows a higher payload as it does not need a support ship or the oxygen and other facilities demanded by human piloted vessels.[8] Robots in space include the Mars rovers which could carry out sampling and photography in the harsh environment of the atmosphere on Mars.

Food Delivery Robots

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Food delivery robots are a type of service robot. In addition to delivering ordered meals from a restaurant’s kitchen to customers’ tables, these robots can also collect leftover dishes and trays after the meal. Food delivery robots first emerged in China in the mid-2010s. During the COVID-19 pandemic in 2019, their use quickly spread across various regions to reduce human contact in customer service.

Although primarily used in restaurants, food delivery robots are also employed in other environments such as hospitals and hotels, where they are used to transport various items. Their main function is to deliver freshly prepared dishes from the kitchen to customers. After restaurant staff designate the delivery location, the robot navigates to the customer's seat to complete the delivery.

These robots are typically capable of autonomous movement. While some rely on magnetic tape on the floor to navigate, others utilize cameras or LiDAR sensors to map indoor routes and determine their position using SLAM (Simultaneous Localization and Mapping).[9] In factory settings, mobile robots generally follow pre-defined routes, where magnetic tape alone is sufficient. However, in restaurants, the frequent cleaning of floors may cause the tape to peel off, and foot traffic patterns tend to be less predictable. Therefore, robots equipped with SLAM technology often perform more efficiently in such environments.

Some delivery robots use cameras to determine their location—by placing special markers or stickers on the ceiling, the robots can use infrared sensors to identify their position through reflected signals. These robots may also be equipped with ultrasonic sensors to detect obstacles. In some cases, food delivery robots are integrated with tabletop tablets, allowing customers to place orders directly. Certain models are even equipped with basic emotional expression capabilities.[10]

Examples of service robot

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Cognitive Service Robot Cosero
Cognitive Service Robot Cosero[11]

See also

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References

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Further reading

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Revisions and contributorsEdit on WikipediaRead on Wikipedia

Service robot

View on Grokipedia
from Grokipedia
A service robot is defined as a robot used in personal or professional applications that performs useful tasks for humans or equipment, excluding industrial automation, and operates with a degree of autonomy to execute intended tasks based on its current state and sensing without continuous human intervention. This distinguishes service robots from industrial robots, which are primarily reprogrammable manipulators for manufacturing processes. Service robots are categorized into professional and personal/domestic types, with professional variants deployed in sectors like , healthcare, and , while personal ones assist in household tasks such as or . The field has seen rapid evolution since the early 2000s, marked by milestones like the 2002 launch of the vacuum cleaner by , which popularized autonomous domestic , and the 2005 introduction of Systems' warehouse robots, later scaled by Amazon for logistics automation. Further advancements include humanoid models like SoftBank's Pepper in 2014, designed for social interaction and in public spaces. In terms of market growth, global sales of professional service robots reached nearly 200,000 units in 2024, reflecting a 9% increase from the prior year, driven by labor shortages, an aging population, and the rise of robot-as-a-service (RaaS) models that grew 31% in adoption. Consumer service robots, including domestic cleaners, exceeded 20 million units sold that year, up 11%. Key applications span transportation and (102,900 units sold, +14%), medical robotics (16,700 units, +91% including surgical and rehabilitation systems), (over 25,000 professional units, +34%), and (over 42,000 units). These robots enhance , , and accessibility, with ongoing standardization efforts like ISO 13482 ensuring safety in human-robot interactions.

Definition and Overview

Definition

A service robot is defined by the (ISO) in standard 8373:2021 as a in personal or professional use that performs useful tasks for humans or equipment. This definition builds on the broader concept of a as an actuated mechanism programmable in two or more axes, with a degree of autonomy, moving within its environment to perform intended tasks. Service robots are distinguished by their focus on non-manufacturing applications, often involving interaction in unstructured or human-populated environments, with professional service robots excluding industrial automation. Key characteristics of service robots include partial to full , enabling them to operate with varying levels of human supervision, and the facilitation of human-robot interaction through interfaces such as voice commands or sensors. They are particularly suited for tasks categorized as the "3 Ds": dirty (e.g., handling hazardous materials), dull or repetitive (e.g., routine ), and dangerous (e.g., in risky areas). These attributes emphasize service robots' role in enhancing safety, efficiency, and by addressing human limitations in challenging scenarios. Levels of autonomy in service robots range from teleoperated (minimal independence) to fully autonomous operation. This allows service robots to adapt to diverse applications, from guided delivery systems to self-navigating assistants. The term "service robot" was coined in the 1990s by the International Federation of Robotics (IFR) and the Economic Commission for (UNECE) to differentiate non-industrial robots from traditional systems, highlighting their potential in consumer and professional services. This nomenclature emerged amid growing interest in beyond factories, formalized through early IFR working groups and adopted into ISO standards by the early 2000s.

