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Tree Planting Drones: Extended-Range Flight for Autonomous Large-Scale Reforestation

AJAS · 2026

Michael Xu · New Jersey Academy of Science

Overview

Restoring biodiverse forest ecosystems and their associated carbon sinks would help substantially mitigate the effects of climate change. Drone-based reforestation offers greater efficiency compared to land-based approaches, but limitations in flight range, seed survival, and operating costs limit widespread application. The objective of this research was to develop an extended-range quadcopter drone capable of autonomous, large-scale tree seed dispersion and reforestation. After progressing through 5 design iterations, undergoing 55 test-flights, and enduring 37 crashes, a large 7.6kg quadcopter drone with a 2.5m frame and 0.9m propellers was engineered. To extend the drone’s flight time beyond existing constraints, a series of innovations were made to the motor/propeller system, frame, and flight controller to maximize efficiency. The drone was engineered to accommodate a wide variety of seed pod designs, dispensing the optimal seed type and burying mechanism to maximize seed survival in the local environment. Combined with advanced sensors, autonomous navigation, and self-stabilization capabilities, a novel drone capable of large-scale tree-planting in distant, deforested, or fire-affected regions was produced. Additionally, with extended flight range, this quadcopter can also be applied to a variety of long range and high payload applications, such as monitoring solar and wind infrastructure, assessing crop health, surveying disaster zones, and delivering heavy parcels.

Competition history

  • AJAS 2026 Category not listed

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Source: AAAS Annual Meeting (Confex) / American Junior Academy of Science

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