Vision-Based Autonomous Robotic Fruit Harvester with Ripeness Classifier
RGB-D camera guidance pipeline identifying ripe tomatoes/apples, predicting 3D spatial center, and guiding a pneumatic suction gripper.
Project Overview
Integrates an Intel RealSense depth camera with a YOLOv8-Segment model. Classifies fruit ripeness based on colorimetric maturity indices, estimates 3D bounding spheres in camera coordinates, and feeds target coordinates to a robotic arm for gentle harvesting.
Integrates an Intel RealSense depth camera with a YOLOv8-Segment model. Classifies fruit ripeness based on colorimetric maturity indices, estimates 3D bounding spheres in camera coordinates, and feeds target coordinates to a robotic arm for gentle harvesting.
RGB-D camera guidance pipeline identifying ripe tomatoes/apples, predicting 3D spatial center, and guiding a pneumatic suction gripper.
Core Project Objectives
Capture continuous analog/digital sensor readings with robust noise filtering and hardware calibration.