3D Trunk Sensing for Orchard Harvester Row Alignment

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Solution Overview

Problem

Mechanical harvesting of oranges and similar row crops is challenging due to the risk of damaging trees, particularly from lateral and angular misalignments of harvesting machines, which can lead to trunk and branch breakage and subsequent disease.

Innovation Solution

The use of two 3D sensors, one arranged low on the vehicle and the other on the roof, to create horizontal and transversal point clouds that help align the vehicle with the tree row by identifying trunk positions and adjusting the vehicle's steering and rotor placement accordingly.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If the driver cabin is arranged on one side of the vehicle to be easily reached by the driver, then the driver can access the vehicle conveniently, but the driver does not have an optimal viewpoint to perfectly match the centerline of the vehicle over the trees alignment

Engineering Contradiction:

Improvedriver accessibilityVSAvoidalignment accuracy

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The patent replaces the mechanical/visual alignment method (driver viewing through cabin) with an optical sensing system (3D sensors/LiDAR) that automatically detects tree trunk positions and calculates misalignment, providing precise measurement without compromising driver accessibility

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces 3D sensors as an intermediary between the driver and the alignment task, where the sensors capture point cloud data of tree trunks and the processing unit calculates misalignment, mediating the alignment function separately from the driver's viewing position

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If the vehicle moves over the crop row with rotors close to the trees, then harvesting efficiency is improved, but the risk of trunk and thick branches breaking increases due to misalignment

Engineering Contradiction:

Improveharvesting efficiencyVSAvoidtree damage risk

Core Design Contradiction:

ProductivityVSObject-affected harmful factors

Solution Approach 1:

The patent implements a feedback loop where 3D sensors continuously scan tree trunk positions, the processing unit calculates lateral and angular misalignment in real-time, and the steering system adjusts the vehicle position to minimize misalignment, creating a closed-loop control that maintains safe spacing while harvesting

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent performs preliminary scanning and alignment calculation before the rotors reach the trees, using 3D sensors to detect trunk positions ahead of time and pre-adjust the vehicle steering to prevent misalignment-induced damage before it occurs

Inventive Principle:

Principle #10Preliminary action

3Reliability

If autonomous control is implemented to address misalignment issues, then tree damage is reduced, but the system complexity increases due to additional sensors and processing requirements

Engineering Contradiction:

Improvetree damage preventionVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent uses a multi-functional 3D sensor system that simultaneously performs tree trunk detection, point cloud generation, and misalignment calculation, allowing one sensor system to handle multiple tasks rather than requiring separate systems for each function

Inventive Principle:

Principle #6Universality (Multi-functionality)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This solution effectively reduces the risk of tree damage by ensuring precise alignment and positioning of the harvesting machine, enabling autonomous operation and improving the efficiency of the harvesting process.

Implementation Method 1

Each point of the point cloud represents a spot where the light—laser in the case of LiDAR—is back reflected by a part of an object in the scene

Methodology Applied

Scientific EffectLight back reflection: Reflection

Data Source

PatentUS20250155893A1Method for managing an agricultural vehicle during harvesting process in a plantation of fruit trees, such as an orange orchard

Publication Date: 2025.05.15 CNH IND ITALIA SPA

AI summary

A method for managing an agricultural vehicle during harvesting process in a plantation of fruit trees, such as an orange orchard, the vehicle being shaped as a portal capable of moving over a crop row and provided with a couple of rotors (R) arranged to work simultaneously on both opposite sides of each plant of the crop row, the method including process of recognition of the trunks of the trees of a plantation to be worked by means of a first 3D sensor (3DS) system interfaced with processing means (CPU) of an agricultural vehicle (V), wherein the first 3D sensor (3DS) system includes a couple of 3D sensors arranged in a low portion of the agricultural vehicle at opposite sides of the vehicle oriented such that to converge in common point (P) circa on a vehicle center line axis (VC) in front of the vehicle, the process including fitting of pseudo-ellipsoids in a horizontal slice of a merged point cloud generated by the two 3D sensors, in order to identify trunks of the crop row.