Cooperative bathymetry-based localization using low-cost autonomous underwater vehicles

We present a cooperative bathymetry-based localization approach for a team of low-cost autonomous underwater vehicles (AUVs), each equipped only with a single-beam altimeter, a depth sensor and an acoustic modem. The localization of the individual AUV is achieved via fully decentralized particle filtering, with the local filter’s measurement model driven by the AUV’s altimeter measurements and ranging information obtained through inter-vehicle communication. We perform empirical analysis on the factors that affect the filter performance. Simulation studies using randomly generated trajectories as well as trajectories executed by the AUVs during field experiments successfully demonstrate the feasibility of the technique. The proposed cooperative localization technique has the potential to prolong AUV mission time, and thus open the door for long-term autonomy underwater.Massachusetts Institute of Technology. Department of Mechanical EngineeringSingapore-MIT Alliance for Research and Technology (SMART) (Graduate Fellowship

Low cost underwater acoustic localization

Over the course of the last decade, the cost of marine robotic platforms has significantly decreased. In part this has lowered the barriers to entry of exploring and monitoring larger areas of the earth's oceans. However, these advances have been mostly focused on autonomous surface vehicles (ASVs) or shallow water autonomous underwater vehicles (AUVs). One of the main drivers for high cost in the deep water domain is the challenge of localizing such vehicles using acoustics. A low cost one-way travel time underwater ranging system is proposed to assist in localizing deep water submersibles. The system consists of location aware anchor buoys at the surface and underwater nodes. This paper presents a comparison of methods together with details on the physical implementation to allow its integration into a deep sea micro AUV currently in development. Additional simulation results show error reductions by a factor of three.Comment: 73rd Meeting of the Acoustical Society of Americ

Cooperative algorithms for a team of autonomous underwater vehicles

Ph.DDOCTOR OF PHILOSOPH

Augmented Terrain-Based Navigation to Enable Persistent Autonomy for Underwater Vehicles in GPS-Denied Environments

Aquatic robots, such as Autonomous Underwater Vehicles (AUVs), play a major role in the study of ocean processes that require long-term sampling efforts and commonly perform navigation via dead-reckoning using an accelerometer, a magnetometer, a compass, an IMU and a depth sensor for feedback. However, these instruments are subjected to large drift, leading to unbounded uncertainty in location. Moreover, the spatio-temporal dynamics of the ocean environment, coupled with limited communication capabilities, make navigation and localization difficult, especially in coastal regions where the majority of interesting phenomena occur. To add to this, the interesting features are themselves spatio-temporally dynamic, and effective sampling requires a good understanding of vehicle localization relative to the sampled feature. Therefore, our work is motivated by the desire to enable intelligent data collection of complex dynamics and processes that occur in coastal ocean environments to further our understanding and prediction capabilities. The study originated from the need to localize and navigate aquatic robots in a GPS-denied environment and examine the role of the spatio-temporal dynamics of the ocean into the localization and navigation processes. The methods and techniques needed range from the data collection to the localization and navigation algorithms used on-board of the aquatic vehicles. The focus of this work is to develop algorithms for localization and navigation of AUVs in GPS-denied environments. We developed an Augmented terrain-based framework that incorporates physical science data, i.e., temperature, salinity, pH, etc., to enhance the topographic map that the vehicle uses to navigate. In this navigation scheme, the bathymetric data are combined with the physical science data to enrich the uniqueness of the underlying terrain map and increase the accuracy of underwater localization. Another technique developed in this work addresses the problem of tracking an underwater vehicle when the GPS signal suddenly becomes unavailable. The methods include the whitening of the data to reveal the true statistical distance between datapoints and also incorporates physical science data to enhance the topographic map. Simulations were performed at Lake Nighthorse, Colorado, USA, between April 25th and May 2nd 2018 and at Big Fisherman\u27s Cove, Santa Catalina Island, California, USA, on July 13th and July 14th 2016. Different missions were executed on different environments (snow, rain and the presence of plumes). Results showed that these two methodologies for localization and tracking work for reference maps that had been recorded within a week and the accuracy on the average error in localization can be compared to the errors found when using GPS if the time in which the observations were taken are the same period of the day (morning, afternoon or night). The whitening of the data had positive results when compared to localizing without whitening

Optimal path shape for range-only underwater target localization using a Wave Glider

Underwater localization using acoustic signals is one of the main components in a navigation system for an autonomous underwater vehicle (AUV) as a more accurate alternative to dead-reckoning techniques. Although different methods based on the idea of multiple beacons have been studied, other approaches use only one beacon, which reduces the system’s costs and deployment complexity. The inverse approach for single-beacon navigation is to use this method for target localization by an underwater or surface vehicle. In this paper, a method of range-only target localization using a Wave Glider is presented, for which simulations and sea tests have been conducted to determine optimal parameters to minimize acoustic energy use and search time, and to maximize location accuracy and precision. Finally, a field mission is presented, where a Benthic Rover (an autonomous seafloor vehicle) is localized and tracked using minimal human intervention. This mission shows, as an example, the power of using autonomous vehicles in collaboration for oceanographic research.Peer ReviewedPostprint (author's final draft

BathyBoat: An Autonomous Surface Vessel for Stand-alone Survey and Underwater Vehicle Network Supervision

