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Welcome to The Turf Zone Podcast. This episode features the article “Autonomous Mowing on Trial” written by Landon Erbrick, Paul Bartley, Mark Hoffman and Tanzeel Rehman of Auburn University and J. Bryan Unruh of the University of Florida.

As the landscape industry faces mounting labor challenges, tightening environmental regulations, and growing pressure to improve efficiency, the emergence of mowing technologies are generating widespread attention. But do these machines actually deliver on their promises of cost savings, labor efficiency, and sustainability?

A multi-disciplinary team of researchers from Auburn University, the University of Florida, and the University of Georgia has launched a multi-year research initiative to answer that very question. Supported by industry partners and the United States Department of Agriculture (USDA), this effort is part of a larger grant-funded project titled “Landscape Equipment Sustainability Strategies: Do More with LESS.” The project involves a comprehensive evaluation of large-platform autonomous mowers to assess their real-world performance, cost-effectiveness, and operational safety across a variety of landscape conditions.

Why This Research Matters

The adoption of automation in turf care is no longer a theoretical discussion. Manufacturers have introduced commercial autonomous platforms, and early adopters are already deploying them on sports fields, university campuses, and business parks, yet independent research remains scarce on the topic.

Most prior studies have focused on small-platform robotic mowers primarily used in residential settings. Traditionally, these machines relied on perimeter wires and random navigation patterns, limiting their efficiency and scalability. However, recent technological advancements—such as real-time kinematic (RTK) positioning and EPOS (Exact Positioning Operating System) navigation—have dramatically improved the precision, reliability, and adaptability of small autonomous mowers. This rapid evolution in positioning and sensing technologies has expanded the potential for autonomy in turf management far beyond the homeowner market.

Building on these advancements, large-platform autonomous mowers, that is, commercial-scale machines capable of operating both manually and autonomously, have now entered the market. These systems aim to address many of the industry’s most pressing challenges, including labor shortages, rising operational costs, and increasing sustainability demands. Our research seeks to evaluate these emerging technologies through a rigorous, data-driven approach to help landscape contractors, municipalities, and turf managers make informed decisions about integrating autonomy into large-scale operations.

What We’re Testing & Why It Matters

This project is evaluating large-platform commercial mowers across four equipment categories:

• Manual gas-powered
• Manual battery-powered
• Autonomous gas-powered
• Autonomous battery-powered

We’re conducting real-world field trials using standardized test plots with varying levels of landscape complexity, from open square acres to obstacle-rich environments designed to mimic trees, bed edges, and other site constraints. Our goal is to understand how different combinations of power source (gas vs. battery) and operator mode (manual vs. autonomous) influence performance, cost, safety, and usability in professional landscaping scenarios.

What We’re Measuring

Across hundreds of acres of mowing in diverse conditions, we’re tracking:

• Labor Efficiency – Time per acre, supervision requirements, and total operator hours
• Energy or Fuel Consumption – Gallons or kilowatt-hours per acre
• Mowing Productivity – Speed (acres/hour) under manual vs. autonomous operation
• Cost of Ownership – Lifetime return on investment (ROI) including equipment price, maintenance, energy, and labor
• Operational Safety & Setup Time – Issues related to autonomous deployment, landscape variability, and required oversight
• Adaptability to Landscape Types – How autonomy performs in simple vs. complex site conditions

Together, these data will help landscape contractors, fleet managers, and municipal buyers evaluate whether, how, and when to adopt autonomous and battery-powered equipment based on real numbers, not hype or pressure.

Safety and Supervision Under the Microscope

We’re also conducting obstacle detection trials using mannequins and field hazards at multiple approach angles to understand how these machines interpret and react to real-world variables.

Our team is especially interested in hybrid operation strategies, where a single operator supervises an autonomous unit while mowing with another, significantly boosting productivity without a full leap into autonomy.

Implications for the Green Industry

This research comes at a critical time. As noise restrictions, emissions regulations (e.g., California AB 1346), and labor shortages reshape the industry, many contractors are asking: What’s the smart next investment?

By delivering field-tested, brand-agnostic insights, our goal is to help professionals:

• Make evidence-based equipment choices
• Optimize labor deployment strategies
• Understand technology limitations and serviceability
• Prepare for future regulations and automation trends.

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