Distinction from Industrial Robots

Industrial robots are defined by the (ISO) as automatically controlled, reprogrammable, multipurpose manipulators programmable in three or more axes, which can be fixed in place or mobile, and are intended for use in industrial applications. This definition emphasizes their role in structured environments, where they perform tasks such as , assembly, and on production lines, often operating in isolation from human workers to ensure and . In contrast, service robots are designed to perform useful tasks for humans or equipment in non-industrial settings, explicitly excluding applications in . The primary distinctions between service robots and industrial robots lie in their operational environments and interaction paradigms. Industrial robots function in highly structured, predictable settings with repetitive, high-precision tasks that minimize variability, typically without direct contact to avoid risks. Service robots, however, are engineered for unstructured, dynamic environments—such as homes, hospitals, or public spaces—where they must navigate variability, adapt to changing conditions, and interact safely with people, often requiring advanced and . This human-centric focus in service robots prioritizes and assistance over pure efficiency, differing from the isolated, task-optimized nature of industrial systems. While overlaps exist in hybrid systems, such as collaborative robots (cobots) used in light industrial assembly with human proximity, service robots fundamentally emphasize utility outside , like in warehouses or healthcare support, rather than core production processes. Regulatory frameworks reinforce these boundaries; the International Federation of Robotics (IFR) and ISO classifications separate industrial robots (tracked under statistics) from service robots (reported in professional and personal categories) to facilitate distinct and policy development. This delineation ensures accurate tracking of technological adoption across sectors.

History

Early Developments (Pre-2000)

The concept of service robots traces its origins to early 20th-century , where Czech writer introduced the term "robot" in his 1920 play R.U.R. (Rossum's Universal Robots), depicting artificial beings designed to perform human labor and services. This fictional vision popularized the idea of autonomous machines assisting humans in everyday tasks, laying a cultural foundation for later technological pursuits. In the mid-20th century, theoretical advancements in control systems further shaped these ideas; American mathematician Norbert Wiener's 1948 book Cybernetics: Or Control and Communication in the Animal and the Machine established the field of , emphasizing feedback mechanisms essential for machine autonomy and interaction with environments, which influenced early robotic designs. The 1960s marked the first practical steps toward mobile service-oriented robots with the development of Shakey at SRI International from 1966 to 1972. Shakey was the world's first mobile robot to integrate artificial intelligence for tasks such as navigation, object recognition, and planning simple actions like pushing blocks, demonstrating rudimentary autonomy in unstructured environments. This project, funded by the U.S. Defense Advanced Research Projects Agency (DARPA), pioneered techniques in computer vision and path planning that would inform future service applications. As a precursor, the industrial Unimate robot arm, introduced in 1961 by Unimation Inc. for assembly line tasks at General Motors, highlighted programmable manipulation but remained focused on manufacturing rather than service contexts. During the 1970s and 1980s, service robot development emphasized teleoperated systems for hazardous environments, particularly in response to nuclear incidents. Following the 1979 , teams at and other institutions designed remote-controlled robots like the Workhorse and core sampler to survey and decontaminate radioactive areas, avoiding human exposure to high levels. These teleoperated machines, equipped with cameras and manipulators, performed inspection and debris removal tasks, establishing reliability in extreme conditions and paving the way for safer human-robot collaboration in . In the , the field gained formal recognition and early prototypes as service robots emerged as a distinct category. The International Federation of Robotics (IFR), in collaboration with the Economic Commission for (UNECE), adopted a preliminary definition and classification system for service robots in the mid-1990s to address non-industrial applications, distinguishing them from manufacturing-focused systems. A notable example was the Helpmate robot, developed by Transitions Research Corporation and first deployed in a in 1992, which autonomously navigated corridors to deliver meals, medications, and supplies, reducing staff workload in healthcare settings.

