Juliacon 2024

Angeline Aguinaldo

I am a Computer Science PhD Candidate at the University of Maryland, College Park (web) focusing on AI and robotics. My research leverages category theory to develop formal methods for modular plan composition, knowledge-based task planning, and plan migrations.

I am also a research staff member at the Johns Hopkins University Applied Physics Laboratory where I have designed and implemented prototype software platforms that support image analysis for humanitarian and disaster relief (info), test and evaluation of metagenomic classifiers (info), and data integration and analysis of social media and other publicly available information.


'What's the plan?', asked my robot
Angeline Aguinaldo

This talk delves into the challenges of developing task planning languages for robots in complex environments. In this work, we make use of categorical databases and rewriting methods, implemented in Julia, to effectively store and manipulate knowledge bases with large ontologies but sparse data. Julia's multiple dispatch and metaprogramming features have allowed us to develop a concise and scalable task planning system for robotic applications.

Method (1.5)