Automatic Arecanut Harvester

Abstract

Manual harvesting of arecanut (betel nut) palms is slow, dangerous, and costly. We propose a quadcopter-based harvester: a small drone carrying a cutting blade, controlled by an STM32 microcontroller. The STM32 reads an MPU-9250 IMU (accelerometer/gyro) to estimate attitude, and a PID controller maintains a stable hover.

A 2.4 GHz nRF24L01 radio link lets an operator control the throttle and steering remotely. In prototype tests, the UAV hovered steadily and successfully severed arecanut bunches from tree branches. This electric drone significantly reduces human labor and hazards, although limited battery life and payload remain constraints. Future work will add autonomous navigation and higher-capacity batteries to enable longer, self-guided harvesting missions.

1. Introduction

Arecanut is a major plantation crop in southern India, but harvesting it is “dull and dangerous.” Workers must climb tall, smooth palm trunks with ropes and sickles, risking falls, injury, and labour shortage. Aerial robots (drones) offer a promising remedy. By flying to the nut clusters, a UAV can collect data or carry tools without endangering people. In agriculture, drones already optimize operations and improve yields: they survey fields, spray chemicals much faster than ground crews.

Motivated by these benefits, this project’s objective is to design a quadcopter UAV that can detach arecanut bunches from palms. The goal is a proof-of-concept system — initially radio-controlled — that safely approaches nut clusters and cuts the bunches for collection, increasing efficiency and worker safety.

2. System Overview

The UAV harvesting platform integrates standard drone hardware with a custom cutter. Its main components are:

• Flight Controller (STM32 MCU + IMU):
  STM32F41CEU6 microcontroller running on-board firmware. An MPU-9250 IMU (3-axis gyro + accel + magnetometer) is connected via I²C to measure roll, pitch, and yaw. The STM32 computes filtered attitude angles (complementary filter) and runs PID loops to stabilize the quadcopter.

• Propulsion (Motors & ESCs):
  Four brushless DC (BLDC) motors with propellers provide lift. Each motor is driven by an ESC controlled by PWM outputs from the STM32. Prototype uses 10″ propellers with matched motors for sufficient thrust.

• Wireless Link (nRF24L01 Radio):
  A 2.4 GHz nRF24L01+ transceiver module serves as the RC link. One module on the UAV and a paired module on a handheld transmitter send pilot commands (throttle, yaw, pitch, roll) over SPI. In tests the link provided a reliable control range of tens of meters.

• Cutter Mechanism:
  A small cutting blade is mounted under/above the drone (prototype shows above), driven by a servo-actuated arm on a linear guide. When positioned under a nut cluster, the blade swings/slides to sever the bunch from the stem. A locking pin holds the cutter during flight. The blade unit was sized to cut tough palm stalks.

Prototype images

3. Flight Control and Wireless Link

The STM32 flight controller implements a cascaded PID control scheme. Gyroscope and accelerometer readings from the IMU are fused (complementary filter) to estimate orientation. We tuned three nested PID loops:

1. Inner loop — stabilizes angular rates (gyros).
2. Outer loop — stabilizes angles (roll, pitch, yaw).
3. Thrust/torque mapping — converts PID outputs into four motor speed commands.

This arrangement lets the UAV hold altitude and resist disturbances. For remote operation the nRF24L01+ link sends pilot inputs from a handheld controller to the UAV receiver. The pilot can center the sticks to hold position while the controller cancels drift; during cutting the pilot positions the blade and triggers the cutter.

4. Testing and Results

Hover Stability

In flight tests the tuned PID controller produced smooth hovering. After takeoff the quadcopter held altitude with only minor oscillation. Roll and pitch stayed within a few degrees even in light breeze.

Harvest Trials

A dynamometer measured the force needed to cut arecanut stalks. In field trials the UAV approached low-hanging clusters and the cutter activated; the blade successfully severed the stems and the bunches dropped free in all harvest tests. The quadcopter absorbed cutter recoil without flipping or tipping, confirming safe flight characteristics.

Safety and Failsafe

Basic safety responses were verified. A low-battery cutoff was implemented: when voltage drops below threshold the system throttles down and lands.

5. Literature Review

• Areca Harvesting Technologies: Semi-automatic tree climbers and some UAV modules (e.g., Rakesh et al., 2020) show mechanical feasibility for mounted harvesters.
• Drone-based Fruit Picking: Examples include suction grippers and multi-DOF end-effectors for hexacopters (Varadaramanujan et al., 2017; Park et al., 2024) — relevant for grasping/approach kinematics without destabilizing the UAV.
• Flight Control Systems: Patrol quadcopters using STM32 + MPU9250 with EKF and cascaded PID controllers (Tang & Lin, 2021) informed our sensor and controller choices.

6. Advantages and Limitations

Advantages

• Increases productivity and reduces the need for risky climbing work (estimated 60–70% cost reduction in labour in some cases).
• Improves worker safety by removing the need for humans to climb tall palms.
• Electric operation avoids on-site exhaust; precise blade control yields clean cuts and preserves tree health.

Limitations

• Flight time: prototype endurance ~10–15 minutes per battery — limits number of trees per sortie.
• Payload/endurance tradeoff: cutter and battery weight reduce flight time.
• Manual operation: no autonomous navigation or target detection in current system.
• Operational challenges: dense plantations, wind, and obstacles complicate flight.
• Reach & cost: fixed cutting range and hardware cost (hundreds of dollars), so cost-effectiveness depends on scale and further development.

7. Conclusion and Future Scope

This project demonstrated a working quadcopter arecanut harvester prototype. An STM32 flight controller with cascaded PID loops stabilized the UAV; an nRF24L01+ radio link supported remote manual operation. The drone hovered steadily in tests and its cutter successfully removed arecanut bunches.

For future work

• On-board vision (camera + onboard compute) to detect nut bunches and guide the cutter for autonomy.
• Improve power systems: higher capacity batteries or swappable packs to lengthen mission time.
• Refine cutter mechanism: e.g., add a collection basket to catch cut nuts safely.
• Develop path planning and obstacle avoidance for denser plantations and longer missions.

Appendix / Notes

• Hardware used (prototype): STM32F41CEU6, MPU-9250 IMU, nRF24L01+ transceivers, BLDC motors + ESCs, 10″ propellers, servo-actuated cutter.
• Report: pending coordinator approval (Report ID: 56326a67-bc65-4bf1-ae11-0bb45c83a0cd, created 2025-04-29T05:40:26.474Z, updated 2025-08-09T11:46:04.072Z).

End of report.