Discover the Top 10 Robotics Trends to Watch in 2026 & Beyond

Accelerate Productivity in 2025

Reignite Growth Despite the Global Slowdown

DOWNLOAD YOUR 25 PAGE TOOLKIT

Executive Summary: What are the Top 10 Robotics Trends in 2026 & Beyond?

1. AI Integration: AI forms the backbone of modern robotics. It drives natural-language programming, predictive maintenance, and fleet optimization. The market is projected to reach USD 33.39 billion by 2030.
2. Sustainable Robotics: Energy-efficient designs, motion optimization, and energy recovery reduce power use by up to 30%. Besides, green robotics is expected to grow at a 12.47% compound annual growth rate (CAGR) through 2030.
3. Collaborative Robots: Cobots handle 30 kg loads and operate safely alongside workers. They support flexible automation across SMEs, logistics, and food production.
4. Humanoids: Advances in dexterity, mobility, and onboard AI align with hardware costs falling 40% over two years. These changes support wider industrial adoption.
5. Robotics as a Service (RaaS): Subscription-based automation expands as firms avoid high capital expenditure. In 2024, 200 000 professional service robots were sold, contributing to fleet growth.
6. Ethical & Regulatory Considerations: Safety, transparency, and human oversight are tightening. 45 US states introduced AI bills, while the EU finalized high-risk regulations for autonomous systems.
7. Autonomous Mobile Robots (AMRs): AMRs are scaling in logistics, healthcare, and manufacturing. The market is expected to reach USD 9.26 billion by 2030, growing at 15.6% CAGR.
8. Edge Computing & Sensor Fusion: By 2025, 75% of enterprise data will be processed at the edge. Robots will gain faster perception, lower latency, and improved multimodal awareness.
9. Soft Robotics: Soft robot designs enable delicate manipulation in food, healthcare, and inspection. The market is projected to grow from USD 2 billion in 2025 to USD 8.8 billion by 2030.
10. Swarm Robotics: Multi-robot coordination is advancing through defense and commercial demand. The US Pentagon allocated USD 500 million to swarm development, supporting industry adoption.

Read on to explore each trend in depth – uncover key drivers, current market stats, cutting-edge innovations, and leading robotics innovators shaping the future.

Frequently Asked Questions

1. What is the market trend in robotics?

The global robotics market is projected to reach USD 553.14 billion by 2035. The growth is driven by AI integration, rising labor costs, demand for automation, and wider adoption of collaborative robots across manufacturing, healthcare, logistics, and agriculture.

2. What are the big 4 robotics?

The leading industrial robotics companies are ABB, FANUC, KUKA, and Yaskawa. They hold 75% of the global market share and play a central role in factory automation worldwide.

Methodology: How We Created the Robotics Trend Report

For our trend reports, we leverage our proprietary StartUs Insights Discovery Platform, covering 9M+ global startups, 20K technologies & trends, plus 150M+ patents, news articles, and market reports.

Creating a report involves approximately 40 hours of analysis. We evaluate our own startup data and complement these insights with external research, including industry reports, news articles, and market analyses. This process enables us to identify the most impactful and current robotics trends.

For each trend, we select two exemplary startups that meet the following criteria:

• Relevance: Their product, technology, or solution aligns with the trend.
• Founding Year: Established between 2020 and 2025.
• Company Size: A maximum of 200 employees.
• Location: Specific geographic considerations.

This approach ensures our reports provide reliable, actionable insights into the robotics innovation ecosystem while highlighting startups driving technological advancements in the industry.

Innovation Map outlines the Top 10 Robotics Trends & 20 Promising Startups

For this in-depth research on the Top Robotics Trends & Startups, we analyzed a sample of 9500+ global startups & scaleups. The Robotics Innovation Map created from this data-driven research helps you improve strategic decision-making by giving you a comprehensive overview of the robotics industry trends & startups that impact your company.

Tree Map reveals the Impact of the Top 10 Robotics Trends

There are advancements in robotics innovation across several categories. Collaborative robots (cobots) support safer human-machine teamwork, while autonomous mobile robots (AMRs) improve logistics and material movement indoors.

Humanoids are emerging for general-purpose tasks in warehouses and service environments. In addition, soft robotics enables delicate handling in food, agriculture, and healthcare.

Further, sustainable robotics emphasizes energy-efficient designs, recyclable materials, and longer lifecycles. At the same time, swarm robotics introduces decentralized coordination for inspection, surveillance, and environmental monitoring. Robotics-as-a-Service (RaaS) lowers adoption barriers by offering subscription-based automation.

Lastly, ethical and regulatory considerations continue to expand as robots gain autonomy and wider use.

Global Startup Heat Map covers 9500+ Robotics Startups & Scaleups

The Global Startup Heat Map showcases the distribution of 9500+ exemplary startups and scaleups analyzed using the StartUs Insights Discovery Platform. It highlights high startup activity in Western Europe and India, followed by the United States. From these, 20 promising startups are featured below, selected based on factors like founding year, location, and funding.