Modern Advancements (2000-Present)

The 2000s ushered in pivotal breakthroughs for service robots, shifting from experimental prototypes to commercial viability. A landmark event was the 2002 launch of the , the first mass-market domestic robot designed for autonomous floor cleaning using basic sensors and navigation algorithms. This innovation made robotic assistance accessible to households, with eventually selling nearly 50 million units worldwide, thereby establishing a consumer market for service robotics. Concurrently, the competitions (2004–2007) accelerated advancements in autonomous navigation, requiring vehicles to traverse desert terrains without human intervention and fostering technologies like and path planning essential for service robot mobility in real-world settings. The 2010s saw expanded commercialization, particularly in professional sectors. Knightscope's introduction of the K5 autonomous security robot in 2014 exemplified this trend, featuring 360-degree surveillance, predictive analytics, and self-charging capabilities to patrol large areas and alert human operators to anomalies. The further catalyzed growth in 2020, dramatically increasing deployment of contactless delivery robots to mitigate infection risks, with companies like scaling operations for last-mile in urban environments. In the 2020s, service robots have integrated sophisticated AI, notably large language models (LLMs) for enhanced human interaction and task execution since 2023. These models enable robots to process instructions, plan multi-step actions, and adapt to dynamic scenarios, as demonstrated in systems combining LLMs with robotic control for applications like hospitality assistance. Humanoid designs advanced with Tesla's Optimus prototype revealed in 2022, a bipedal robot aimed at performing repetitive or hazardous service tasks through AI-driven manipulation and learning. In 2025, Tesla initiated limited production of Optimus, targeting initial deployments for internal factory tasks with plans for external service applications. Market expansion has been documented in International Federation of Robotics (IFR) World Robotics reports, showing professional service robot shipments nearly quintupling from 41,000 units in 2015 to nearly 200,000 in 2024, driven by and healthcare demands. Regulatory developments, including the AI Act of 2024, have influenced deployment by classifying AI in robots by risk levels—imposing transparency and safety requirements on high-risk systems to promote trustworthy integration into society.

Types

Professional Service Robots

Professional service robots are defined by the International Federation of Robotics (IFR) as service robots designed for use by trained operators, typically requiring specialized for setup, operation, or to ensure and in organizational settings. These robots perform tasks in commercial environments such as , medical care, , cleaning, inspection, and frontline services, distinguishing them from personal robots by their focus on enhancing in business operations rather than individual consumer needs. Key subcategories of professional service robots include transportation and , where systems enable warehouse automation through autonomous mobile robots (AMRs) for picking, sorting, and inventory management; healthcare, featuring surgical assistants that support precision procedures in operating rooms; field applications like , with robotic harvesters that automate crop picking and monitoring in outdoor settings; and public relations or , exemplified by reception bots that provide guidance and in hotels or offices. Additional categories encompass professional cleaning robots for floor and surface disinfection in large facilities, and units for monitoring like pipes and buildings, and specialized systems for construction, demolition, , or . These subcategories address diverse professional needs, with transportation and representing over 50% of professional service robot sales due to rising for automated solutions. In operational contexts, professional service robots are deployed in structured yet dynamic environments such as hospitals for patient support and sterilization, warehouses for amid varying inventory flows, and farms for navigating uneven terrain during harvesting. Their design emphasizes efficiency, reliability, and integration with workflows to boost operational while minimizing downtime. According to IFR , approximately 72% of service robot producers worldwide focus on professional models, reflecting their central role in commercial . In 2024, global sales of professional service robots reached nearly 200,000 units, a 9% increase from the previous year, underscoring their growing adoption across industries.

Personal Service Robots

Personal service robots are defined by the International Federation of Robotics (IFR), in alignment with ISO standards, as non-commercial robots that perform useful tasks for humans or equipment in personal or domestic settings, excluding industrial automation. These robots assist with individual or household activities, including support for the disabled or elderly, and encompass applications in domestic maintenance, , and mobility enhancement. Key subcategories of personal service robots include domestic cleaning robots, such as those for vacuuming floors or mowing lawns, which automate routine household chores; companionship robots, exemplified by social robots that provide emotional interaction and monitoring for users; and rehabilitation devices, like wearable exoskeletons that aid mobility for individuals with physical impairments. These categories prioritize non-intrusive, everyday functionality to support personal independence. Design principles for personal service robots emphasize user-centric features to ensure and reliability in home environments. Safety for personal care robots is governed by ISO 13482, which mandates inherently safe designs, protective measures against hazards, and clear user information to minimize risks during operation. Ease of use is critical, with intuitive interfaces and minimal setup requirements to suit non-technical users, while integration with smart home ecosystems enables coordinated actions like voice-activated controls or IoT connectivity. Additionally, lower production costs—driven by scalable and consumer-oriented pricing—make these robots viable for widespread household adoption, often retailing under $1,000 for entry-level models. Adoption of personal service robots has accelerated due to demographic shifts, particularly aging populations that heighten demand for assistive technologies in daily living and caregiving. The IFR reports that the personal service robot segment fueled annual unit sales growth exceeding 10% and reaching nearly 20 million units in 2024. This surge underscores the segment's role in addressing individual needs amid global trends like population aging and labor constraints in .

