499 research outputs found
A parallel hypothesis method of autonomous underwater vehicle navigation
Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution June 2009This research presents a parallel hypothesis method for autonomous underwater vehicle
navigation that enables a vehicle to expand the operating envelope of existing
long baseline acoustic navigation systems by incorporating information that is not
normally used. The parallel hypothesis method allows the in-situ identification of
acoustic multipath time-of-flight measurements between a vehicle and an external
transponder and uses them in real-time to augment the navigation algorithm during
periods when direct-path time-of-flight measurements are not available. A proof of
concept was conducted using real-world data obtained by the Woods Hole Oceanographic
Institution Deep Submergence Lab's Autonomous Benthic Explorer (ABE)
and Sentry autonomous underwater vehicles during operations on the Juan de Fuca
Ridge.
This algorithm uses a nested architecture to break the navigation solution down
into basic building blocks for each type of available external information. The algorithm
classifies external information as either line of position or gridded observations.
For any line of position observation, the algorithm generates a multi-modal block
of parallel position estimate hypotheses. The multimodal hypotheses are input into
an arbiter which produces a single unimodal output. If a priori maps of gridded
information are available, they are used within the arbiter structure to aid in the
elimination of false hypotheses. For the proof of concept, this research uses ranges
from a single external acoustic transponder in the hypothesis generation process and
grids of low-resolution bathymetric data from a ship-based multibeam sonar in the
arbitration process.
The major contributions of this research include the in-situ identification of acoustic
multipath time-of-flight measurements, the multiscale utilization of a priori low-resolution
bathymetric data in a high-resolution navigation algorithm, and the design
of a navigation algorithm with a
exible architecture. This flexible architecture allows
the incorporation of multimodal beliefs without requiring a complex mechanism for
real-time hypothesis generation and culling, and it allows the real-time incorporation
of multiple types of external information as they become available in situ into the
overall navigation solution
Cooperative AUV Navigation using a Single Maneuvering Surface Craft
In this paper we describe the experimental implementation of an online algorithm for cooperative localization of submerged autonomous underwater vehicles (AUVs) supported by an autonomous surface craft. Maintaining accurate localization of an AUV is difficult because electronic signals, such as GPS, are highly attenuated by water. The usual solution to the problem is to utilize expensive navigation sensors to slow the rate of dead-reckoning divergence. We investigate an alternative approach that utilizes the position information of a surface vehicle to bound the error and uncertainty of the on-board position estimates of a low-cost AUV. This approach uses the Woods Hole Oceanographic Institution (WHOI) acoustic modem to exchange vehicle location estimates while simultaneously estimating inter-vehicle range. A study of the system observability is presented so as to motivate both the choice of filtering approach and surface vehicle path planning. The first contribution of this paper is to the presentation of an experiment in which an extended Kalman filter (EKF) implementation of the concept ran online on-board an OceanServer Iver2 AUV while supported by an autonomous surface vehicle moving adaptively. The second contribution of this paper is to provide a quantitative performance comparison of three estimators: particle filtering (PF), non-linear least-squares optimization (NLS), and the EKF for a mission using three autonomous surface craft (two operating in the AUV role). Our results indicate that the PF and NLS estimators outperform the EKF, with NLS providing the best performance.United States. Office of Naval Research (Grant N000140711102)United States. Office of Naval Research. Multidisciplinary University Research InitiativeSingapore. National Research FoundationSingapore-MIT Alliance for Research and Technology. Center for Environmental Sensing and Monitorin
Information-Aware Guidance for Magnetic Anomaly based Navigation
In the absence of an absolute positioning system, such as GPS, autonomous
vehicles are subject to accumulation of positional error which can interfere
with reliable performance. Improved navigational accuracy without GPS enables
vehicles to achieve a higher degree of autonomy and reliability, both in terms
of decision making and safety. This paper details the use of two navigation
systems for autonomous agents using magnetic field anomalies to localize
themselves within a map; both techniques use the information content in the
environment in distinct ways and are aimed at reducing the localization
uncertainty. The first method is based on a nonlinear observability metric of
the vehicle model, while the second is an information theory based technique
which minimizes the expected entropy of the system. These conditions are used
to design guidance laws that minimize the localization uncertainty and are
verified both in simulation and hardware experiments are presented for the
observability approach.Comment: 2022 International Conference on Intelligent Robots and Systems
October 23 to 27, 2022 Kyoto, Japa
Efficient AUV Navigation Fusing Acoustic Ranging and Side-scan Sonar
This paper presents an on-line nonlinear least
squares algorithm for multi-sensor autonomous underwater
vehicle (AUV) navigation. The approach integrates the global
constraints of range to and GPS position of a surface vehicle
or buoy communicated via acoustic modems and relative pose
constraints arising from targets detected in side-scan sonar images.
