{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/8601"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/8601","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Obstacle detection for robot navigation using structured light","abstract":"Obstacle detection is an essential function for autonomous mobile robots. Current autonomous systems are generally heavy, high-powered devices. Additionally, obstacle detection systems often employ active ranging sensors that exhibit poor angular resolution, thereby preventing vehicles from navigating through narrow spaces. Other systems require considerable processing to resolve objects. The work in this thesis attempts to design a small, lightweight, low-cost, and low-power system to detect obstacles in the direct field of view of a small robotic vehicle. In particular, the range to the obstacle as well as shape estimation is key data that would aid in robot navigation as well as data gathering. Rather than using conventional active or passive ranging techniques, this thesis examines projections of structured light to determine range to the obstacle and surface information of the obstruction. A physical model was developed and tested through simulation, and verified in hardware.","abstract_html":"Obstacle detection is an essential function for autonomous mobile robots. Current autonomous systems are generally heavy, high-powered devices. Additionally, obstacle detection systems often employ active ranging sensors that exhibit poor angular resolution, thereby preventing vehicles from navigating through narrow spaces. Other systems require considerable processing to resolve objects. The work in this thesis attempts to design a small, lightweight, low-cost, and low-power system to detect obstacles in the direct field of view of a small robotic vehicle. In particular, the range to the obstacle as well as shape estimation is key data that would aid in robot navigation as well as data gathering. Rather than using conventional active or passive ranging techniques, this thesis examines projections of structured light to determine range to the obstacle and surface information of the obstruction. A physical model was developed and tested through simulation, and verified in hardware.","abstract_has_math":false,"creators":["Tran, Deborah L. (Deborah Lynn Hong), 1978-"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.","school":null,"contributors":[],"advisors":["Kenneth M. Houston and Leslie Pack Kaelbling."],"committee_chairs":[],"committee_members":[],"year":2001,"date_issued":"2001","date_published":"2001","updated_at":"2026-07-22T22:21:40Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/8601","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Kenneth M. Houston and Leslie Pack Kaelbling."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. 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