Technologies

Sensing and Perception

Service robots rely on a suite of sensors to acquire environmental data, enabling them to navigate, interact, and perform tasks in dynamic settings such as homes, hospitals, and warehouses. Core sensors include cameras for , which capture 2D images to detect objects and scenes; systems for 3D mapping, providing precise distance measurements via pulses to construct spatial models; ultrasonic and sensors for proximity detection, identifying nearby obstacles through sound waves or heat signatures; and inertial measurement units () for orientation and motion tracking, measuring and to maintain stability. Perception algorithms process this sensor data to interpret the environment in real time. techniques, such as YOLO (You Only Look Once) models, facilitate object recognition by dividing images into grids and predicting bounding boxes and class probabilities with high speed, allowing service robots to identify items like household objects or medical supplies. SLAM (Simultaneous Localization and Mapping) algorithms integrate sensor inputs to build and update maps while estimating the robot's position, using probabilistic methods like extended Kalman filters or graph-based optimization to handle uncertainties in indoor service environments. For human-robot interaction, service robots employ speech recognition systems based on automatic speech recognition (ASR) to convert spoken commands into text, enabling for tasks like guiding users or responding to queries in noisy settings. analysis supports emotional AI by detecting micro-expressions through convolutional neural networks, classifying emotions such as or to adapt behaviors, as seen in assistive robots for . Recent advancements as of 2025 include the integration of large language models (LLMs) for more sophisticated task planning and contextual understanding in human-robot interactions, enhancing service robots' ability to handle complex, instructions in real-world scenarios. Post-2020 advancements emphasize multi-modal fusion, where visual, auditory, and inertial data are combined using frameworks to enhance robustness against failures or occlusions, improving overall accuracy in complex service scenarios. further enables low-latency processing by performing these computations locally on the , reducing delays to milliseconds and supporting real-time decision-making without reliance on infrastructure.

Mobility and Manipulation

Service robots utilize diverse mobility mechanisms to navigate environments tailored to professional and personal applications, including wheeled, legged, and aerial systems. Wheeled platforms, commonly employing differential drive configurations, dominate indoor service tasks due to their energy efficiency, stability on smooth surfaces, and simplicity in control, as seen in robots like delivery assistants in hospitals or warehouses. Legged mobility, particularly bipedal designs, provides versatility for traversing uneven or cluttered terrains, enabling service robots to operate in dynamic settings such as homes or outdoor sites where wheeled bases falter. Aerial configurations, exemplified by drones, support elevated or inaccessible tasks like , inspections, or last-mile delivery, leveraging flight for rapid repositioning without ground constraints. Manipulation capabilities in service robots are primarily achieved through articulated robotic arms integrated with end-effectors such as parallel-jaw grippers, suction cups, or adaptive tools, which allow for grasping, placing, and interacting with objects of varying shapes and fragility. These arms typically feature 3 to 7 (DOF) to balance dexterity and payload capacity; lower-DOF designs (3-4) suffice for simple pick-and-place operations in , while higher-DOF systems (6-7) enable fine manipulation akin to human hand movements in personal care scenarios. For instance, the TIAGo mobile manipulator employs a 7-DOF arm to perform versatile service tasks like fetching items in domestic or professional environments. Precise control of both mobility and manipulation is essential for reliable operation, with proportional-integral-derivative (PID) controllers widely used to regulate motor velocities and positions, ensuring smooth trajectories and error minimization during motion. Path planning algorithms, such as the A* search method, facilitate efficient by optimal routes while incorporating real-time avoidance, critical for service robots operating in human-populated spaces. Recent innovations in the 2020s have focused on enhancing safety and flexibility through , which incorporates compliant materials and actuators to absorb impacts and enable gentle human-robot interactions, reducing risks in collaborative service roles like elderly assistance. Modular designs further promote adaptability, allowing service robots to reconfigure components—such as interchangeable arms or base units—for specialized professional uses like industrial handling or personal applications including home cleaning, thereby extending operational lifespan and customization.

