Research

Using Simulations to Aid Robot Learning

Simulations are the primary way for a robot to predict actions and safely learn. This project investigates how we can train robot task models using simulations, and how those models can be helpful for human teachers and operators.

SAIL: Simulation-Informed Active In-the-Wild Learning
Elaine Schaertl Short, Adam Allevato, Andrea L. Thomaz
Conference paper, to appear at HRI 2019

2 additional papers under review

Affordance Discovery using Simulated Exploration
Adam Allevato, Andrea L. Thomaz, Mitch Pryor
Extended abstract, AAMAS 2018
PDF | bibtex


3D Computer Vision for Robotics

Using Point Cloud Library and OpenCV, I developed a 3D pose estimation library based on Robot Operating System (ROS). I showed that the library was effective for use in robotic sorting, remote inspection, and small part picking. The library has not (yet) been made public, but only due to lack of demand. If you’re interested, shoot me an email.

An Object Recognition and Pose Estimation Library for Intelligent Industrial Automation
Adam Allevato
Masters’ thesis, Spring 2016
PDF | bibtex


Glovebox Workcell Manufacturing and Integration

In this three-year project, our team at the Nuclear and Applied Robotics Group (NRG) deployed robots in various configurations inside nuclear gloveboxes. Developed in conjunction with Los Alamos National Laboratory, we investigated visual recognition, mixed-waste sorting, and manufacturing tasks such as automated hole drilling with a highly customized robotic system.

This project resulted in a number of publicly-available ROS packages, many of which are available on the NRG lab’s GitHub pages, which I helped run.

Automated Glovebox Workcell Design
Edwin Paredes, Christina Petlowany, Matthew Horn, Adam Allevato, Mitch Pryor
Conference paper, WMS 2018

Demonstrating Autonomous and Robust Sorting in a Glovebox Environment
Adam Allevato, Matthew Horn, Mitch Pryor
Conference paper, ANS D&RS 2016
PDF | bibtex

Characterizing Glovebox Automation Tasks using Partially Observable Markov Decision Processes
Adam Allevato, Mitch Pryor
Conference paper, ANS D&RS 2016
PDF | bibtex

Using a Depth Camera for Object Classification in Nuclear Gloveboxes
Adam Allevato, Thomas Lu, Mitch Pryor
Podium Presentation/Technical Session, 2015 ANS Student Conference
PDF | bibtex


Choosing Observation Points for a Camera Robot

We developed an algorithm to select a viewpoint from which to observe a task. This can be useful in a two-robot scenario where one robot is the “cameraman” and the other is the “worker” or “actor.” The camera viewpoint is chosen so as to stay out of the actor’s way, while still providing a good view of the task region.

Getting the Shot: Socially-Aware Viewpoints for Autonomously Observing Tasks
Adam Allevato, Andrew Sharp, Mitch Pryor
Conference paper, ARSO 2017
site | PDFbibtex | slides | code


Hough Transform Calculator

The Hough Transform is a computer vision technique for searching for structure (like lines or circles) in an image. This was a final project for a computer graphics class.

site