System Design and Control of an Apple Harvesting Robot
By Kaixiang Zhang, Kyle Lammers, Pengyu Chu, Zhaojian Li, Renfu Lu. arXiv.org, 2020
386 citations recorded by the source corpus.
There is a growing need for robotic apple harvesting due to decreasing availability and rising cost in labor. Towards the goal of developing a viable robotic system for apple harvesting, this paper presents synergistic mechatronic design and motion control of a robotic apple harvesting prototype, which lays a critical foundation for future advancements. Specifically, we develop a deep learning-based fruit detection and localization system using an RGB-D camera. A three degree-of-freedom manipulator is then designed with a hybrid pneumatic/motor actuation mechanism to achieve fast and dexterous movements. A vacuum-based end-effector is used for apple detaching. These three components are integrated into a robotic apple harvesting prototype with simplicity, compactness, and robustness. Moreover, a nonlinear velocity-based control scheme is developed for the manipulator to achieve accurate and agile motion control. Test experiments are conducted to demonstrate the performance of the developed apple harvesting robot.
Subfields: Plant Science
View Paper: https://www.semanticscholar.org/paper/394c385e27e42d68c347e716ed8756b37f7bc3d9
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In Plant Science
Citations in the corpus
- Automation in Agriculture by Machine and Deep Learning Techniques: A Review of Recent Developments (2021, methodology): “…which consisted of a manipulator, end-effector, and vision system, whereas the SVM with RBF (radial basis function) was used for the recognition of apples, and the effectiveness of the system was shown by performing the experiments in the laboratory and real agricultural farms (De-An et al., 2011).”
- Research and development in agricultural robotics: a perspective of digital farming. (2018, background): “…configuration for visual servo control [49,80-82] , optimal manipulator design and control [29,38] , end-effector and gripper design [8,83] , stability tests for robot performance analysis in the dense obstacle environments [84] , motion planning algorithms [85] , and orchard…”
- Cucumber Fruits Detection in Greenhouses Based on Instance Segmentation (2019, background): “Fruit detection is an important research filed in precision agriculture, which is widely applied to yield estimation, and fruit picking robot [1]–[3].”
- IoT, Big Data, and Artificial Intelligence in Agriculture and Food Industry (2020, neutral): “Robotic arm and end effector research continued to improve accuracy and speed of gripping and detaching apples from trees [44-46].”