{"id":{"repo_id":"byu","oai_identifier":"oai:scholarsarchive.byu.edu:etd-1184"},"canonical_url":"https://search.dev.ndltd.org/etd/byu/oai:scholarsarchive.byu.edu:etd-1184","repository":{"repo_id":"byu","name":"Brigham Young University","base_url":"https://scholarsarchive.byu.edu/do/oai/"},"display":{"title":"An Ecological Display for Robot Teleoperation","abstract":"This thesis presents an interface for effectively teleoperating robots that combines an ecological display of range and video information with quickening based on dead-reckoning prediction. This display is built by viewing range and video information from a virtual camera trailing the robot. This is rendered in 3-D by using standard hardware acceleration and 3-D graphics software. Our studies demonstrate that this interface improves performance for most people, including those that do not have much previous experience with robotics. These studies involved 32 test subjects in a simulated environment and 8 in the real world. Subjects were required to drive the robot through several mazes while remembering a sequence of items. People took less time using the ecological interface and experienced fewer collisions, with a much lower workload as measured by joystick entropy. People preferred the interface over a standard interface with side-by-side range and video information and no prediction. Participants tended to rate the interface as more learn-able and more intuitive; participants also felt more confident in the robot's expected behavior.","abstract_html":"This thesis presents an interface for effectively teleoperating robots that combines an ecological display of range and video information with quickening based on dead-reckoning prediction. This display is built by viewing range and video information from a virtual camera trailing the robot. This is rendered in 3-D by using standard hardware acceleration and 3-D graphics software. Our studies demonstrate that this interface improves performance for most people, including those that do not have much previous experience with robotics. These studies involved 32 test subjects in a simulated environment and 8 in the real world. Subjects were required to drive the robot through several mazes while remembering a sequence of items. People took less time using the ecological interface and experienced fewer collisions, with a much lower workload as measured by joystick entropy. People preferred the interface over a standard interface with side-by-side range and video information and no prediction. Participants tended to rate the interface as more learn-able and more intuitive; participants also felt more confident in the robot&#x27;s expected behavior.","abstract_has_math":false,"creators":["Ricks, Robert W."],"institution":"Brigham Young University - Provo","degree_name":"MS","degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-24T01:27:25Z","subjects":["Ecological Interfaces","Teleoperation","Robotics","DirectX","Computer Science","Computer","Brigham Young University","Computer Sciences"],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarsarchive.byu.edu/etd/185","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Ricks, Robert W."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2004-08-31T07:00:00Z"]},{"key":"dc:publisher","label":"Institution","values":["Brigham Young University - Provo"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Ecological Interfaces","Teleoperation","Robotics","DirectX","Computer Science","Computer","Brigham Young University","Computer Sciences"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarsarchive.byu.edu/etd/185","https://scholarsarchive.byu.edu/context/etd/article/1184/viewcontent/ETD_CISOPTR_204.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Physical and Mathematical Sciences; Computer Science"]},{"key":"dc:description.abstract","label":"Abstract","values":["This thesis presents an interface for effectively teleoperating robots that combines an ecological display of range and video information with quickening based on dead-reckoning prediction. This display is built by viewing range and video information from a virtual camera trailing the robot. This is rendered in 3-D by using standard hardware acceleration and 3-D graphics software. Our studies demonstrate that this interface improves performance for most people, including those that do not have much previous experience with robotics. These studies involved 32 test subjects in a simulated environment and 8 in the real world. Subjects were required to drive the robot through several mazes while remembering a sequence of items. People took less time using the ecological interface and experienced fewer collisions, with a much lower workload as measured by joystick entropy. People preferred the interface over a standard interface with side-by-side range and video information and no prediction. 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Our studies demonstrate that this interface improves performance for most people, including those that do not have much previous experience with robotics. These studies involved 32 test subjects in a simulated environment and 8 in the real world. Subjects were required to drive the robot through several mazes while remembering a sequence of items. People took less time using the ecological interface and experienced fewer collisions, with a much lower workload as measured by joystick entropy. People preferred the interface over a standard interface with side-by-side range and video information and no prediction. 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