Soft manipulator robot for selective tomato harvesting
dc.contributor.author | Mohamed, A | |
dc.contributor.author | Shaw-Sutton, J | |
dc.contributor.author | Green, BM | |
dc.contributor.author | Andrews, W | |
dc.contributor.author | Rolley-Parnell, EJ | |
dc.contributor.author | Zhou, Y | |
dc.contributor.author | Zhou, P | |
dc.contributor.author | Mao, X | |
dc.contributor.author | Fuller, MP | |
dc.contributor.author | Stoelen, MF | |
dc.date.accessioned | 2019-09-04T14:46:09Z | |
dc.date.available | 2019-09-04T14:46:09Z | |
dc.date.issued | 2019-07-08 | |
dc.identifier.isbn | 9789086863372 | |
dc.identifier.uri | http://hdl.handle.net/10026.1/14873 | |
dc.description.abstract |
The harvesting of soft fruits and vegetables is a labour-intensive process, often representing more than 50% of the total costs for the producer. In this paper, a harvesting robot is proposed for tomato picking. The robotic solution is developed to address the needs of tomato producers in the Shanghai region in China, one that faces population growth and therefore a higher demand on food supply. The robotic system presented consists of a variable-stiffness manipulator arm, a soft robot gripper, and different types of sensors that are used to identify and locate in 3D and pick the tomatoes. The implemented variable compliance enables the robot manipulator to work in a semi-structured environment without damage to itself, the crop or the surrounding. The hardware and software of the robot is described in detail. Early results from the first testing of a proof-of-concept on fresh tomatoes placed on artificial stems in Shanghai are presented, as well as picking UK tomato varieties in greenhouse conditions. | |
dc.format.extent | 799-805 | |
dc.language.iso | en | |
dc.publisher | Wageningen Academic Publishers | |
dc.title | Soft manipulator robot for selective tomato harvesting | |
dc.type | conference | |
dc.type | Conference Proceeding | |
plymouth.conference-name | 12th European Conference on Precision Agriculture | |
plymouth.publication-status | Published | |
plymouth.journal | Precision agriculture ’19 | |
dc.identifier.doi | 10.3920/978-90-8686-888-9_99 | |
plymouth.organisational-group | /Plymouth | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA/UoA06 Agriculture, Veterinary and Food Science | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA/UoA11 Computer Science and Informatics | |
plymouth.organisational-group | /Plymouth/Users by role | |
plymouth.organisational-group | /Plymouth/Users by role/Academics | |
dcterms.dateAccepted | 2019-01-01 | |
dc.rights.embargodate | 2023-7-18 | |
dc.rights.embargoperiod | Not known | |
rioxxterms.versionofrecord | 10.3920/978-90-8686-888-9_99 | |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | |
rioxxterms.type | Conference Paper/Proceeding/Abstract |