From manual to autonomous: How TALOS is redefining solar operations

Across Europe, the expansion of solar energy is reshaping the renewable landscape. Yet as PV systems grow in size and complexity, their upkeep remains heavily dependent on manual labour. Cleaning panels, trimming vegetation, monitoring faults and ensuring safety are time-consuming and often hazardous activities.

The Horizon Europe-funded project TALOS (roboTics and Artificial intelligence Living labs improving Operations in PV Scenarios) tackles these challenges through an ambitious blend of robotics, AI and real-world experimentation. Bringing together utilities, research centres, technology developers and SMEs, the consortium is developing an integrated ecosystem of smart machines capable of operating in some of the most demanding PV environments: from vast land-based farms to floating solar arrays and dual-use agricultural sites.

TALOS applies a living-lab approach, combining co-creation with on-site testing. Each pilot represents a different operational context and technology focus:

• Land-based PV sites in Spain explore autonomous robots for cleaning and vegetation control.
• Floating PV installations in Portugal validate robotic systems adapted to water environments, supported by drones and underwater inspection units.
• Agri-PV fields in the Netherlands integrate ground robots and AI-driven monitoring for crop and energy optimisation.

The project’s technical backbone lies in its multi-robot management platform, which coordinates tasks among heterogeneous robotic agents. This digital environment integrates several key exploitable results (KERs) identified in TALOS’s development roadmap, including:

• AI-based fault detection systems supported by digital twins of PV plants;
• Autonomous ground and surface vehicles for cleaning, mowing and inspection;
• Unmanned aerial vehicles (UAVs) for visual and thermal analysis;and 
• A robot control and coordination platform enabling human-in-the-loop supervision.

All components are connected through a cloud-based data management architecture that allows the seamless exchange of information between robots, sensors and operators. The data collected feed predictive models, enabling maintenance to be scheduled precisely when and where it is most effective.

When robots take over solar maintenance

Preliminary tests across the TALOS pilots show a substantial reduction in routine manual interventions. Cleaning and mowing operations, traditionally performed by field workers under high temperature conditions or in difficult terrain, can now be executed autonomously. Robots are capable of operating continuously without downtime, guided by AI-optimised routes that account for obstacles, weather and energy availability.

By shifting repetitive and risky activities to machines, operators are freed for higher value analytical tasks while safety incidents decrease. This is particularly evident in large solar farms, where the frequency of maintenance directly correlates with worker exposure to heat stress and physical strain.

TALOS integrates AI fault detection systems that compare live sensor data with expected performance profiles generated by digital twins. These models simulate the behaviour of PV systems under various environmental conditions, allowing deviations to be identified before they escalate into costly failures.

Through this approach, the project demonstrates how predictive maintenance can replace traditional reactive models. Instead of waiting for faults to appear, operators can rely on automated recommendations that prioritise interventions according to the potential energy loss or financial impact. This data-driven logic not only improves uptime but also extends the lifespan of critical components.

Each PV context presents unique technical and environmental constraints. On land-based sites, robots must navigate uneven surfaces and variable vegetation density. Floating systems add the complexity of water movement, requiring lightweight designs, adaptive mooring and water-resistant navigation systems. Agri-PV installations face a different challenge: maintaining delicate crops while sharing sunlight with solar panels.

TALOS addresses these variations by customising the robotic solutions to each environment. For example, lightweight electric robots reduce soil compaction in orchards, while floating cleaning units recycle water to minimise environmental impact. This modular approach demonstrates the versatility of robotic design and its potential to be scaled across Europe’s heterogeneous PV landscape.

Automation within TALOS extends beyond mechanical tasks. The project’s smart energy management system, developed in collaboration with research partners, ensures that robots operate in synchrony with the local energy ecosystem. Charging stations are positioned strategically to use surplus solar power, while AI algorithms schedule robotic missions according to real-time energy production.

Circular logic

This circular logic transforms maintenance from a cost-driven necessity into an active component of energy efficiency. By integrating robotics with renewable generation, TALOS shows how automation can contribute to a broader decarbonisation strategy.

The introduction of robotics into PV operations has significant implications for labour, cost and sustainability. Automated maintenance lowers operational expenditure, a crucial factor given that operation and maintenance represent roughly one-quarter of the levelised cost of electricity for PV systems.

At the same time, automation fosters new employment profiles in system supervision, data analytics and robotic maintenance. Instead of eliminating jobs, TALOS points to a shift towards more technical and safer roles. Environmentally, the precise application of resources such as water or cleaning agents contributes to lower waste and reduced carbon footprint.

TALOS exemplifies how robotics and AI can redefine the economics and sustainability of solar energy. Through a living-lab framework and real-world pilots, the project demonstrates that autonomous operations are not a distant vision but an emerging reality capable of improving reliability, safety and cost efficiency.

As Europe accelerates its transition to renewable energy, projects like TALOS provide a practical blueprint for digital transformation in the solar sector. The next steps include refining interoperability among robotic systems, ensuring regulatory alignment and supporting the market uptake of these technologies.

For more information, visit the project website.

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