Want to Explore Robotics Innovations & Trends?

Top 10 Emerging Robotics Trends [2026 and Beyond]

1. AI Integration: AI Robots Market to Reach USD 33.39B by 2030

Many economies face aging populations and shrinking workforces, particularly in manufacturing. By 2024, more than 50% of manufacturers reported using AI and machine learning in production processes.

AI has become a central trend in robotics as it expands the range of tasks robots are able to perform. Generative AI enables more intuitive robot programming. Manufacturers are developing AI-driven interfaces that allow users to program robots with natural language instead of complex code.

A 2024 survey found that 47% of manufacturers ranked ease of use as their top priority when adopting new technology. With natural language interfaces, robot integration and operation become simplified.

Further, analytical AI allows robots to process sensor data, recognize patterns, and optimize operations for accuracy and speed.

Robot and chip makers are also investing in simulation platforms that let robots train in virtual environments. These AI-driven digital twins expose robots to countless scenarios before real-world deployment.

For instance, NVIDIA Isaac Sim is an open-source framework built on NVIDIA Omniverse. It enables developers to simulate and test AI-driven robotics solutions within physically based virtual environments.

Moreover, AI integration reduces maintenance costs and downtime. Predictive systems analyze performance data to anticipate failures and optimize upkeep. This is especially useful as an hour of unplanned downtime in automotive manufacturing costs about USD 2.3 million.

AI also coordinates large robot fleets in dynamic environments. For example, Amazon introduced DeepFleet, a generative AI model that optimizes travel routes for its fleet, reduces congestion, and improves efficiency by 10%.

Also, the global AI robots market is expected to grow from USD 6.11 billion in 2025 to USD 33.39 billion by 2030, at a CAGR of 40.4%.

Akson Robotics enables AI-driven Weed Mapping

Danish startup Akson Robotics develops CropUP, an AI-driven weed-mapping platform that creates precision spray maps using imagery from off-the-shelf RTK drones. It processes multispectral field images through machine learning models that detect and classify weeds, crops, soil, and tractor tracks. It also segments weed categories to enable targeted treatment.

The platform produces customizable spray maps compatible with more than ten agricultural terminals. Farmers are able to adjust dosage levels and buffer zones based on field conditions. It supports multiple crop types and integrates a workflow where they plan drone flight paths, upload imagery, and generate export-ready maps.

In addition, the platform reduces chemical use and aids farmers in complying with tightening spraying regulations through precise spot-spraying recommendations.

AIPL facilitates AI-powered Autonomous Manufacturing

South Korean startup AIPL makes AI-based automation and inspection technologies that modernize shipbuilding and semiconductor production through data-driven, unmanned processes. It applies deep-learning vision models to welding imagery to detect defects in real time, classify their size and shape, and store inspection history in a Welding Quality Management System that supports long-term traceability and maintenance.

Besides, the startup deploys autonomous work solutions that recognize complex environments by aligning 3D scan data with CAD models. These systems generate robot work paths and simulate manufacturing conditions to predict deformation and analyze potential defects.

AIPL also operates autonomous material transport robots that combine indoor GPS, LiDAR, and deep reinforcement learning. These robots ensure stable navigation in large shipyards and dynamic industrial spaces.

2. Sustainable Robotics: Optimized Motion & Energy Recovery Cut Electricity Use Up to 30%

A 2024 ABB global survey found that 58% of industrial manufacturers view high energy costs as a barrier to competitiveness. In addition, 93% plan to invest in energy-efficiency improvements over the next three years to reduce costs and meet sustainability targets.

Robots are designed with minimal environmental impact and are deployed to support sustainability goals. This includes energy-efficient designs, recyclable materials, and longer lifecycles, as well as applications in clean energy, recycling, and safer workplaces.

For example, optimizing robot motion and recovering braking energy reduces electricity consumption by up to 30%. Industrial robot controls convert kinetic energy into electricity and feed it back to the grid, further reducing net power demand.

Academic research in 2024 showed that industrial robots lower pollution intensity in manufacturing by improving energy efficiency and enabling stronger pollution controls.

Looking ahead, the green manufacturing robotics market is projected to grow at a CAGR of 12.47%, increasing from USD 3.293 billion in 2025 to USD 5.927 billion by 2030.

Further, rising energy bills and carbon targets are driving the adoption of these greener technologies.

By late 2024, AMP Robotics’ AI platform had identified more than 150 billion pieces of material and sorted over 2.5 million tons of recyclables. About 400 robots across multiple facilities use computer vision to recover materials that would otherwise go to landfill. The company also raised USD 91 million in Series D funding in December 2024 to expand robot-powered recycling operations.

Moreover, robots designed to reduce chemical use make farming more sustainable. John Deere’s See & Spray Ultimate technology allows growers to target weeds instead of relying on broadcast spraying, which cuts non-residual herbicide use by up to two-thirds.

