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  <title><![CDATA[PhD Proposal by Luis F. W. Batista]]></title>
  <body><![CDATA[<p>Title: Autonomous System for Identifying and Capturing Floating Waste</p><p>&nbsp;</p><p>Luis F. W. Batista</p><p>Ph.D. Student in Computer Science</p><p>School of Interactive Computing</p><p>Georgia Tech-Europe</p><p>&nbsp;</p><p>Date: 30th April, 2025</p><p>Time: 10:00–11:30 am Eastern (16:00-17:30 CEST)</p><p>&nbsp;</p><p>Location: Virtual</p><p><strong>Microsoft Teams</strong>&nbsp;<a href="https://aka.ms/JoinTeamsMeeting?omkt=en-US" target="_blank" title="https://aka.ms/JoinTeamsMeeting?omkt=en-US">Need help?</a></p><p><a href="https://teams.microsoft.com/l/meetup-join/19%3ameeting_NWQxMWViNWQtMjhhZC00NTdlLWFmZjAtMzY5ODk0NTBlNDIz%40thread.v2/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%220b47e7b0-fb74-4852-b1f8-86c17559a776%22%7d" target="_blank" title="https://teams.microsoft.com/l/meetup-join/19%3ameeting_NWQxMWViNWQtMjhhZC00NTdlLWFmZjAtMzY5ODk0NTBlNDIz%40thread.v2/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%220b47e7b0-fb74-4852-b1f8-86c17559a776%22%7d"><strong>Join the meeting now</strong></a></p><p>Meeting ID: 282 920 901 69</p><p>Passcode: SG27gj2J</p><p>&nbsp;</p><p>Committee:</p><p>Dr. Cédric Pradalier (Advisor) - School of Interactive Computing - Georgia Institute of Technology</p><p>Dr. Seth Hutchinson (Co-advisor) - School of Interactive Computing - Georgia Institute of Technology</p><p>Dr. Sehoon Ha - School of Interactive Computing - Georgia Institute of Technology</p><p>Dr. Harish Ravichandar - School of Interactive Computing - Georgia Institute of Technology</p><p>&nbsp;</p><p>Abstract</p><p>Plastic pollution in aquatic environments presents a pressing ecological issue. This thesis develops an autonomous system for detecting and collecting floating waste, integrating advanced visual perception, reinforcement learning-based control, with field-tests validation. Key contributions include the use of polarimetric imaging to improve perception on reflective water surfaces, and a robust reinforcement learning framework for navigation that accounts for real-world hydrodynamics. The perception and control components are combined into a complete pipeline, validated through extensive simulation and real-world field trials to demonstrate the system's effectiveness and potential for scalable environmental cleanup applications</p>]]></body>
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