1
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Zhao L, Dai HY, Lang L, Zhang M. An Adaptive Filtering Method for Cooperative Localization in Leader–Follower AUVs. SENSORS 2022; 22:s22135016. [PMID: 35808511 PMCID: PMC9269801 DOI: 10.3390/s22135016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 06/19/2022] [Accepted: 06/23/2022] [Indexed: 02/04/2023]
Abstract
In the complex and variable marine environment, the navigation and localization of autonomous underwater vehicles (AUVs) are very important and challenging. When the conventional Kalman filter (KF) is applied to the cooperative localization of leader–follower AUVs, the outliers in the sensor observations will have a substantial adverse effect on the localization accuracy of the AUVs. Meanwhile, inaccurate noise covariance matrices may result in significant estimation errors. In this paper, we proposed an improved Sage–Husa adaptive extended Kalman filter (improved SHAEKF) for the cooperative localization of multi-AUVs. Firstly, the measurement anomalies were evaluated by calculating the Chi-square test statistics based on the innovation. The detection threshold was determined according to the confidence level of the Chi-square test, and the Chi-square test statistics exceeding the threshold were regarded as measurement abnormalities. When measurement anomalies occurred, the Sage–Husa adaptive extended Kalman filter algorithm was improved by suboptimal maximum a posterior estimation using weighted exponential fading memory, and the measurement noise covariance matrix was adjusted online. The numerical simulation of leader–follower multi-AUV cooperative localization verified the effectiveness of the improved SHAEKF and demonstrated that the average root mean square and the average standard deviation of the localization errors based on the improved SHAEKF were significantly reduced in the case of the presence of measurement abnormalities.
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Affiliation(s)
- Lin Zhao
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China; (L.Z.); (L.L.)
| | - Hong-Yi Dai
- College of Science, National University of Defense Technology, Changsha 410073, China;
| | - Lin Lang
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China; (L.Z.); (L.L.)
| | - Ming Zhang
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China; (L.Z.); (L.L.)
- Correspondence:
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2
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A Distance Increment Smoothing Method and Its Application on the Detection of NLOS in the Cooperative Positioning. SENSORS 2021; 21:s21238028. [PMID: 34884032 PMCID: PMC8659529 DOI: 10.3390/s21238028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 11/17/2021] [Accepted: 11/27/2021] [Indexed: 11/17/2022]
Abstract
The wide use of cooperative missions using multiple unmanned platforms has made relative distance information an essential factor for cooperative positioning and formation control. Reducing the range error effectively in real time has become the main technical challenge. We present a new method to deal with ranging errors based on the distance increment (DI). The DI calculated by dead reckoning is used to smooth the DI obtained by the cooperative positioning, and the smoothed DI is then used to detect and estimate the non-line-of-sight (NLOS) error as well as to smooth the observed values containing random noise in the filtering process. Simulation and experimental results show that the relative accuracy of NLOS estimation is 8.17%, with the maximum random error reduced by 40.27%. The algorithm weakens the influence of NLOS and random errors on the measurement distance, thus improving the relative distance precision and enhancing the stability and reliability of cooperative positioning.
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3
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A Scalable Framework for Map Matching Based Cooperative Localization. SENSORS 2021; 21:s21196400. [PMID: 34640720 PMCID: PMC8512796 DOI: 10.3390/s21196400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 09/21/2021] [Accepted: 09/22/2021] [Indexed: 11/17/2022]
Abstract
Localization based on scalar field map matching (e.g., using gravity anomaly, magnetic anomaly, topographics, or olfaction maps) is a potential solution for navigating in Global Navigation Satellite System (GNSS)-denied environments. In this paper, a scalable framework is presented for cooperatively localizing a group of agents based on map matching given a prior map modeling the scalar field. In order to satisfy the communication constraints, each agent in the group is assigned to different subgroups. A locally centralized cooperative localization method is performed in each subgroup to estimate the poses and covariances of all agents inside the subgroup. Each agent in the group, at the same time, could belong to multiple subgroups, which means multiple pose and covariance estimates from different subgroups exist for each agent. The improved pose estimate for each agent at each time step is then solved through an information fusion algorithm. The proposed algorithm is evaluated with two different types of scalar field based simulations. The simulation results show that the proposed algorithm is able to deal with large group sizes (e.g., 128 agents), achieve 10-m level localization performance with 180 km traveling distance, while under restrictive communication constraints.
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4
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Zhao W, Zhao H, Zou D, Liu L. A Novel Factor Graph and Cubature Kalman Filter Integrated Algorithm for Single-Transponder-Aided Cooperative Localization. ENTROPY 2021; 23:e23101244. [PMID: 34681968 PMCID: PMC8534709 DOI: 10.3390/e23101244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 09/19/2021] [Accepted: 09/22/2021] [Indexed: 11/28/2022]
Abstract
Cooperative localization (CL) of underwater multi-AUVs is vital for numerous underwater operations. Single-transponder-aided cooperative localization (STCL) is regarded as a promising scheme for multi-AUVs CL, benefiting from the fact that an accurate reference is adopted. To improve the positioning accuracy and robustness of STCL, a novel Factor Graph and Cubature Kalman Filter (FGCKF)-integrated algorithm is proposed in this paper. In the proposed FGCKF, historical information can be efficiently used in measurement updating to overcome uncertain observation environments, which greatly helps to improve the performance of filtering progress. Furthermore, Adaptive CKF, sum product, and Maximum Correntropy Criterion (MCC) methods are designed to deal with outliers of acoustic transmission delay, sound velocity, and motion velocity, respectively. Simulations and experiments are conducted, and it is verified that the proposed FGCKF algorithm can improve positioning accuracy and robustness greatly than traditional filtering methods.