Clean energy operations benefit as well. Wind and solar farm operators deploy autonomous robots for panel cleaning and turbine inspection to reduce downtime and improve renewable power efficiency.

Snowbotix creates Electric, All-Season, Multi-Utility Robots

US-based startup Snowbotix manufactures autonomous, all-electric multi-utility robots for outdoor maintenance throughout the year. Its platform combines sensors, AI-driven navigation, and modular attachments to automate snow clearing, sweeping, and vegetation management in non-road, high-risk environments.

The robots operate with real-time mapping, obstacle detection, and terrain-adaptive controls. These features support performance in extreme weather and on slopes up to 35 degrees.

In addition, the startup integrates interchangeable tools for plowing, mowing, sweeping, and de-icing. The command software enables fleet management, GPS-verified reporting, and continuous monitoring.

SeaGen makes AI & Solar-Powered Marine Robots

UK-based startup SeaGen develops AI and solar-powered marine robots that monitor biodiversity and assess the health of oceans, rivers, and lakes. Its platform integrates sensors, cameras, and environmental probes to collect live data on marine life, pollutants, and water conditions. It processes this information through onboard analytics and AI models to identify species, track changes, and detect environmental patterns.

The startup’s modular Baseline Buoy supports visual, acoustic, and environmental monitoring through four configurable module slots. Further, the mobile Baseline Rover extends coverage by scanning wider areas and returning to its mooring for charging and data transmission.

SeaGen also operates the Baseline App, which provides live and historical data in an accessible format. The app enables users to document local environmental changes and share insights.

The startup also creates AlgaRay, which removes invasive seaweed and pollutants, while the AlgaVator automates seaweed cultivation to support biodiversity and carbon reduction.

3. Collaborative Robots: New Cobots Handle 20-30 Kg Loads & Full Pallets

Businesses require flexibility and agility in production. The short product cycles, customization, and volatile demand make automation more effective when it is redeployed quickly. Cobots fit this need because they are easy to reprogram or relocate for new tasks and are well-suited for small and mid-sized enterprises (SMEs) with high-mix, low-volume production.

The post-pandemic e-commerce boom and continuous logistics operations have increased demand for automation in warehousing, fulfillment, and supply chains. Cobots, often mounted on mobile bases, are used for packing, palletizing, and material handling in facilities that face round-the-clock demand spikes.

The advances in sensors, machine vision, and end-effectors allow cobots to operate with awareness and precision. Modern cobots include 3D cameras, LiDAR, and force sensors that detect humans or obstacles in real time and adjust movements to avoid collisions.

Earlier cobots were limited to light duties. However, newer models offer higher payload capacities and extended reach. Manufacturers released cobots capable of handling 20-30 kg loads and full pallets in 2024. For example, FANUC introduced CRX-30iA, a food-grade cobot with a 30 kg payload and 1.75 m reach for palletizing tasks at Pack Expo 2024.

In factories, cobots are addressing skilled tasks such as welding, where labor shortages persist. Raymath, a metal fabricator, deployed UR10e cobots for complex welding in a high-mix production line. The cobots doubled welding speed and increased output 4 times while reducing the number of operators required on the shop floor.

Cobots are also entering food handling and retail. A notable example is the automated cobot bakery system developed by Fanuc and WIESHEU, which is nicknamed Bakisto and manages early-morning bread baking and oven loading.

In terms of investment, South Korea’s Doosan Robotics, manufacturer of cobot solutions, launched the country’s largest IPO of the year, which raised about KRW 421.2 billion to support expansion.

Further, the collaborative robot market is projected to grow from USD 1.9 billion in 2025 to USD 4.88 billion by 2030, with a CAGR of 20.76% during this period.

AutoMates Robotics creates a Flexible Feeding System

Belgian startup AutoMates Robotics makes a feeding and kitting system that automates orientation, detection, and delivery of small parts to simplify assembly workflows. The system processes components loaded into vibrating trillbeds and applies a vision algorithm to identify each item’s position. Further, it directs a robotic arm to pick and place products for downstream handling or automated bagging.

It supports product registration within seconds and adapts to changing production needs through programmable parameters and interchangeable configurations. In addition, it reduces assembly errors by stabilizing part flow and improving picking accuracy. The real-time kit customization aids in minimizing unnecessary inventory.

SICA packaging & robotics builds Cobot Workstations

Dutch startup SICA packaging & robotics develops cobot palletizing systems that automate box stacking and material handling to improve packaging efficiency in food, beverage, co-packing, pharma, animal feed, and consumer goods operations.

The system combines collaborative robot arms from Doosan and Fanuc with vision-guided alignment, grippers, and conveyor integration. These features allow robots to pick products, create stacking patterns, and load pallets with consistent accuracy.

It operates through proprietary drag-and-drop software. It enables businesses to enter product specifications, design multi-layer pallet patterns, and control label orientation or interleave placement directly from a computer.

The system runs continuously, reduces physical strain on employees by taking over repetitive lifting tasks, and supports compliance with ARBO ergonomic standards.

