{"678638":{"#nid":"678638","#data":{"type":"event","title":"MS Proposal by Abinay J. Brown","body":[{"value":"\u003Cp\u003EAbinay J. Brown\u003Cbr\u003E(Advisor: Prof. Kyriakos Vamvoudakis)\u003Cbr\u003Ewill propose a master\u2019s thesis entitled,\u003Cbr\u003EReal-Time Vision-Based Hazard Detection with Safe\u003Cbr\u003ETrajectory Optimization via Successive Convexification\u003Cbr\u003Efor Lunar Landing\u003Cbr\u003EOn\u003Cbr\u003EWednesday, December 3rd at 2:00 p.m.\u003Cbr\u003EMontgomery Knight Building 317\u003Cbr\u003EAbstract\u003Cbr\u003EWith the renewed interest in returning to the Moon, achieving autonomous and safe lunar descent and\u003Cbr\u003Elanding is paramount for the success of future missions. Safe and autonomous descent also reduces the\u003Cbr\u003Eoverhead logistics of pre-planning, surveying, and mapping lunar landing sites. During the descent phase\u003Cbr\u003Eof a lunar mission, the lander must steer away from rough terrain hazards and descend safely to the\u003Cbr\u003Esurface while constrained by fuel, maneuverability, and localization uncertainty. This thesis presents a\u003Cbr\u003Eframework for real-time state estimation, hazard detection from descent imagery, and safetyconstrained\u003Cbr\u003Etrajectory optimization. The proposed framework navigates using dead reckoning and\u003Cbr\u003EKalman filter-based sensor fusion to track the descent path using accelerometer and altimetry data\u003Cbr\u003Ewhile leveraging image segmentation computer vision models to identify lunar hazards such as craters\u003Cbr\u003Eand hills. Finally, a full-horizon minimum-time trajectory optimization problem with control and terminal\u003Cbr\u003Estate constraints is approached using successive convexification (SCvx) optimization scheme. Hazardous\u003Cbr\u003Eregions identified from descent imagery are represented as ellipse-based chance constraints enforced at\u003Cbr\u003Ethe terminal state, ensuring the lander avoids hazards with high confidence despite positional\u003Cbr\u003Euncertainty. The use of SCvx enables the decomposition of the nonlinear thrust vectoring dynamics and\u003Cbr\u003Econstraints into a series of convex subproblems, significantly enhancing computational efficiency and\u003Cbr\u003Eachieving real-time feasibility. This optimization is performed in a receding-horizon control loop,\u003Cbr\u003Eallowing the lander to continuously reoptimize and adapt its descent trajectory in response to updated\u003Cbr\u003Ehazard maps generated from real-time imagery. Simulations of the proposed framework are\u003Cbr\u003Eimplemented in a computer-generated 3D lunar environment to validate the approach.\u003Cbr\u003ECommittee\u003Cbr\u003E\uf0b7 Prof. Kyriakos Vamvoudakis \u2013 School of Aerospace Engineering (advisor)\u003Cbr\u003E\uf0b7 Prof. Lu Gan\u2013 School of Aerospace Engineering\u003Cbr\u003E\uf0b7 Prof. Glen Chou\u2013 School of Aerospace Engineering\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EReal-Time Vision-Based Hazard Detection with Safe\u003Cbr\u003ETrajectory Optimization via Successive Convexification\u003Cbr\u003Efor Lunar Landing\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Real-Time Vision-Based Hazard Detection with Safe Trajectory Optimization via Successive Convexification for Lunar Landing"}],"uid":"27707","created_gmt":"2024-11-25 18:40:27","changed_gmt":"2024-11-25 18:40:55","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-12-03T14:00:00-05:00","event_time_end":"2024-12-03T16:00:00-05:00","event_time_end_last":"2024-12-03T16:00:00-05:00","gmt_time_start":"2024-12-03 19:00:00","gmt_time_end":"2024-12-03 21:00:00","gmt_time_end_last":"2024-12-03 21:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Montgomery Knight Building 317","extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"166866","name":"MS Proposal"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}