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SEQUENCE:1
X-APPLE-TRAVEL-ADVISORY-BEHAVIOR:AUTOMATIC
235076
20260422T152320Z
DTSTART;TZID=America/New_York:20260428T090000
DTEND;TZID=America/New_York:2
 0260428T103000
URL;TYPE=URI:https://www.wpi.edu/news/calendar/events/robot
 ics-engineering-masters-thesis-presentation-adil-shiyas
Robotics Engineering Master\&#039;s Thesis Presentation: Adil Shiyas
COAD: Constant-Time Planning for Continuous Goal Manipulation with Compress
 ed Library and Online Adaptation\n\n\n\n      \n      \n\n\n\nAbstract:  I
 n many robotic manipulation tasks, the robot repeatedly solves motion-plan
 ning problems that differ mainly in the location of the goal object and it
 s associated obstacle, while the surrounding workspace remains fixed. Prio
 r works have shown that leveraging experience and offline computation can 
 accelerate repeated planning queries, but they lack guarantees of covering
  the continuous task space and require storing large libraries of solution
 s. In this work, we present COAD, a framework that provides constant-time 
 planning over a continuous goal-parameterized task space. COAD discretizes
  the continuous task space into finitely many Task Coverage Regions. Inste
 ad of planning and storing solutions for every region offline, it construc
 ts a compressed library by only solving representative root problems. Othe
 r problems are handled through fast adaptation from these root solutions. 
 At query time, the system retrieves a root motion in constant time and ada
 pts it to the desired goal using lightweight adaptation modules such as li
 near interpolation, Dynamic Movement Primitives, or simple trajectory opti
 mization. We evaluate the framework on various manipulators and environmen
 ts in simulation and the real world, showing that COAD achieves substantia
 l compression of the motion library while maintaining high success rates a
 nd sub-millisecond-level queries, outperforming baseline methods in both e
 fficiency and path quality.\nAdvisor: Professor Constantinos ChamzasCommit
 tee: Professor Kevin Leahy, Professor Griffin Tabor\n
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