Additionally, the platform improves productivity through stable cycle times. It also provides production insights that highlight inefficiencies at the line level.

4. Humanoids: Hardware Costs Have Dropped 40% in Two Years

The advances in AI, especially generative AI and multimodal models, are enabling robots to perceive, learn, and make decisions with greater autonomy.

In 2024, NVIDIA announced Isaac GR00T, a foundation model that allows robots to learn skills from human demonstrations and natural language instructions.

Humanoid hardware has advanced in mobility and dexterity. The modern robots are able to walk, run, jump, and navigate complex terrain. Their arms and grippers handle tools and objects with increasing accuracy. For example, Figure’s latest humanoid carries up to 25 kg and manipulates everyday objects, while XPeng Robotics’ prototype includes over 60 hand joints for fine motor control.

The hardware improvements extend to batteries, materials, and actuators. Boston Dynamics introduced an electric Atlas, replacing its hydraulic design. Figure 02 added 50% more battery capacity, which offers hours of runtime with a quick-swap design. It also tripled onboard computing power and integrated multiple AI cameras to support greater autonomy.

Also, the humanoid hardware costs have dropped about 40% in two years. Unitree’s model, priced near USD 16 000, now equals the annual wage of a minimum-wage worker in the US, while operating continuously without breaks.

Further, several global tech leaders, along with specialized robotics start-ups, are increasing production of humanoids.

Factories are beginning to adopt humanoids for material handling and assembly. Foxconn, for instance, has introduced humanoid robots to move carts of parts between workstations, a task previously handled by human runners.

“The factory will also be among the first to deploy humanoid robots powered by the NVIDIA Isaac GR00T N model on its production lines, as Foxconn and Nvidia aim to build a world-leading benchmark AI smart factory,” the company stated in a release issued during Nvidia’s developers’ conference in Washington, D.C.

Experts at the World Economic Forum suggest humanoid robots could become common in daily life within the next decade. They estimate that billions of humanoids may operate worldwide by 2040 in roles beyond factory work.

Moreover, the global humanoid robot market is projected to grow from USD 2.92 billion in 2025 to USD 15.26 billion by 2030, with a CAGR of 39.2%.

Physical Robotics creates a Physical Intelligent Humanoid

Norwegian startup Physical Robotics develops Pi, an upper-body humanoid robot for dexterous tasks in industrial and service environments. It operates with multi-degree-of-freedom hands, force-controlled joints, and sensor-driven perception that enable precise gripping, twisting, and object manipulation without damaging items or losing stability.

The robot uses Physical Intelligence, an AI framework that combines real-world data, motion control, and adaptive learning. This allows Pi to sense its surroundings, plan interactions, and adjust movements in real time.

Its legless design improves safety in tight spaces, shortens engineering cycles, and supports deployment without workspace modifications while maintaining human-scale reach and capability.

In addition, the system addresses high-risk, repetitive, or unpleasant tasks across manufacturing, healthcare, logistics, waste management, and harsh environments. It matches human-like dexterity with continuous, fatigue-free performance.

Muks Robotics makes Omni-Modal AI Humanoids

Indian startup Muks Robotics builds AI-powered humanoid and industrial robots that automate physical tasks, inspection workflows, and interactive services in commercial and industrial settings. Its humanoid, Spaceo, uses FusionMax, an omni-modal AI system that unifies vision, language, voice, planning, and navigation for autonomous operation.

The startup produces variants such as Spaceo Pro for industrial tasks, Spaceo M1 for multilingual social interaction, and Spaceo Prime for advanced research. Each of these models operates through coordinated multi-joint actuation and real-time sensing.

Muks Robotics also expands its portfolio with industry-specific systems. These include the Guardeo inspection robot and DeepVision Pro and Watchmen solutions for dimensioning, OCR, presence-absence verification, human detection, product counting, and operator safety.

Additionally, the platform integrates modular hardware with AI-driven perception. This supports deployment in manufacturing, automotive, logistics, and public environments without requiring major layout changes.

5. Robotics as a Service (RaaS): 200K Professional Service Robots Sold in 2024

The International Federation of Robotics (IFR) reported that nearly 200 000 professional service robots were sold worldwide in 2024, a 9% increase from the prior year.

“There is strong demand for service robots in a number of different application areas. In order to integrate automation without making a heavy upfront investment, more-and-more companies are deciding to enter into subscription or rental agreements rather than purchasing robots outright. The robot-as-a-service fleet (RaaS) has grown impressively by 31%.”

– Takayuki Ito, President of the International Federation of Robotics

Persistent staff shortages remain a key driver of adoption. In logistics and fulfillment, high turnover and seasonal demand peaks make flexibility essential. Deloitte projects a shortfall of 2.1 million manufacturing workers in the US by 2030. Also, the Bureau of Labor Statistics data shows that warehousing faces an annual turnover rate of 49%.

The advanced robots often cost between USD 50 000 and 200 000, placing them beyond the reach of many small and mid-sized firms. RaaS changes this by spreading costs through subscription models.

