Rethinking how robots “see” in agriculture

One of the toughest challenges in agricultural robotics is working in natural, unstructured environments. Dense leaves, twisting vines, and shaded fruit can block cameras, limiting a robot’s ability to prune, harvest, or detect ripeness.

Unfortunately, many tactile sensors available today are either too fragile, too expensive, or simply impractical for large-scale farming.

That’s why researchers at Carnegie Mellon University are exploring an exciting new approach: SonicBoom.

Instead of vision systems, SonicBoom uses an array of six specially protected contact microphones housed inside a PVC pipe. When the sensor touches something, it picks up vibrations. By analyzing the differences in sound waves, the system can determine the exact point of contact—within just 0.43 to 2.2 cm of precision—and potentially even identify what the object is.

Key advantages:

• Durable and low-cost: Built to survive harsh field conditions.
• Adaptable: Can be embedded directly into robotic arms.
• Versatile: Suitable for vineyards, horticulture, and even vertical farms.

The potential impact extends beyond agriculture. Imagine safer robots working in close proximity to humans, or navigating dark, confined environments where cameras fall short.

For regions like Qatar, Saudi Arabia, and the UAE—where food security is a top priority—this innovation could play a pivotal role in advancing controlled-environment farming.

Looking ahead, SonicBoom highlights how shifting from “seeing” to “feeling” could unlock the next generation of robotics across both farming and industry.