IDTechEx Research - Agricultural Robots and AI

A Question of When and Not If - Seite 2

Agricultural Robots: A Cost-Effective Precision Revolution?

Examples of these products or robots are shown below. These are often small or mid-sized robots which are designed to autonomously navigate and to automatically take some precise plant-specific action.

Machine vision technology is often a core competency of these robots, enabling the robots to see, identify, localise, and to take some intelligent site-specific action on individual plants. The machine vision increasingly uses deep learning algorithms often trained on expert-annotated image datasets, allowing the technology to far exceed the performance of conventional algorithms and to match or even exceed even that of expert agronomists. Crucially, this approach enables a long-term technology roadmap, which can be extended to recognize all types of crops and to analyse their associated conditions, e.g., water-stress, disease, etc.

Many versions of this emerging robotic class are autonomous. The autonomy challenge is much simpler than a car. The environment is well controlled and predictable, and the speed of travel is low. The legislation is today a hinderance, including in places such as California, but will become more accommodative relatively soon.

The rise of autonomous robots, provided they require little remote supervision, can alter the economics of machine design, enabling the rise of smaller and slower machines. Indeed, this elimination of the driver overhead per vehicle is the basis of the swarm concept. There is clearly a large productivity gap today between current large and high-power vehicles and those composed of fleets of slow small robots. This productivity gap however can narrow as the latter has substantial room for improvement.

The first major target market is in weeding. The ROI benefits here are driven by labour savings, chemical savings, boosted yields, and less land compaction. Precision action (spraying, mechanical, or electrical) reduces consumption of agrochemicals by 90% compared to untargeted application. It also improves yield (e.g., by 5-10%) because collateral damage of the crops by untargeted chemical application can be minimized. This technology can further enable farmers to tackle herbicide-resistant weeds, which are a growing problem, especially in some hotspots. Finally, the robots leave behind no unusable compacted soil.