The rollout of 5G networks and IoT infrastructure further enables RaaS. High-bandwidth, low-latency connectivity allows robots to be monitored or controlled remotely by cloud systems or teleoperators. It enables providers to manage fleets across dispersed locations, deliver over-the-air updates, and perform predictive maintenance without on-site intervention. 5G-powered robots were deployed in diverse settings, from delivery services in Georgia to river-cleaning operations in Singapore.

Cloud robotics platforms also play a central role with Amazon’s AWS RoboMaker offering simulation and management tools.

In December 2024, KUKA introduced a subscription model for its robotic arms. Under this plan, manufacturers pay a monthly fee covering the robot, maintenance, and software updates, while avoiding high upfront costs.

Looking ahead, the global service robotics market is projected to grow from USD 26.35 billion in 2025 to USD 90.09 billion by 2032, with a CAGR of 19.2%.

Security Robotics creates a Security & Service Robots Platform

German startup Security Robotics develops a Robots-as-a-Service platform that deploys networked service and security robots to automate patrols, reception tasks, and facility monitoring across varied environments.

The system connects multiple robot models through a unified platform that coordinates sensors, cameras, navigation modules, and communication functions. It allows users to switch to manual control when needed for direct operation and full access to onboard capabilities.

The platform supports specialized robots for indoor visitor management, outdoor perimeter surveillance, and difficult terrain. Each unit includes tailored drive systems, movement profiles, and hardware configurations.

In addition, the startup offers flexible customization through modular add-ons such as extra sensors, inspection tools, speakers, lighting, and auxiliary cameras. These options allow projects to match specific requirements.

Red Rabbit Robotics offers Autonomous Humanoid Labor as a Service

Canadian startup Red Rabbit Robotics manufactures autonomous humanoid robots that provide general-purpose labor as a service. These robots execute routine industrial and commercial tasks with human-like precision.

The system integrates advanced sensors, multi-modal perception, and machine-learning models. This enables robots to navigate facilities, recognize objects, and perform actions while adapting continuously to their environment.

The platform combines these capabilities with round-the-clock operation, automated scheduling, and remote supervision. Tasks are completed consistently without fatigue or turnover.

The robots also improve workplace safety by reducing injuries, missed defects, and mis-shipments through repeatable, accurate performance.

6. Ethical & Regulatory Considerations: 45 States Introduced AI Bills & 31 Enacted New Laws in 2024

Safety incidents involving robots, from factory accidents to self-driving vehicle crashes, have raised public awareness. The fatal accident in South Korea in 2023 and reports of warehouse robots injuring employees increased calls for stricter safety protocols.

Modern robots often integrate AI and operate autonomously, which introduces new ethical challenges. AI-driven decision-making creates bias, opacity, or unforeseen behaviors.

Regulators are pushing for algorithmic transparency and human oversight in high-risk systems. The EU’s AI Act, for example, classifies surgical robots and autonomous vehicles as high-risk, which require conformity assessments, transparency, and human-in-the-loop controls.

In 2024, at least 45 US states plus DC and territories introduced AI bills, and 31 states enacted new laws or resolutions addressing AI and automated systems. Colorado’s law requires reasonable care to avoid discrimination in high-risk AI systems. Other rules are sector-specific, such as New York’s proposal to ban weaponizing civilian robots and state-level limits on delivery robots covering speed, weight, and insurance.

Between 2023 and 2025, the EU finalized three major laws: the updated Machinery Regulation (EU 2023/1230), a revised Product Liability Directive, and the AI Act. The Machinery Regulation, effective January 2027, addresses autonomous and AI-driven machines directly. It introduces autonomy thresholds, requiring robots that learn or self-evolve to undergo enhanced safety conformity assessments to prove safe operation under unforeseen conditions.

The UK government in 2024 released an AI policy that favors guidance over prescriptive rules. The UK relies on existing agencies and sector-specific guidelines for areas such as medical devices and autonomous vehicles.

Further, startups like 3Laws Robotics develop middleware that acts as an independent governor on robot behavior. Its system applies mathematically provable safety techniques, such as Control Barrier Functions from Caltech, to enforce constraints. It also provides auditable evidence that robots meet standards like ISO 3691-4 for industrial truck safety and ISO 26262 for functional safety in vehicles.

Large corporations are also incorporating ethics into robotics R&D. Toyota and Honda have invested in assistive robots for the elderly. They work closely with regulators in Japan and the EU to ensure these devices meet safety and privacy requirements in caregiving.

MAXimuz Technology advances AI Ethics

UAE-based startup MAXimuz Technology develops AI-powered humanoid robotics platforms that support industry, healthcare, and community environments through responsible, human-centric design.

Its systems combine modular hardware, mobility mechanisms, and Actualize AI Technology. It processes sensory inputs, recognizes emotions, conducts cognitive interactions, and performs tasks such as patient guidance, wellness monitoring, and customer assistance.

