{"id":{"repo_id":"uwo","oai_identifier":"oai:uwo.scholaris.ca:20.500.14721/27890"},"canonical_url":"https://search.dev.ndltd.org/etd/uwo/oai:uwo.scholaris.ca:20.500.14721/27890","repository":{"repo_id":"uwo","name":"Western University","base_url":"https://uwo.scholaris.ca/server/oai/request"},"display":{"title":"Development of a Real-Time 3D Mushroom Vision System for Autonomous Mushroom Harvesting","abstract":"The agricultural industry is developing autonomous systems to sustain the demands of global population growth. There are many challenges associated with the development of autonomous systems for the agricultural industry because of their dynamic and constrained environments. An example is the mushroom harvesting industry as it requires an indoor, dark, and highly humid environment for the rapid growth of mushrooms on narrowly stacked compost beds. Manual labour is currently the only acceptable method of harvesting mushrooms, but overtime, the harsh conditions cause high worker turn-over rates, driving the cost of manual labour up while overall reducing the potential of the industry. A mushroom scanner was developed to scan a mushroom bed in real-time and to provide the data to a recently developed mobile harvesting unit, designed to pick mushrooms using a robotic claw, which up until now, lacked the ability to find them. The scanner can precisely determine the 3D position and orientation of all visible mushrooms using a custom real-time image processing algorithm. The algorithm then filters the data for target sized mushrooms and sends commands to the harvesting unit for picking with high precision. The mushroom scanner system was designed, developed, and tested in both laboratory and industrial settings, and has proven its potential in the mushroom harvesting industry.","abstract_html":"The agricultural industry is developing autonomous systems to sustain the demands of global population growth. There are many challenges associated with the development of autonomous systems for the agricultural industry because of their dynamic and constrained environments. An example is the mushroom harvesting industry as it requires an indoor, dark, and highly humid environment for the rapid growth of mushrooms on narrowly stacked compost beds. Manual labour is currently the only acceptable method of harvesting mushrooms, but overtime, the harsh conditions cause high worker turn-over rates, driving the cost of manual labour up while overall reducing the potential of the industry. A mushroom scanner was developed to scan a mushroom bed in real-time and to provide the data to a recently developed mobile harvesting unit, designed to pick mushrooms using a robotic claw, which up until now, lacked the ability to find them. The scanner can precisely determine the 3D position and orientation of all visible mushrooms using a custom real-time image processing algorithm. The algorithm then filters the data for target sized mushrooms and sends commands to the harvesting unit for picking with high precision. The mushroom scanner system was designed, developed, and tested in both laboratory and industrial settings, and has proven its potential in the mushroom harvesting industry.","abstract_has_math":false,"creators":["Glibetic, Stefan"],"institution":"The University of Western Ontario","degree_name":"M Eng Sci","degree_level":null,"degree_discipline":"Electrical and Computer Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Mehrdad Kermani"],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-12-08","date_published":"2017-12-08","updated_at":"2026-07-27T21:56:09Z","subjects":["Automation","Agriculture","Autonomous Harvesting","Machine Vision","Active Stereo"],"languages":["en_ca"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/20.500.14721/27890","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Mehrdad Kermani"]},{"key":"dc:creator","label":"Author","values":["Glibetic, Stefan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-07-10T15:33:43Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2025-07-10T15:33:43Z"]},{"key":"dc:date.issued","label":"Date","values":["2017-12-08"]},{"key":"dc:publisher","label":"Institution","values":["The University of Western Ontario"]},{"key":"dc:type","label":"Dc Type","values":["thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical and Computer Engineering"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M Eng Sci"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Automation","Agriculture","Autonomous Harvesting","Machine Vision","Active Stereo"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en_ca"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/20.500.14721/27890"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The thesis cover page in the PDF document includes references to Western University’s previous institutional repository platform, known as Scholarship@Western, and links to that platform (beginning with ir.lib.uwo.ca). In citing or referring to this thesis, use the DOI or handle from this page instead. Sample citation: Author name, \"Thesis title.