Applications

Healthcare

Service robots have transformed healthcare by enabling precise interventions, supporting rehabilitation, and enhancing patient care in various settings. In surgical applications, systems like the , developed by , facilitate minimally invasive procedures through robotic arms controlled by surgeons at a console. First cleared by the U.S. (FDA) in 2000 for general laparoscopic surgery, the da Vinci system provides enhanced visualization, dexterity, and control, allowing operations such as prostatectomies, hysterectomies, and cardiac surgeries with smaller incisions and reduced blood loss compared to traditional methods. By 2025, da Vinci systems have been used in nearly 17 million procedures worldwide, demonstrating their widespread adoption in operating rooms. In rehabilitation, service robots assist patients recovering from injuries or neurological conditions by providing structured and promoting mobility. , such as the ReWalk Personal Exoskeleton, worn over the lower body, deliver powered assistance to the hips and knees, enabling individuals with injuries to stand, walk, and navigate stairs. The ReWalk received FDA clearance for personal use in 2014 and is deployed in clinical settings to improve training and cardiovascular health during rehabilitation sessions. robots extend to mental health support, where interactive devices guide cognitive behavioral exercises or provide companionship to alleviate anxiety and depression symptoms; for instance, socially assistive robots like those based on humanoid platforms deliver personalized prompts for or social interaction in therapeutic environments. For , service robots address isolation and hygiene needs, particularly in support and infection control. The PARO therapeutic robot, resembling a baby and equipped with sensors for responsive interactions, was introduced in 2003 to engage patients emotionally through touch and sound, reducing agitation and improving mood in individuals with . Post-COVID-19, UV-C disinfection robots, such as the UVD Robot, have been integrated into routines to autonomously navigate rooms and emit light to eliminate pathogens on surfaces, minimizing human exposure to contaminants and supporting safer care for vulnerable populations. These applications yield measurable impacts, including reduced fatigue from ergonomic console designs that allow seated operation during lengthy procedures. According to the International Federation of (IFR), medical service robots experienced significant annual growth, with sales surging 91% in 2024 alone, reflecting a compound expansion of over 20% from 2020 to 2025 driven by healthcare demands.

Logistics and Delivery

Service robots have transformed logistics and delivery by automating , transportation, and last-mile distribution in , urban environments, and outdoor settings. In , Amazon's acquisition of Systems in 2012 introduced mobile robots that transport shelves to picking stations, significantly streamlining processes. By mid-2025, Amazon had deployed over one million such robots across its global fulfillment centers, enabling faster inventory movement and reducing human labor in repetitive tasks. For last-mile delivery, sidewalk-based robots navigate pedestrian paths to transport goods directly to consumers, minimizing and emissions. Starship Technologies, founded in 2014, pioneered autonomous delivery bots that use sensors and AI for obstacle avoidance, handling groceries, meals, and packages in urban areas like and European cities. Similarly, Kiwibot robots, developed since 2017, specialize in on-campus food delivery at universities such as the and , where they autonomously carry orders from dining halls to dorms and buildings. Outdoor logistics applications extend service robots to agriculture and port operations, addressing challenging terrains and large-scale tasks. John Deere's 8R autonomous tractor, unveiled in 2022, integrates GPS, cameras, and to perform and planting without human operators, enhancing precision farming on expansive fields. In ports, inspection drones equipped with AI for visual analysis monitor cranes, loading equipment, and infrastructure; for instance, the deploys such drones via secure networks to assess conditions remotely, improving safety and reducing manual risks. The integration of service robots in these areas has yielded notable efficiency gains. Adoption surged during the from 2020 to 2022, as labor shortages and contactless demands accelerated warehouse automation and deployments worldwide.