The platform applies an ethics-by-design framework that embeds transparency, accountability, and privacy into each deployment. Its robotics code of conduct emphasizes augmenting human capability rather than replacing it.

In addition, the company builds solutions such as the NeuroCare system for senior support. It also designs modular robots that adapt to sector-specific requirements across hospitals, classrooms, retail sites, and public spaces.

OpenMind builds an Open Source AI Robot Operating System

US-based startup OpenMind creates an AI-native software stack that enables robots to think, learn, and coordinate in real-world environments. Its platform processes sensory inputs, language model outputs, and vision detections through OM1, a modular operating system that integrates LLMs, perception models, and agentic workflows to support adaptive behavior in humanoid and quadruped robots.

The system includes plug-and-play data collection tools, onboard reasoning engines, and multimodal interaction pipelines. These features translate environmental understanding into precise robotic actions.

Besides, the startup operates FABRIC, a decentralized coordination network that provides trusted identity, location verification, and peer-to-peer communication for collaborative machine operations.

OpenMind also aids businesses in developing trustworthy AI systems by offering clear guidance, evaluation methods, and evidence-based insights that strengthen ethical decision-making and long-term governance.

7. Autonomous Mobile Robots (AMRs): Market to Reach USD 9.2B by 2030

With unemployment low in many regions and workforces aging, companies are turning to AMRs to handle routine or strenuous jobs. These robots operate around the clock, offset labor gaps, and reduce reliance on hard-to-fill roles such as overnight warehouse runners.

Rising customer expectations for rapid delivery are driving investment. Warehouses that deploy AMRs for order picking, sorting, and packing shorten fulfillment times and improve efficiency.

The advances in LiDAR and camera systems give AMRs precise environmental perception in real time. At the same time, stronger onboard processing, often cloud-assisted, enables smarter decisions on the move. This makes AMRs today more reliable, flexible, and easier to deploy, which supports wider adoption.

In May 2024, DHL marked its 500 millionth unit picked by Locus Robotics AMRs. The company operates swarms of Locus Origin robots that assist human pickers by carrying and sorting items. By mid-2024, more than 6000 Locus robots were active across 35 DHL sites worldwide.

Besides, AMRs in hospitals ferry medications, samples, and supplies through hallways, reducing nurse workloads. Aethon’s TUG robots are common in some facilities, while UV light disinfecting robots gained traction during the pandemic for room sterilization.

Some AMRs are able to lift loads over one ton, replacing forklifts for certain pallet moves. Mobile manipulators, such as Boston Dynamics’ Stretch robot, drive into trailers and unload boxes autonomously, where it combines mobility with AI-powered gripping.

Battery technology is advancing, with many latest models using lithium-ion batteries that run for hours and support opportunity charging during idle moments. Some warehouses have installed wireless charging pads at checkpoints, allowing AMRs to recharge briefly while awaiting commands.

Moreover, the autonomous mobile robot market is estimated at USD 4.49 billion in 2025 and projected to reach USD 9.26 billion by 2030, with a CAGR of 15.60% during this period.

DRVBOT makes Warehouse AMRs

Turkish startup DRVBOT manufactures autonomous mobile robots that support warehouse operations by automating item transport and optimizing worker task flow. The system processes sensor inputs, mapped layouts, and instructions from warehouse management systems to navigate aisles, retrieve items, and deliver loads through real-time path planning and coordinated movement.

The startup’s DERIVATIVE platform integrates adaptive robots, a central server, and software that connects directly with existing WMS infrastructure to enable quick deployment and continuous operations.

Additionally, the robots work alongside staff to reduce walking time and remove the physical effort of moving carts or pallets. They also improve throughput during high-demand periods by scaling fleets efficiently.

Flowbotic builds AMRs for Intralogistics

Portuguese startup Flowbotic develops autonomous mobile robots that improve intralogistics through automated transport, material handling, and facility navigation. Its systems process LiDAR data, onboard sensors, and mapped layouts to move loads, tow carts, and handle pallets using natural or reflector-assisted navigation with accurate positioning.

The startup offers a portfolio of AMRs, including GoMouse, GoMouse-x, GoTugger, GoTugger-x, and GoPallet. Each of these model features defines speed, load capacity, and traction specifications to address specific workflows in warehouses and industrial sites.

In addition, Flowbotic integrates an intelligent management platform that enables route configuration, real-time monitoring, and fleet coordination. This supports efficient operation and allows quick scaling when demand increases.

8. Edge Computing & Sensor Fusion: 75% of Enterprise Data Will Be Processed at the Edge by 2025

By 2025, Gartner projects that 75% of enterprise-generated data will be created and processed outside centralized data centers or the cloud, closer to devices at the network edge.

Robots often operate in safety-critical or time-sensitive contexts, such as self-driving cars or surgical systems, where milliseconds matter. Processing sensor data at the edge reduces latency by removing cloud delays and enables faster responses.

