ICRA2019: Streaming Scene Maps for Co-Robotic Exploration

We recently presented our paper titled Streaming Scene Maps for Co-Robotic Exploration in Bandwidth Limited Environments on enabling co-robotic exploration in bandwidth-limited environments at ICRA.…

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Barbados 2019 Field Trials

We just successfully completed our 2019 robot field trials at the Bellairs Research Institute 2019 Sea Trials in Holetown, Barbados. The main goals of the trials were to test our new ASV and AUV co-o…

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IROS2018: Approximate Distributed Spatiotemporal Topic Models for Multi-Robot Terrain Characterization.

Our paper on enabling distributed learning in bandwidth limited environments was one of the finalists for the best paper award at IROS 2018 (6 finalists among 1,254 accepted). Abstract: Unsupervised…

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Film: Coding Curiosity

A short film by Laura Castanon et. al, describing the exploration robotics research happening in WARPLab.…

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Co-Robotic Exploration in Bandwidth Constrained Environments

This project addresses the control and communications among underwater robotic vehicles to explore and map in ocean environments, where the communications are inherently low bandwidth, may be degraded…

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Learning Seasonal Phytoplankton Communities with Topic Models [2nd prize in the student poster competition at the OCEANS17]

We have developed a probabilistic generative model for phytoplankton communities. The proposed model takes counts of a set of phytoplankton taxa in a timeseries as its training data, and models commun…

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Summer Intern Project: SlickLizard Autonomous Surface Vehicle

USBL systems work best when there is not much horizontal distance between the transceiver and transponder. However, when deploying ROVs off a dock, there can be lots of distance between the USBL mode…

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IROS 2017: Feature discovery and visualization of robot mission data using convolutional autoencoders and Bayesian nonparametric topic modeling

Abstract: We introduce a novel unsupervised machine learning framework that incorporates the ability of convolutional autoencoders to discover features from images that directly encode spatial informa…

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ICRA 2017: Phytoplankton Hotspot Prediction With an Unsupervised Spatial Community Model

Many interesting natural phenomena are sparsely distributed and discrete. Locating the hotspots of such sparsely distributed phenomena is often difficult because their density gradient is likely to b…

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Visualizing AUV missions to Hannibal seamount

The following visualizations correspond to 16 dives by the SeaBed AUV at Hannibal seamount in Panama in 2015. These visualizations demonstrate that the learned model is automatically able to character…

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