Kartik Nagpal

Kartik Nagpal

Learning high-complexity robot interaction in safety-critical environments

Publications

Optimal Robotic Assembly Sequence Planning (ORASP): A Sequential Decision-Making Approach

Published in 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024

Proposed a new formulation of the robotic assembly sequencing problem as a Markov Decision Process. Then showed how a class of methods called Graph Exploration Assembly Planners (GEAPs) can be used to gather optimal assembly sequences from a graph. We then showcased a deep reinforcement learning extension for handling very complex structures, all while handling diverse constraints.

Recommended citation: [https://doi.org/10.1109/IROS58592.2024.10802475](https://doi.org/10.1109/IROS58592.2024.10802475)

Real-time quadrotor trajectory optimization with time-triggered corridor constraints

Published in AIAA Journal of Guidance, Control, and Dynamics, 2023

ONE of the challenges for flying quadrotors in cluttered envi-ronments is to optimize their trajectories subject to collision avoidance constraints in real time. Along such a trajectory, the position of the quadrotor must stay within a set of collision-free corridors. Each corridor is a bounded convex flight space.

Recommended citation: https://doi.org/10.2514/1.G007218

Transparency and Accountability in Space Domain Awareness: Demonstrating ASTRIAGraph’s Capabilities with the United Nations Registry Data

Published in Texas ScholarWorks, 2021

Near-earth space is geopolitically and commercially contested, and in need of environmental protection. To achieve space safety, security, and sustainability, we are developing ASTRIAGraph, a framework that enables monitoring, assessment, and verification of space actor behavior in the context of legal and policy instruments.

Recommended citation: http://dx.doi.org/10.26153/tsw/11754