The rollout of 5G networks further supports edge-enabled robotics. Forecasts suggest 5G connections will reach 2.9 billion by the end of 2025. With ultra-low latency and high throughput, robots are able to communicate with nearby edge servers through Multi-access Edge Computing or directly with each other.

The falling hardware costs and the availability of power-efficient AI chips make edge computing more accessible. Processors and accelerators that once required data centers now fit on robots. Even small robots or drones carry onboard computers capable of millions or billions of AI operations per second. Edge computing provides on-site AI brains, which reduces reliance on cloud round-trips.

Self-supervised and multimodal AI models also advance sensor fusion. Vision-language models and transformer-based architectures allow robots to combine visual data with other inputs more intelligently, interpreting context rather than raw values. The models, such as Meta’s DINOv3 improve visual reasoning and aid robots in processing sensor data in more human-like ways.

Further, Physical AI simulation environments let developers refine sensor fusion algorithms in virtual settings before deploying them in real-world applications.

Self-driving cars and delivery robots rely heavily on sensor fusion and edge computing. For example, Tesla’s Autopilot processes vision data from multiple cameras using a custom AI computer inside the car.

D-Robotics creates Robotics & Edge Intelligence Development Kit

Chinese startup D-Robotics builds a hardware and software platform that equips robotics companies with computing boards, AI acceleration engines, and ready-to-deploy tools for building intelligent machines.

Its RDK series processes sensing data, visual inputs, and control signals through heterogeneous multicore architectures and proprietary BPUs. These units deliver 5-128 TOPS of inference power for perception, reasoning, and real-time motion control.

The platform includes development kits such as the RDK X3, RDK X5, and RDK S100. Each kit provides standardized interfaces, multi-camera support, PoE connectivity, and extensive I/O options. These features accelerate prototyping and integration across wheeled robots, robotic arms, autonomous vehicles, and embodied systems.

Besides, D-Robotics offers NodeHub, a library of more than 200 open-source algorithms and application examples. It also provides ROS 2 packages, peripherals, and community support to simplify end-to-end development.

Sensible Robotics makes a Tactile Sensing System

US-based startup Sensible Robotics develops tactile sensing technology that gives robots touch perception through a smart-fabric system made from piezo-resistive textiles. Its platform processes pressure, vibration, texture, and angular force data using conformal sensor arrays that wrap around robotic fingers, hands, and surfaces. These inputs generate 3D contact maps and vector outputs in real time.

The system provides full-surface coverage, slippage awareness, and multi-modal sensor fusion. It improves dexterous manipulation, expands environmental awareness, and supports safe interaction in industrial and tele-presence applications.

In addition, the startup offers software integrations, multiple data interface formats, and a technology stack validated through millions of deployed sensors.

9. Soft Robotics: Market to Reach USD 8.8B by 2030 at 34.45% CAGR

A study found there were 41 robot-related fatalities during the 1992 to 2017 period in the US. This shows traditional rigid robots pose injury risks.

On the other hand, soft robots are built from compliant materials and reduce impact forces. They are designed for safer human-robot interaction, and when they bump into people or grip objects, they don’t cause damage.

Several industries have distinct automation needs that soft robotics addresses. In the food industry, fragile and irregular items such as fruits, baked goods, and meat require careful handling under strict hygiene standards. Soft robotic grippers pick and pack food without bruising or contamination.

Besides, German firm Schmalz acquired the soft-gripper business (mGrip) of Soft Robotics Inc. (USA) in 2024 to expand in food automation.

Healthcare has also adopted soft robotics. The demand comes from minimally invasive surgical tools, rehabilitation devices, and wearable exoskeletons for mobility assistance. Wearable soft exosuits and exoskeletons aid stroke and spinal injury patients in regaining movement. Companies such as Ekso Bionics have developed wearable exoskeletons that support patient rehabilitation and assist workers in factories.

Moreover, elastomers, gels, and programmable materials improve strength, durability, and precision in soft robots. For example, in 2024, a Yale soft robot used a bicontinuous thermoplastic foam joint to amputate and reattach its own limb.

New ventures are also emerging. Mimic Robotics, a Swiss spin-off from ETH Zurich founded in 2024, raised USD 16 million in November 2025 to develop AI-driven robotic hands with human-level dexterity.

Besides, the soft robotics market is estimated at USD 2.00 billion in 2025 and projected to reach USD 8.80 billion by 2030, with a CAGR of 34.45% during this period.

Herobots builds Soft Robots for Hazardous Environments

Italian startup Herobots develops soft robotic systems and software that support remote inspection, maintenance, and manipulation in confined or hazardous industrial environments. Its T-Bot platform uses tendon-driven actuation, slender continuum structures, and interchangeable sensors to navigate tight spaces. It performs tasks such as debris removal, 3D mapping, and precision inspection through RGB, 3D, ultrasonic, and thermal modules.

The startup also provides HeroSuite, a software environment that processes robot dynamics, vibration behavior, and workspace constraints. This platform enables design optimization, advanced motion planning, and real-time digital-twin simulations to support safer task development and execution.