Domestic and Entertainment

Domestic service robots encompass autonomous devices designed to perform household chores, providing convenience and efficiency for everyday users. The series, introduced in 2002, represents a pioneering example in , utilizing visual (vSLAM) technology to create detailed home maps for systematic navigation and obstacle avoidance. By 2025, iRobot has sold over 50 million Roomba units worldwide, demonstrating widespread adoption for tasks like vacuuming carpets and hard floors. These robots often feature self-emptying docks and app-based scheduling, reducing manual intervention in home maintenance. Beyond indoor cleaning, outdoor assistance robots like the Husqvarna Automower, first launched in 1995 as the world's initial commercial , handle yard upkeep autonomously using boundary wires and GPS for precise coverage. By mid-2025, Husqvarna has sold over 1 million Automower units, enabling users to maintain lawns up to several acres without human oversight. For elderly support, the Care-O-bot series, developed by Fraunhofer IPA since the late 1990s, serves as a mobile assistant capable of fetching items, monitoring health, and facilitating daily activities in home settings. Prototypes like Care-O-bot 4 emphasize safe human-robot interaction through modular designs for tasks such as serving drinks or providing reminders. In entertainment, social robots foster companionship and leisure. The Jibo robot, released in 2017, aimed to engage families with expressive animations, voice recognition, and photo-taking capabilities, though production ceased in 2019 after shipping around 4,800 pre-ordered units. Sony's Aibo, originally launched in 1999 and revived in 2018 with AI-driven behaviors like learning tricks and responding to touch, has sold over 150,000 original units and more than 20,000 of the updated model by 2025, appealing as an interactive pet alternative. These robots often simulate emotional bonds, with Aibo using cloud-based learning to adapt to owners' preferences. Consumer trends highlight increasing smart home integration, with many domestic robots compatible with voice assistants like for seamless control. For instance, models allow voice commands to start cleaning or return to base via Alexa skills, enhancing automation in connected households. The global domestic service robots market reached approximately USD 14.62 billion in 2025, driven by rising demand in developed regions where robotic vacuums achieve penetration rates exceeding 30% in households, reflecting broader acceptance of automation for chores.

Market and Future

The global service robotics market is projected to reach a value between $26.35 billion and $62.85 billion in 2025, reflecting robust growth driven by increasing adoption across sectors. This expansion is anticipated to continue at a (CAGR) ranging from 15% to 19.2% through 2032-2034, fueled by advancements in and demand for efficient solutions. Professional service robots dominate the market, accounting for approximately 70-80% of the value in recent years, with and transportation applications leading due to high deployment in warehousing and delivery operations. In contrast, personal service robots, such as household cleaning devices, represent about 20-30% of the market, primarily through consumer-oriented products. The Asia-Pacific region holds the largest share, commanding over 35-40% of the global market in 2025, attributed to its manufacturing prowess and rapid industrialization in countries like and . Key drivers include persistent labor shortages in aging populations and the surge in , which has accelerated the need for automated handling and delivery systems. According to the International Federation of Robotics (IFR), shipments of professional service robots reached nearly 200,000 units in 2024, a 9% increase from the prior year, with projections indicating continued upward momentum into 2025 led by segments. Prominent companies shaping the market include , known for consumer vacuums like ; SoftBank Robotics, with social robots such as Pepper for ; and , specializing in advanced mobility solutions like Spot for professional inspections. investment in exceeded $6 billion in 2024, supporting in service applications amid rising interest in AI-integrated systems. Service robots face significant technical challenges that hinder their widespread adoption. One primary limitation is battery life, which typically ranges from 4 to 8 hours for most models, restricting operational duration and necessitating frequent recharging that disrupts continuous tasks in applications like delivery or healthcare. Additionally, achieving robustness in unstructured environments remains difficult, as robots struggle with unpredictable obstacles, variable lighting, and dynamic human interactions, often leading to failures or risks without advanced adaptive algorithms. Ethical and regulatory concerns further complicate deployment. Job displacement is a major issue, with service robots potentially automating routine tasks in sectors like and , exacerbating and requiring workforce reskilling programs. Privacy risks arise from AI perception systems that process visual and audio data in homes or public spaces, raising concerns about unauthorized and data breaches. The EU AI Act, effective from 2024, classifies certain service robots as high-risk if their AI components pose threats to , safety, or , mandating rigorous conformity assessments, transparency, and human oversight for deployment. Emerging trends are addressing these barriers through innovative integrations. robots are gaining traction for versatile service roles, with pilots in demonstrating improved dexterity in warehouses and homes, as seen in initiatives by companies like Figure AI that test real-world adaptability. is advancing logistics by enabling coordinated fleets of small robots to handle dynamic inventory tasks collaboratively, reducing individual failures through decentralized decision-making. efforts focus on eco-friendly materials, such as biodegradable polymers and recycled components, to minimize environmental impact during production and end-of-life disposal. Looking ahead, the service robotics market is projected to exceed $200 billion by 2034, driven by scalable adoption in and sectors. AI advancements are expected to enable general-purpose service robots by 2030, capable of learning diverse tasks autonomously and operating in varied settings without specialized programming.

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