Estimating uncertain spatial relationships in robotics
Autonomous robot vehicles
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
FastSLAM: a factored solution to the simultaneous localization and mapping problem
Eighteenth national conference on Artificial intelligence
Techniques for Deep Sea Near Bottom Survey Using an Autonomous Underwater Vehicle
International Journal of Robotics Research
Algorithm for computer control of a digital plotter
IBM Systems Journal
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
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In this paper, we describe the control, navigation, and mapping methods that were developed for a hovering autonomous underwater vehicle that explored flooded cenotes in Mexico. The cenotes of Sistema Zacat脙鲁n in Tamaulipas, Mexico are flooded sinkholes, exotic geological formations with unique water chemistry. The largest, Zacat脙鲁n, is over 300-m deep. None of the cenotes were mapped before the present DEPTHX project. The goals of the DEPTHX project were to construct metrically accurate three-dimensional maps of the cenotes, and to collect environmental data, imagery, water samples, and core samples. The unknown extent of the cenotes, together with the challenging scientific mission, spurred the development of a robotic vehicle that autonomously, with no communications to the surface, built accurate three-dimensional maps using sonar and collected a variety of scientific data, including core samples from the cenote walls. In this paper, we describe the design, implementation, and testing of the robot software, as well as the results from mapping four cenotes of Sistema Zacat脙鲁n.