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  <title><![CDATA[PhD Defense by Lorenzo Ticozzi]]></title>
  <body><![CDATA[<p><strong>Title:</strong>&nbsp;Geometric Modeling, Control, and Estimation of Hybrid Rigid-Continuum Space Manipulators</p><p>&nbsp;</p><p><strong>Date:&nbsp;</strong>Thursday November 19, 2026</p><p><strong>Time:&nbsp;</strong>1:00 pm – 3:00 pm EST</p><p><strong>Location:&nbsp;</strong>Remote</p><p><strong>Meeting Link:</strong>&nbsp;<a href="https://teams.microsoft.com/meet/2327470462272752?p=e6lw2qUsvCu9SJS4C8">https://teams.microsoft.com/meet/2327470462272752?p=e6lw2qUsvCu9SJS4C8</a></p><p>&nbsp;</p><p><strong>Lorenzo Ticozzi</strong></p><p>Robotics PhD candidate</p><p>Daniel Guggenheim School of Aerospace Engineering</p><p>Georgia Institute of Technology</p><p>&nbsp;</p><p><strong>Committee:</strong></p><p>Dr. Panagiotis Tsiotras (Advisor) -&nbsp;School of Aerospace Engineering</p><p>Dr. Patricio Vela - School of Electrical and Computer Engineering</p><p>Dr. Yue Chen - School of Biomedical Engineering</p><p>Dr. Frank Dellaert - School of Interactive Computing</p><p>Dr. Yashwanth Nakka - School of Aerospace Engineering</p><p>&nbsp;</p><p><strong>Abstract:</strong></p><p>The current shift towards In-Space Servicing, Assembly, and Manufacturing (ISAM) calls for robotic systems that balance maneuvering precision with operational safety, capable of executing high-accuracy tasks while remaining safe in the presence of limited, uncertain information. Conventional rigid manipulators often require complex strategies to interact with fragile, uncooperative targets, while purely continuum robots are limited in payload capacity and maneuvering accuracy.&nbsp;</p><p>&nbsp;</p><p>This thesis investigates a Hybrid Rigid-Continuum Space Manipulator System that integrates a tendon-driven continuum appendage with a rigid robotic arm to bridge this gap. First, a minimal-order, closed-form dynamic model is derived using the Geometric Variable Strain (GVS) approach, resulting in a computationally efficient formulation of coupled floating-base spacecraft–manipulator dynamics that explicitly accounts for momentum conservation. Then, the proposed model is employed to design nonlinear state feedback controllers achieving stabilization and task-space trajectory-tracking. Next, this thesis develops a novel continuum-robot state estimation approach encoding the closed-form GVS kinematics within a factor graph framework, with improved accuracy and robustness over existing alternatives demonstrated both in simulations and experiments. Finally, we build upon the previous modeling and estimation contributions to present a kinematic framework for the complete state estimation of the space manipulator.</p>]]></body>
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