Visual State Estimation of Marine Vessels from Monocular Horizon Views Using Lie Groups

Derek Benham, Joshua G. Mangelson

Paper Under Preparation

Low-Cost Urban Localization with Magnetometer and LoRa Technology

Derek Benham, Ashton Palacios, Philip Lundrigan, Joshua G. Mangelson

International Conference on Intelligent Robots and Systems (IROS) 2024, Abu Dhabi, UAE

With the goal of developing low-cost and innovative perception and localization techniques for autonomous vehicles, this work explores a system that solely relies on a LoRa receiver and a magnetometer for agent localization within urban environments. Using the received signal strength from LoRa beacons distributed across a test area of 16,000 square meters, a model of expected RSSI values per beacon is estimated using Gaussian Process (GP) regression. Motion is estimated using a probabilistic signal similarity classifier, and localization is obtained via a particle filter. Our experiments demonstrate that our proposed system is able to estimate our location to within three meters RMSE. In real-world scenarios, characterized by signal interference and environmental complexities, our approach highlights the potential of leveraging affordable technology such as LoRa receivers and magnetometers for robust and accurate location estimation in complex urban environments. The integration of low-cost LoRa devices, Gaussian Process regression, particle filtering and our novel signal similarity motion estimator offers a promising avenue for achieving cost-effective localization solutions without compromising accuracy or reliability.

3D Reconstruction of Reefs using Autonomous Surface Vessels and an Analysis of Chain vs 3D Rugosity Measurement Robustness

Derek Benham, Aaron Newman, Kalai Ellis, Richard Gill, and Joshua G. Mangelson

IEEE/OES Oceans Conference 2022, Hampton Roads, VA

Coral reefs are at risk. To study and minimize the impacts of global warming, pollution, or land sediment disposition on the reef, regular and accurate measurements are needed to assess the coral's health. We present a method of using surface vessels to autonomously collect GPS-tagged images to be used in creating a 3D model of the reef which we tested in Molokai, Hawaii. We also discuss the shortcomings of chain rugosity measurements (the longtime standard for categorizing reef health) and how surface complexity measurements, a metric only obtained from creating 3D models from imagery are less subject to these flaws.