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X-APPLE-TRAVEL-ADVISORY-BEHAVIOR:AUTOMATIC
234296
20260407T092459Z
DTSTART;TZID=America/New_York:20260421T153000
DTEND;TZID=America/New_York:2
 0260421T170000
URL;TYPE=URI:https://www.wpi.edu/news/calendar/events/robot
 ics-engineering-masters-thesis-presentation-jaskrit-singh
Robotics Engineering Master\'s Thesis Presentation - Jaskrit Singh
DGT-Map: Directional Global Traversability Mapping Utilizing Multi-Task Lea
 rning for Heterogeneous Vehicles\n\n\n\n      \n      \n\n\n\nAbstract: Of
 f-road traversability is direction-dependent and influenced by vehicle dyn
 amics, yet most traversability maps assign a single isotropic cost per loc
 ation and cannot generalize across vehicles. This work introduces DGT-Map,
  a self-supervised framework for learning directional, global traversabili
 ty costmaps from RGB-D observations. The method predicts a locomotion-deri
 ved signal for terrain patches using a convolutional neural network traine
 d on fused color and geometric features. By utilizing multi-task learning 
 across multiple vehicles, the model learns a shared terrain representation
  while still capturing vehicle specific differences.. At inference, DGT-Ma
 p generates heading-indexed costmaps that integrate into a Hybrid A* plann
 ing framework. The system is evaluated on challenging terrains, including 
 slopes that are traversable downhill but not uphill and ridge obstacles fe
 asible for some vehicles but not others. Across tasks and vehicles, DGT-Ma
 p improves navigation success by 30-40% over geometric, binary, and learne
 d direction-agnostic baselines.\nAdvisor: Professor Constantinos ChamzasCo
 mmittee: Professor Jing Xiao, Professor Nitin Sanket\n
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