Further, Herobots offers HeroEye, an AI-powered multisensor vision system. It combines RGB and thermal imaging, point-cloud reconstruction, and feature tracking to improve environmental perception in low-light and complex settings.

Hippos Exoskeleton creates Smart Soft-Exoskeletons

US-based startup Hippos Exoskeleton makes an AI-guided knee protection device that supports movement and lowers the risk of ACL injury during daily activities and sports. The system analyzes rotation, hyperextension, and joint dynamics in real time through embedded sensors. It then deploys an airbag mechanism around the knee within 30 milliseconds to stop abnormal motion before damage occurs.

The device also tracks ACL-related indicators such as knee laxity, fatigue, and strain. These measurements provide users with injury-risk analytics that guide safer training decisions.

Hippos Exoskeleton also applies AI calibration to match activation thresholds to each user’s joint characteristics and ensure protection levels remain personalized.

10. Swarm Robotics: Pentagon Allocated USD 500M in 2024 for Low-Cost Drone Swarms

The rapid advances in AI and network technology have enabled complex multi-robot coordination. Swarm algorithms draw inspiration from nature, using decentralized ant colony logic to coordinate robots.

Lightweight edge AI models give each robot local intelligence, while improved wireless communication through 5G and mesh networks allows swarms to synchronize in real time. It strengthens collective decision-making and reliability.

The US Pentagon’s Replicator program allocated USD 500 million in 2024 to develop swarms of low-cost drones.

Military interest remains a major catalyst. Defense agencies view swarms as strategic tools for surveillance and combat. In 2025, Sweden launched a program with Saab that enables a single soldier to control 100 drones for varied missions.

Small, low-cost boards run onboard AI, while lightweight sensors and microcontrollers allow robots to perceive and decide locally.

New communication strategies keep large groups in sync. Short-range mesh networks and ultra-wideband radio let robots connect with neighbors even in cluttered or GPS-denied environments.

Companies are releasing orchestration tools that treat swarms as unified systems. Cloud-based command centers, digital twin simulators, and standardized APIs allow operators to deploy and update hundreds of robots efficiently.

In warehouses, swarms of mobile robots have improved throughput and reduced costs. Unbox Robotics deployed swarms of sorting AMRs that achieved 99.9% accuracy while tripling productivity and reducing cost per package by 30-50% in parcel fulfillment centers.

Swarm robotics is also addressing environmental challenges. Low-cost drones and rovers track pollution plumes, monitor wildlife habitats, and support disaster response. Germany-based SWARM Biotactics raised EUR 10 million in 2025 to develop bio-robotic insect swarms for search-and-rescue and defense applications.

Further, the global swarm robotics market is projected to reach USD 1.9 billion in 2025 and grow at a CAGR of 25.6%, reaching USD 14.7 billion by 2034.

ARES Autonomy advances Swarm Intelligence

Irish startup ARES Autonomy develops a swarm-intelligence platform that allows an operator to control and coordinate large groups of autonomous drones. The system fuses perception data, edge computing modules, and cloud-based SwarmLLM algorithms to interpret environments, distribute tasks, and synchronize multi-vehicle behavior across aerial and ground assets.

The platform integrates vendor-agnostic interfaces that connect with UAS, fixed-wing systems, VTOL aircraft, UUVs, and ground vehicles. Its swarm mesh network supports computer-vision navigation and anti-jamming performance in GPS-denied environments.

In addition, the startup provides scalable cloud services, real-time edge processing, and cost-efficient hardware designed for multi-drone missions.

Swarm Aero supports Swarm-Scale Command & Control

US-based startup Swarm Aero builds a UAV platform built for swarm operations. It enables large groups of autonomous aircraft to carry out coordinated missions with limited operator input.

The system combines distributed edge computing, onboard autonomy, and a universal swarm node. This node links each vehicle into a sensor mesh, which allows the swarm to share environmental data, update behaviors in real time, and translate mission intent into precise aircraft actions.

The startup integrates lightweight composite airframes, scalable manufacturing processes, and browser-based command interfaces. These tools allow small teams to mobilize and direct thousands of uncrewed vehicles across air, sea, and ground domains, even in contested or communications-limited environments.

Swarm Aero also supports adaptive sensing, mobile communications, logistics, and defense applications through payload-efficient designs and collaborative autonomy.

Discover all Robotics Trends, Technologies & Startups

Looking ahead, robotics will evolve through breakthroughs such as self-repairing robots, multi-agent AI coordination, and biologically inspired locomotion. Further, telepresence systems with realistic interaction and autonomous construction robots are approaching practical use.

As these innovations mature, robotics will reshape productivity, strengthen safety, and redefine human-machine collaboration across major industries.

The Robotics Trends & Startups outlined in this report only scratch the surface of trends that we identified during our data-driven innovation & startup scouting process. Identifying new opportunities & emerging technologies to implement into your business goes a long way in gaining a competitive advantage.