PulkitĀ Rustagi

Multi-Objective Planning Using Context-Based Preferences at Oregon State University

Corvallis, Oregon, United States
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Summary

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Senior
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Top School
Pulkit Rustagi is a Robotics Ph.D. candidate at Oregon State University with 10 years of experience designing scalable multi-agent and multi-objective planning systems for real robots. He developed the Contextual Lexicographic MDP framework and algorithms that fuse context-specific policies into global, cycle-free controllers validated on Turtlebots, and also created RECON to mitigate negative side effects in systems scaling to ~1000 agents. His work blends theory (contraction-based L1 adaptive control, credit assignment for blame) with hands-on firmware and ROS/Gazebo implementation, demonstrated across UAV swarms and mobile robots. Pulkit has driven projects from high-accuracy UWB localization to satellite attitude control, showing a consistent ability to translate advanced control and planning research into field-tested systems. An understated strength is his knack for bridging simulation and hardware, ensuring algorithms remain robust when deployed in the real world.
code10 years of coding experience
job1 year of employment as a software developer
bookDoctor of Philosophy - PhD, Robotics, Doctor of Philosophy - PhD, Robotics at Oregon State University
bookUniversity of Illinois Urbana-Champaign
bookBachelor of Technology - BTech, Bachelor of Technology - BTech at Indian Institute of Technology, Kharagpur
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Github Skills (19)

intellisense6
vscode5
vscode-extension5
python5
simulator5
simulation5
visual-studio-code4
visual-studio4
pylint3
ros3
robotics3
matlab2
python-extension2
geometric2
model-predictive-control1

Programming languages (5)

TypeScriptC++CMATLABPython

Github contributions (5)

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PulkitRustagi/RobotSystems

Jan 2025 - Feb 2025

Contributions:78 pushes, 1 branch in 1 month
Contributions:16 pushes, 2 branches in 1 year 1 month
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