Binocular Vision Tracking for Fruit Vibration Harvesting
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Solution Overview
Problem
Current research on fruit vibration harvesting lacks detailed understanding of fruit movement during the harvesting process, particularly in mechanical vibration harvesting of fruits like red dates, walnuts, and ginkgo, where the movement of fruits is not adequately tracked to explain the principle of vibratory fruit dropping effectively.
Innovation Solution
A binocular-vision-based method for tracking fruit space attitude and motion, which involves marking feature points on the fruit, establishing coordinate systems, using high-speed cameras to photograph and process images, and calculating displacement, speed, and acceleration to track the fruit's movement and posture during vibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional vibration harvesting research views the tree as a second-order system and measures overall stiffness and damping ratio, then the theoretical basis for vibratory harvesting machinery is established, but the movement of fruits during the vibration harvesting process cannot be tracked in detail
Solution Approach 1:
The measurement system is segmented into multiple high-speed cameras positioned at different angles, each capturing specific aspects of fruit motion. The fruit itself is segmented by marking three distinct feature points on its surface, allowing independent tracking of each point's trajectory. This segmentation enables detailed reconstruction of three-dimensional fruit movement without requiring a single complex measurement system.
Solution Approach 2:
Marker points are introduced as intermediaries on the fruit surface to facilitate optical tracking. These markers serve as mediators between the fruit's actual motion and the camera system's measurement capability, converting complex fruit movement into trackable point trajectories that can be processed by vision algorithms.
2Loss of information
If high-speed cameras are used to photograph fruit dynamic motion and track feature points, then the movement trajectory and posture of fruit can be obtained, but the complexity of image processing and coordinate transformation increases
Solution Approach 1:
A connected base coordinate system is preliminarily established on the fruit before measurement, with its origin at the fruit-stem junction and axes aligned with key geometric features. This pre-established coordinate framework enables direct calculation of motion parameters from captured images without requiring complex post-processing coordinate transformations, as the marker points' coordinates can be directly related to the fruit's motion state.
Solution Approach 2:
The three-dimensional spatial coordinates of feature points are copied from two-dimensional image planes through binocular vision triangulation. Instead of directly measuring complex fruit posture, the system captures simplified point position information from multiple camera views and reconstructs three-dimensional coordinates, converting complex spatial measurement into manageable point cloud data processing.
3Reliability
If the cantilever straight beam model is used for tree vibration analysis, then the theoretical basis for vibratory harvesting is improved, but the detailed movement characteristics of individual fruits during vibration cannot be explained
Solution Approach 1:
The research approach transitions from macro-level tree vibration analysis to micro-level fruit motion tracking by adding the dimension of individual fruit observation. While the cantilever beam model describes overall tree vibration, the binocular vision system simultaneously captures three-dimensional trajectories of marker points on individual fruits, enabling analysis of fruit-specific motion characteristics that complement the theoretical model.
Solution Approach 2:
The system captures dynamic motion parameters including displacement, velocity, and acceleration of fruit feature points throughout the vibration process. By tracking the time-varying positions of markers on fruits during actual vibration harvesting operations, the system provides experimental dynamic data that validates and enriches the theoretical predictions of the cantilever beam model at the fruit level.
Data Source
AI summary
A binocular-vision-based method for tracking fruit space attitude and fruit space motion, the method comprising: establishing a connected base coordinate system by taking a junction of a fruit and a fruit stem as an origin; statically photographing a feature point on the surface of the fruit and a point of the connected base coordinate system established at the junction of the fruit and the fruit stem; storing a photographed image; acquiring an inherent relationship between the feature point and the connected base coordinate system; photographing dynamic motion of the fruit; acquiring absolute coordinates of the feature point on the surface of the fruit; calculating, according to the inherent relationship between the feature point and the connected base coordinate system, absolute coordinates of a point of the connected base coordinate system at each moment corresponding to each frame of image; and respectively calculating the displacement, instantaneous speed and instantaneous acceleration of the fruit, calculating swing angular displacement and swing angular acceleration of the fruit, and calculating a fruit torsion angular speed and a fruit torsion angular acceleration at the moment t. The study of a fruit motion state in the field of forest fruit harvest through vibration is performed, so that the motion of fruits can be better tracked.