{"id":{"repo_id":"denver","oai_identifier":"oai:digitalcommons.du.edu:etd-3383"},"canonical_url":"https://search.dev.ndltd.org/etd/denver/oai:digitalcommons.du.edu:etd-3383","repository":{"repo_id":"denver","name":"University of Denver","base_url":"https://digitalcommons.du.edu/do/oai/"},"display":{"title":"Bridging Design and Perception: Novel Tools and Technologies for Creating Effective Human-Robot Interactions","abstract":"<p>This thesis explores human perception of robots through the use of novel tools and technologies. First, the impact of Augmented Reality (AR) data presentation on human perception of robots is investigated. A study conducted with the AR human-robot teaming system found that robot performance significantly influenced participants’ perceptions, overshadowing the impact of matching or mismatching robot confidence feedback. Second, the DU Want to Build-A-Bot platform is presented, which enables participatory robot design and opens the door for novel research of how robot design affects human perception. The Build-A-Bot platform enables the collection of diverse robot designs, facilitating machine learning analysis to pinpoint key design features that shape human mental models of robot capabilities.</p>","abstract_html":"&lt;p&gt;This thesis explores human perception of robots through the use of novel tools and technologies. First, the impact of Augmented Reality (AR) data presentation on human perception of robots is investigated. A study conducted with the AR human-robot teaming system found that robot performance significantly influenced participants’ perceptions, overshadowing the impact of matching or mismatching robot confidence feedback. Second, the DU Want to Build-A-Bot platform is presented, which enables participatory robot design and opens the door for novel research of how robot design affects human perception. The Build-A-Bot platform enables the collection of diverse robot designs, facilitating machine learning analysis to pinpoint key design features that shape human mental models of robot capabilities.&lt;/p&gt;","abstract_has_math":false,"creators":["Dossett, Benjamin"],"institution":null,"degree_name":"M.S. in Computer Science","degree_level":"Masters Thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Kerstin S. Haring","Christopher Reardon","Daniel Pittman","Pilyoung Kim"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-06-15T07:00:00Z","date_published":"2024-06-15T07:00:00Z","updated_at":"2026-07-24T02:01:48Z","subjects":["Human-computer interaction","Human-robot teaming","Robot design","Robotics","Theory of mind","Artificial Intelligence and Robotics","Cognition and Perception","Computer Engineering","Computer Sciences","Engineering","Other Computer Sciences","Psychology"],"languages":["English (eng)"],"rights":["<p>Copyright is held by the author. User is responsible for all copyright compliance.</p>"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.du.edu/etd/2402","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Kerstin S. 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