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Title: | SOFT AND HYBRID ROBOTICS FOR AGRITECHNOLOGY | Authors: | XING ZIHAO | ORCID iD: | orcid.org/0009-0008-9027-9936 | Keywords: | robot, additive manufacturing, 3D-printing, agritech, computer vision, deep learning | Issue Date: | 7-Dec-2022 | Citation: | XING ZIHAO (2022-12-07). SOFT AND HYBRID ROBOTICS FOR AGRITECHNOLOGY. ScholarBank@NUS Repository. | Abstract: | Vertical indoor farming represents a more sustainable alternative to traditional agriculture. Fruit and vegetables are planted at a high density in rows of tall racks. However, the profitability of such ventures is threatened by high operating costs. Here we show that the strawberry harvesting system includes the hybrid gripper, machine vision system and robot control system. The hybrid gripper made from hard and soft materials can pick the strawberry without cutting, thereby preventing undesirable damage to strawberry plants. The machine vision system can locate the strawberry stems in 3D coordinates by using deep learning and a stereo camera. The robot control system has high accuracy to control the robot arm and reach the picking point. This successful proof-of-concept system demonstrates the high potential of soft robotics as a promising technology for future agriculture technologies. | URI: | https://scholarbank.nus.edu.sg/handle/10635/238644 |
Appears in Collections: | Master's Theses (Open) |
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