\" (Year). Western University Open Repository. https://doi.org/10.71858/123456."]},{"key":"dc:description.abstract","label":"Abstract","values":["The agricultural industry is developing autonomous systems to sustain the demands of global population growth. There are many challenges associated with the development of autonomous systems for the agricultural industry because of their dynamic and constrained environments. An example is the mushroom harvesting industry as it requires an indoor, dark, and highly humid environment for the rapid growth of mushrooms on narrowly stacked compost beds. Manual labour is currently the only acceptable method of harvesting mushrooms, but overtime, the harsh conditions cause high worker turn-over rates, driving the cost of manual labour up while overall reducing the potential of the industry. A mushroom scanner was developed to scan a mushroom bed in real-time and to provide the data to a recently developed mobile harvesting unit, designed to pick mushrooms using a robotic claw, which up until now, lacked the ability to find them. The scanner can precisely determine the 3D position and orientation of all visible mushrooms using a custom real-time image processing algorithm. The algorithm then filters the data for target sized mushrooms and sends commands to the harvesting unit for picking with high precision. The mushroom scanner system was designed, developed, and tested in both laboratory and industrial settings, and has proven its potential in the mushroom harvesting industry."]},{"key":"dc:title","label":"Title","values":["Development of a Real-Time 3D Mushroom Vision System for Autonomous Mushroom Harvesting"]}]}],"canonical_facts":{"dc:contributor.advisor":["Mehrdad Kermani"],"dc:creator":["Glibetic, Stefan"],"dc:date.accessioned":["2025-07-10T15:33:43Z"],"dc:date.available":["2025-07-10T15:33:43Z"],"dc:date.issued":["2017-12-08"],"dc:description":["The thesis cover page in the PDF document includes references to Western University’s previous institutional repository platform, known as Scholarship@Western, and links to that platform (beginning with ir.lib.uwo.ca). In citing or referring to this thesis, use the DOI or handle from this page instead. Sample citation: Author name, \"Thesis title.\" (Year). Western University Open Repository. https://doi.org/10.71858/123456."],"dc:description.abstract":["The agricultural industry is developing autonomous systems to sustain the demands of global population growth. There are many challenges associated with the development of autonomous systems for the agricultural industry because of their dynamic and constrained environments. An example is the mushroom harvesting industry as it requires an indoor, dark, and highly humid environment for the rapid growth of mushrooms on narrowly stacked compost beds. Manual labour is currently the only acceptable method of harvesting mushrooms, but overtime, the harsh conditions cause high worker turn-over rates, driving the cost of manual labour up while overall reducing the potential of the industry. A mushroom scanner was developed to scan a mushroom bed in real-time and to provide the data to a recently developed mobile harvesting unit, designed to pick mushrooms using a robotic claw, which up until now, lacked the ability to find them. The scanner can precisely determine the 3D position and orientation of all visible mushrooms using a custom real-time image processing algorithm. The algorithm then filters the data for target sized mushrooms and sends commands to the harvesting unit for picking with high precision. The mushroom scanner system was designed, developed, and tested in both laboratory and industrial settings, and has proven its potential in the mushroom harvesting industry."],"dc:identifier.uri":["https://hdl.handle.net/20.500.14721/27890"],"dc:language.iso":["en_ca"],"dc:publisher":["The University of Western Ontario"],"dc:subject":["Automation","Agriculture","Autonomous Harvesting","Machine Vision","Active Stereo"],"dc:title":["Development of a Real-Time 3D Mushroom Vision System for Autonomous Mushroom Harvesting"],"dc:type":["thesis"],"thesis:degree_discipline":["Electrical and Computer Engineering"],"thesis:degree_name":["M Eng Sci"]},"updated_at":"2026-07-27T21:56:09Z"}