Exploration of remote environments, once the domain of intrepid adventurers, can now be conducted in relative safety using unmanned vehicles. This article describes the joint University of Michigan (UMich) and Michigan Tech Research Institute’s project to design and to build a new autonomous surface vessel (ASV) for use in research, education, and resource management as well as in the commercial sector. Originally designed to assist with bathymetric surveys in the wilderness of northern Alaska, the BathyBoat has become a test-bed platform for new research in collaborative heterogeneous underwater robotic search and survey missions in ports, harbors, lakes, and rivers. The UMich Marine Hydrodynamics Laboratories are actively researching autonomous technologies such as cooperative navigation, surface vessel control, and multivehicle search and survey using the BathyBoat and the UMich Perceptual Robotics Laboratory’s Iver2 autonomous underwater vehicles. This article presents an overview of these research topics and highlights relevant real-world testing and recent missions involving the BathyBoat ASV on Alaska’s North Slope, the harbors of Illinois, and various riverine environments in Michigan.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/83223/1/2010e_MTS_Journal.pd

BathyBoat: Autonomous surface command and control for underwater vehicle networks

This paper reports the preparation of two modified Ocean-Server AUV systems and the construction of a new autonomous surface vessel (ASV) for cooperative simultaneous localization and mapping (SLAM) research at the University of Michigan (UMich). The Marine Hydrodynamics Laboratories (MHL) has designed and fabricated the new ASV BathyBoat to serve as a targeted remote sensing platform and a mobile command and control center for underwater search and survey activities performed by UMich Perceptual Robotics Laboratory (PeRL) AUVs. The ASV is outfitted with a suite of sensors including a RadarSonics 250 acoustic depth sensor, Garmin WAAS-enabled GPS, Honeywell HMR3300 digital compass and accelerometer, Vernier CON-BTA conductivity probe, a WHOI Micro-Modem for two-way communication with the AUVs, and other sensors discussed subsequently. Wireless data transmission from the surface offers the ability to monitor, in real-time, the state of the AUVs. In addition, updated mission objectives can be relayed, from ship or shore, through the ASV for mid- mission adjustments. Ongoing scientific and engineering research objectives are discussed, along with an overview of the new autonomous surface vessel and a summary of field trials on the North Slope of Alaska.NSF #IIS 0746455ONR #N00014-07-1-0791Michigan Tech Research Institutehttp://deepblue.lib.umich.edu/bitstream/2027.42/65070/1/UI2010_Final.pd

TRIDENT: A Framework for Autonomous Underwater Intervention

TRIDENT is a STREP project recently approved by the European Commission whose proposal was submitted to the ICT call 4 of the 7th Framework Program. The project proposes a new methodology for multipurpose underwater intervention tasks. To that end, a cooperative team formed with an Autonomous Surface Craft and an Intervention Autonomous Underwater Vehicle will be used. The proposed methodology splits the mission in two stages mainly devoted to survey and intervention tasks, respectively. The project brings together research skills specific to the marine environments in navigation and mapping for underwater robotics, multi-sensory perception, intelligent control architectures, vehiclemanipulator systems and dexterous manipulation. TRIDENT is a three years project and its start is planned by first months of 2010.This work is partially supported by the European Commission through FP7-ICT2009-248497 projec

Experiments on Surface Reconstruction for Partially Submerged Marine Structures

Over the past 10 years, significant scientific effort has been dedicated to the problem of three-dimensional (3-D) surface reconstruction for structural systems. However, the critical area of marine structures remains insufficiently studied. The research presented here focuses on the problem of 3-D surface reconstruction in the marine environment. This paper summarizes our hardware, software, and experimental contributions on surface reconstruction over the past few years (2008–2011). We propose the use of off-the-shelf sensors and a robotic platform to scan marine structures both above and below the waterline, and we develop a method and software system that uses the Ball Pivoting Algorithm (BPA) and the Poisson reconstruction algorithm to reconstruct 3-D surface models of marine structures from the scanned data. We have tested our hardware and software systems extensively in Singapore waters, including operating in rough waters, where water currents are around 1–2 m/s. We present results on construction of various 3-D models of marine structures, including slowly moving structures such as floating platforms, moving boats, and stationary jetties. Furthermore, the proposed surface reconstruction algorithm makes no use of any navigation sensor such as GPS, a Doppler velocity log, or an inertial navigation system.Singapore-MIT Alliance for Research and Technology. Center for Environmental Sensing and Modelin

An Overview of Autonomous Underwater Vehicle Research and Testbed at PeRL

This article provides a general overview of the autonomous underwater vehicle (AUV) research thrusts being pursued within the Perceptual Robotics Laboratory (PeRL) at the University of Michigan. Founded in 2007, PeRL’s research centers on improving AUV autonomy via algorithmic advancements in environmentally-based perceptual feedback for real-time mapping, navigation, and control. Our three major research areas are: (1) real-time visual simultaneous localization and mapping (SLAM); (2) cooperative multi-vehicle navigation; and (3) perception-driven control. Pursuant to these research objectives PeRL has developed a new multi-AUV SLAM testbed based upon a modified Ocean-Server Iver2 AUV platform. PeRL upgraded the vehicles with additional navigation and perceptual sensors for underwater SLAM research. In this article we detail our testbed development, provide an overview of our major research thrusts, and put into context how our modified AUV testbed enables experimental real-world validation of these algorithms.This work is supported in part through grants from the National Science Foundation (Award #IIS 0746455), the Office of Naval Research (Award #N00014-07-1-0791), and a NOAA Ocean Exploration grant (Award #WC133C08SE4089).Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/64455/1/hbrown-2009a.pd