The approach utilizes an efficient optimization algorithm,
iSAM, which allows for consistent on-line estimation of the
entire set of trajectory constraints. The optimized trajectory
can then be used to more accurately navigate the AUV, to
extend mission duration, and to avoid GPS surfacing. As iSAM
provides efficient access to the marginal covariances of previously
observed features, automatic data association is greatly
simplified — particularly in sparse marine environments. A
key feature of our approach is its intended scalability to
single surface sensor (a vehicle or buoy) broadcasting its GPS
position and simultaneous one-way travel time range (OWTT)
to multiple AUVs. We discuss why our approach is scalable
as well as robust to modem transmission failure. Results are
provided for an ocean experiment using a Hydroid REMUS
100 AUV co-operating with one of two craft: an autonomous
surface vehicle (ASV) and a manned support vessel. During
these experiments the ranging portion of the algorithm ran online
on-board the AUV. Extension of the paradigm to multiple
missions via the optimization of successive survey missions (and
the resultant sonar mosaics) is also demonstrated.United States. Office of Naval Research (Grant N000140711102
Cooperative monocular-based SLAM for multi-UAV systems in GPS-denied environments
This work presents a cooperative monocular-based SLAM approach for multi-UAV systems that can operate in GPS-denied environments. The main contribution of the work is to show that, using visual information obtained from monocular cameras mounted onboard aerial vehicles flying in formation, the observability properties of the whole system are improved. This fact is especially notorious when compared with other related visual SLAM configurations. In order to improve the observability properties, some measurements of the relative distance between the UAVs are included in the system. These relative distances are also obtained from visual information. The proposed approach is theoretically validated by means of a nonlinear observability analysis. Furthermore, an extensive set of computer simulations is presented in order to validate the proposed approach. The numerical simulation results show that the proposed system is able to provide a good position and orientation estimation of the aerial vehicles flying in formation.Peer ReviewedPostprint (published version
Synchronous-Clock, One-Way-Travel-Time Acoustic Navigation for Underwater Vehicles
This paper reports the development and deployment of a synchronous-clock acoustic navigation system suitable for the simultaneous navigation of multiple underwater vehicles. Our navigation system is composed of an acoustic modem–based communication and navigation system that allows for onboard navigational data to be broadcast as a data packet by a source node and for all passively receiving nodes to be able to decode the data packet to obtain a one-way-travel-time (OWTT) pseudo-range measurement and navigational ephemeris data. The navigation method reported herein uses a surface ship acting as a single moving reference beacon to a fleet of passively listening underwater vehicles. All vehicles within acoustic range are able to concurrently measure their slant range to the reference beacon using the OWTT measurement methodology and additionally receive transmission of reference beacon position using the modem data packet. The advantages of this type of navigation system are that it can (i) concurrently navigate multiple underwater vehicles within the vicinity of the surface ship and (ii) provide a bounded-error XY position measure that is commensurate with conventional moored long-baseline (LBL) navigation systems [i.e., ] but unlike LBL is not geographically restricted to a fixed-beacon network. We present results for two different field experiments using a two-node configuration consisting of a global positioning system–equipped surface ship acting as a global navigation aid to a Doppler-aided autonomous underwater vehicle. In each experiment, vehicle position was independently corroborated by other standard navigation means. Results for a maximum likelihood sensor fusion framework are reported.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86046/1/reustice-2.pd
Underwater Localization System Combining iUSBL with Dynamic SBL in ¡VAMOS! Trials
Emerging opportunities in the exploration of inland water bodies, such as underwater mining of flooded open pit mines, require accurate real-time positioning of multiple underwater assets. In the mining operation scenarios, operational requirements deny the application of standard acoustic positioning techniques, posing additional challenges to the localization problem. This paper presents a novel underwater localization solution, implemented for the ¡VAMOS! project, based on the combination of raw measurements from a short baseline (SBL) array and an inverted ultrashort baseline (iUSBL). An extended Kalman filter (EKF), fusing IMU raw measurements, pressure observations, SBL ranges, and USBL directional angles, estimates the localization of an underwater mining vehicle in 6DOF. Sensor bias and the speed of sound in the water are estimated indirectly by the filter. Moreover, in order to discard acoustic outliers, due to multipath reflections in such a confined and cluttered space, a data association layer and a dynamic SBL master selection heuristic were implemented. To demonstrate the advantage of this new technique, results obtained in the field, during the ¡VAMOS! underwater mining field trials, are presented and discussed.This work was funded by the ¡VAMOS! project funded by the European Commission under the H2020 EU Framework Programme for Research and by National Funds through the Portuguese funding agency, FCT (Fundação para a Ciência e a Tecnologia), within project UIDB/50014/2020 and TEC4SEA - Modular Platform for Research, Test and Validation of Technologies supporting a Sustainable Blue Economy from National Roadmap for Research Infrastructures of Strategic Interest, NORTE-01-0145-FEDER-022097- PINFRA/22097/2016.info:eu-repo/semantics/publishedVersio
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