{"id":{"repo_id":"uoit","oai_identifier":"oai:ontariotechu.scholaris.ca:10155/1051"},"canonical_url":"https://search.dev.ndltd.org/etd/uoit/oai:ontariotechu.scholaris.ca:10155/1051","repository":{"repo_id":"uoit","name":"Ontario Institute of Technology","base_url":"https://ontariotechu.scholaris.ca/server/oai/request"},"display":{"title":"Development of an obstacle detection and navigation system for autonomous powered wheelchairs","abstract":"This thesis describes the development and prototyping of an after market system to convert an electric powered wheelchair into an autonomous wheelchair. The purpose of this research is to automatize powered wheelchairs for children who are impacted by conditions such as cerebral palsy. Maneuvering a powered wheelchair with a joystick is difficult and painful for users who have a high level of cerebral deficiency and other chronic conditions. The autonomous powered wheelchair is designed to maneuver in an indoor environment whilst avoiding static and dynamic obstacles. The add-on system comprised of stereo vision sensors (ZED Camera), and IMU is designed to use Robot Operating System (ROS) to communicate and control the movement of the wheelchair. With the addition of a 3D map of the environment generated using visual sensors through ROS packages, the system identifies and avoids obstacles. Simultaneous Localization and Mapping (SLAM) and autonomous navigation packages were tested and modified. Slopes and drops identified in the 3D map are converted such that they are compatible with the 2D navigation packages of ROS. Configuration settings were determined and tested to ensure that the system works as required. The results demonstrated that the powered wheelchair can be modified to become an autonomous wheelchair using ZED Camera and IMU, such that it can navigate indoors effectively avoiding static and dynamic obstacles.","abstract_html":"This thesis describes the development and prototyping of an after market system to convert an electric powered wheelchair into an autonomous wheelchair. The purpose of this research is to automatize powered wheelchairs for children who are impacted by conditions such as cerebral palsy. Maneuvering a powered wheelchair with a joystick is difficult and painful for users who have a high level of cerebral deficiency and other chronic conditions. The autonomous powered wheelchair is designed to maneuver in an indoor environment whilst avoiding static and dynamic obstacles. The add-on system comprised of stereo vision sensors (ZED Camera), and IMU is designed to use Robot Operating System (ROS) to communicate and control the movement of the wheelchair. With the addition of a 3D map of the environment generated using visual sensors through ROS packages, the system identifies and avoids obstacles. Simultaneous Localization and Mapping (SLAM) and autonomous navigation packages were tested and modified. Slopes and drops identified in the 3D map are converted such that they are compatible with the 2D navigation packages of ROS. Configuration settings were determined and tested to ensure that the system works as required. The results demonstrated that the powered wheelchair can be modified to become an autonomous wheelchair using ZED Camera and IMU, such that it can navigate indoors effectively avoiding static and dynamic obstacles.","abstract_has_math":false,"creators":["Diwan, Heta"],"institution":"University of Ontario Institute of Technology","degree_name":"Master of Applied Science (MASc)","degree_level":null,"degree_discipline":"Mechanical Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Nokleby, Scott"],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-05-01","date_published":"2019-05-01","updated_at":"2026-07-24T05:35:30Z","subjects":["Robotics","Autonomous wheelchair","Obstacle detection","Slope and stair detection","Autonomous navigation"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10155/1051","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Nokleby, Scott"]},{"key":"dc:creator","label":"Author","values":["Diwan, Heta"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2019-07-05T19:16:23Z","2022-03-29T16:49:30Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2019-07-05T19:16:23Z","2022-03-29T16:49:30Z"]},{"key":"dc:date.issued","label":"Date","values":["2019-05-01"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical Engineering"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Applied Science (MASc)"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Ontario Institute of Technology"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Robotics","Autonomous wheelchair","Obstacle detection","Slope and stair detection","Autonomous navigation"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10155/1051"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This thesis describes the development and prototyping of an after market system to convert an electric powered wheelchair into an autonomous wheelchair. The purpose of this research is to automatize powered wheelchairs for children who are impacted by conditions such as cerebral palsy. Maneuvering a powered wheelchair with a joystick is difficult and painful for users who have a high level of cerebral deficiency and other chronic conditions. The autonomous powered wheelchair is designed to maneuver in an indoor environment whilst avoiding static and dynamic obstacles. The add-on system comprised of stereo vision sensors (ZED Camera), and IMU is designed to use Robot Operating System (ROS) to communicate and control the movement of the wheelchair. With the addition of a 3D map of the environment generated using visual sensors through ROS packages, the system identifies and avoids obstacles. Simultaneous Localization and Mapping (SLAM) and autonomous navigation packages were tested and modified. Slopes and drops identified in the 3D map are converted such that they are compatible with the 2D navigation packages of ROS. Configuration settings were determined and tested to ensure that the system works as required. The results demonstrated that the powered wheelchair can be modified to become an autonomous wheelchair using ZED Camera and IMU, such that it can navigate indoors effectively avoiding static and dynamic obstacles."]},{"key":"dc:title","label":"Title","values":["Development of an obstacle detection and navigation system for autonomous powered wheelchairs"]}]}],"canonical_facts":{"dc:contributor.advisor":["Nokleby, Scott"],"dc:creator":["Diwan, Heta"],"dc:date.accessioned":["2019-07-05T19:16:23Z","2022-03-29T16:49:30Z"],"dc:date.available":["2019-07-05T19:16:23Z","2022-03-29T16:49:30Z"],"dc:date.issued":["2019-05-01"],"dc:description.abstract":["This thesis describes the development and prototyping of an after market system to convert an electric powered wheelchair into an autonomous wheelchair. The purpose of this research is to automatize powered wheelchairs for children who are impacted by conditions such as cerebral palsy. Maneuvering a powered wheelchair with a joystick is difficult and painful for users who have a high level of cerebral deficiency and other chronic conditions. The autonomous powered wheelchair is designed to maneuver in an indoor environment whilst avoiding static and dynamic obstacles. The add-on system comprised of stereo vision sensors (ZED Camera), and IMU is designed to use Robot Operating System (ROS) to communicate and control the movement of the wheelchair. With the addition of a 3D map of the environment generated using visual sensors through ROS packages, the system identifies and avoids obstacles. Simultaneous Localization and Mapping (SLAM) and autonomous navigation packages were tested and modified. Slopes and drops identified in the 3D map are converted such that they are compatible with the 2D navigation packages of ROS. Configuration settings were determined and tested to ensure that the system works as required. The results demonstrated that the powered wheelchair can be modified to become an autonomous wheelchair using ZED Camera and IMU, such that it can navigate indoors effectively avoiding static and dynamic obstacles."],"dc:identifier.uri":["https://hdl.handle.net/10155/1051"],"dc:language.iso":["en"],"dc:subject":["Robotics","Autonomous wheelchair","Obstacle detection","Slope and stair detection","Autonomous navigation"],"dc:title":["Development of an obstacle detection and navigation system for autonomous powered wheelchairs"],"dc:type":["Thesis"],"thesis:degree_discipline":["Mechanical Engineering"],"thesis:degree_name":["Master of Applied Science (MASc)"],"thesis:institution_name":["University of Ontario Institute of Technology"]},"updated_at":"2026-07-24T05:35:30Z"}