ArticleSensors (Basel, Switzerland)2014
A proposal for automatic fruit harvesting by combining a low cost stereovision camera and a robotic arm.
Article in Sensors (Basel, Switzerland), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Maintenance Cost Minimization for an Agricultural Harvesting Gripper.Sensors (Basel, Switzerland) · 2023Article
- Recognition and Counting of Apples in a Dynamic State Using a 3D Camera and Deep Learning Algorithms for Robotic Harvesting Systems.Sensors (Basel, Switzerland) · 2023Article
- Adaptive control of a wheelchair mounted robotic arm with neuromorphically integrated velocity readings and online-learning.Frontiers in neuroscience · 2022Article
- The Concept of the Constructional Solution of the Working Section of a Robot for Harvesting Strawberries.Sensors (Basel, Switzerland) · 2021Article
- Soft Grippers for Automatic Crop Harvesting: A Review.Sensors (Basel, Switzerland) · 2021Review
- Green Grape Detection and Picking-Point Calculation in a Night-Time Natural Environment Using a Charge-Coupled Device (CCD) Vision Sensor with Artificial Illumination.Sensors (Basel, Switzerland) · 2018Article
- On-Tree Mango Fruit Size Estimation Using RGB-D Images.Sensors (Basel, Switzerland) · 2017Article
- Robust Grape Cluster Detection in a Vineyard by Combining the AdaBoost Framework and Multiple Color Components.Sensors (Basel, Switzerland) · 2016Article
- Vineyard yield estimation based on the analysis of high resolution images obtained with artificial illumination at night.Sensors (Basel, Switzerland) · 2015Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper proposes the development of an automatic fruit harvesting system by combining a low cost stereovision camera and a robotic arm placed in the gripper tool. The stereovision camera is used to estimate the size, distance and position of the fruits whereas the robotic arm is used to mechanically pickup the fruits. The low cost stereovision system has been tested in laboratory conditions with a reference small object, an apple and a pear at 10 different intermediate distances from the camera. The average distance error was from 4% to 5%, and the average diameter error was up to 30% in the case of a small object and in a range from 2% to 6% in the case of a pear and an apple. The stereovision system has been attached to the gripper tool in order to obtain relative distance, orientation and size of the fruit. The harvesting stage requires the initial fruit location, the computation of the inverse kinematics of the robotic arm in order to place the gripper tool in front of the fruit, and a final pickup approach by iteratively adjusting the vertical and horizontal position of the gripper tool in a closed visual loop. The complete system has been tested in controlled laboratory conditions with uniform illumination applied to the fruits. As a future work, this system will be tested and improved in conventional outdoor farming conditions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.