James Johnson — accepted AI-conference papers

2021

AquaVis: A Perception-Aware Autonomous Navigation Framework for Underwater Vehicles

Marios Xanthidis, Michail Kalaitzakis, Nare Karapetyan, James Johnson, Nikolaos Vitzilaios, Jason M. O’Kane +1

IROS 2021poster

Visual monitoring operations underwater require both observing the objects of interest in close-proximity, and tracking the few feature-rich areas necessary for state estimation. This paper introduces the first navigation framework, called AquaVis, that produces on-line visibility-aware motion plans…

Cited by 15 Source ↗Scholar ↗

2021

Mental Models of AI Agents in a Cooperative Game Setting (Extended Abstract)

Katy Ilonka Gero, Zahra Ashktorab, Casey Dugan, Qian Pan, James Johnson, Werner Geyer +6

IJCAI 2021poster

As more and more forms of AI become prevalent, it becomes increasingly important to understand how people develop mental models of these systems. In this work we study people's mental models of an AI agent in a cooperative word guessing game. We run a study in which people play the game with an AI a…

Cited by 0 Source ↗PDF ↗Scholar ↗

2020

Navigation in the Presence of Obstacles for an Agile Autonomous Underwater Vehicle

Marios Xanthidis, Nare Karapetyan, Hunter Damron, Sharmin Rahman, James Johnson, Allison O’Connell +2

ICRA 2020poster

Navigation underwater traditionally is done by keeping a safe distance from obstacles, resulting in "fly-overs" of the area of interest. Movement of an autonomous underwater vehicle (AUV) through a cluttered space, such as a shipwreck or a decorated cave, is an extremely challenging problem that has…

Cited by 45 Source ↗Scholar ↗

2019

Experimental Comparison of Open Source Visual-Inertial-Based State Estimation Algorithms in the Underwater Domain

Bharat Joshi, Sharmin Rahman, Michail Kalaitzakis, Brennan Cain, James Johnson, Marios Xanthidis +5

IROS 2019poster

A plethora of state estimation techniques have appeared in the last decade using visual data, and more recently with added inertial data. Datasets typically used for evaluation include indoor and urban environments, where supporting videos have shown impressive performance. However, such techniques…

Cited by 119 Source ↗Scholar ↗