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Affiliation(s)
- Wanlong Zhao
- School of Information Science and Engineering, Harbin Institute of Technology, Weihai 264209, China;
| | - Huifeng Zhao
- College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China;
| | - Deyue Zou
- School of Information and Communication Engineering, Dalian University of Technology, Dalian 116081, China
- Correspondence: (D.Z.); (L.L.)
| | - Lu Liu
- College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China;
- Correspondence: (D.Z.); (L.L.)
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5
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Cooperative acoustic navigation of underwater vehicles without a DVL utilizing a dynamic process model: Theory and field evaluation. J FIELD ROBOT 2021. [DOI: 10.1002/rob.22008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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6
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De Palma D, Indiveri G, Parlangeli G. Control Protocols for Range-Based Navigation of a Networked Group of Underwater Vehicles. Front Robot AI 2020; 7:519985. [PMID: 33501301 PMCID: PMC7805725 DOI: 10.3389/frobt.2020.519985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 09/09/2020] [Indexed: 11/13/2022] Open
Abstract
This paper tackles the problem of formation reconstruction for a team of vehicles based on the knowledge of the range between agents of a subset of the participants. One main peculiarity of the proposed approach is that the relative velocity between agents, which is a fundamental data to solve the problem, is not assumed to be known in advance neither directly communicated. For the purpose of estimating this quantity, a collaborative control protocol is designed in order to mount the velocity data in the motion of each vehicle as a parameter through a dedicated control protocol, so that it can be inferred from the motion of the neighbor agents. Moreover, some suitable geometrical constraints related to the agents' relative positions are built and explicitly taken into account in the estimation framework providing a more accurate estimate. The issue of the presence of delays in the transmitted signals is also studied and two possible solutions are provided explaining how it is possible to get a reasonable range data exchange to get the solution both in a centralized fashion and in a decentralized one. Numerical examples are presented corroborating the validity of the proposed approach.
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Affiliation(s)
- Daniela De Palma
- Department of Innovation Engineering (DII), University of Salento (Interuniversity Center of Integrated Systems for the Marine Environment node), Lecce, Italy
| | - Giovanni Indiveri
- Department of Informatics, Bioengineering, Robotics, and Systems Engineering (DIBRIS), University of Genova (Interuniversity Center of Integrated Systems for the Marine Environment node), Genova, Italy
| | - Gianfranco Parlangeli
- Department of Innovation Engineering (DII), University of Salento (Interuniversity Center of Integrated Systems for the Marine Environment node), Lecce, Italy
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7
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Sun J, Hu F, Jin W, Wang J, Wang X, Luo Y, Yu J, Zhang A. Model-Aided Localization and Navigation for Underwater Gliders Using Single-Beacon Travel-Time Differences. SENSORS 2020; 20:s20030893. [PMID: 32046168 PMCID: PMC7039302 DOI: 10.3390/s20030893] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Revised: 02/03/2020] [Accepted: 02/04/2020] [Indexed: 11/19/2022]
Abstract
An accurate motion model and reliable measurements are required for autonomous underwater vehicle localization and navigation in underwater environments. However, without a propeller, underwater gliders have limited maneuverability and carrying capacity, which brings difficulties for modeling and measuring. In this paper, an extended Kalman filter (EKF)-based method, combining a modified kinematic model of underwater gliders with the travel-time differences between signals received from a single beacon, is proposed for estimating the glider positions in a predict-update cycle. First, to accurately establish a motion model for underwater gliders moving in the ocean, we introduce two modification parameters, the attack and drift angles, into a kinematic model of underwater gliders, along with depth-averaged current velocities. The attack and drift angles are calculated based on the coefficients of hydrodynamic forces and the sensor-measured angle variation over time. Then, instead of satisfying synchronization requirements, the travel-time differences between signals received from a single beacon, multiplied by the sound speed, are taken as the measurements. To further reduce the EKF estimation error, the Rauch-Tung-Striebel (RTS) smoothing method is merged into the EKF system. The proposed method is tested in a virtual spatiotemporal environment from an ocean model. The experimental results show that the performance of the RTS-EKF estimate is improved when compared with the motion model estimate, especially by 46% at the inflection point, at least in the particular study developed in this article.
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Affiliation(s)
- Jie Sun
- State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China; (J.S.); (F.H.); (W.J.); (J.W.); (X.W.); (Y.L.); (A.Z.)
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Feng Hu
- State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China; (J.S.); (F.H.); (W.J.); (J.W.); (X.W.); (Y.L.); (A.Z.)
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
| | - Wenming Jin
- State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China; (J.S.); (F.H.); (W.J.); (J.W.); (X.W.); (Y.L.); (A.Z.)
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
| | - Jin Wang
- State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China; (J.S.); (F.H.); (W.J.); (J.W.); (X.W.); (Y.L.); (A.Z.)
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
| | - Xu Wang
- State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China; (J.S.); (F.H.); (W.J.); (J.W.); (X.W.); (Y.L.); (A.Z.)
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
| | - Yeteng Luo
- State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China; (J.S.); (F.H.); (W.J.); (J.W.); (X.W.); (Y.L.); (A.Z.)
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
| | - Jiancheng Yu
- State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China; (J.S.); (F.H.); (W.J.); (J.W.); (X.W.); (Y.L.); (A.Z.)
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
- Correspondence:
| | - Aiqun Zhang
- State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China; (J.S.); (F.H.); (W.J.); (J.W.); (X.W.); (Y.L.); (A.Z.)
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
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8
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An expectation-maximization based single-beacon underwater navigation method with unknown ESV. Neurocomputing 2020. [DOI: 10.1016/j.neucom.2019.10.066] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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9
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A Novel Cooperative Localization Method Based on IMU and UWB. SENSORS 2020; 20:s20020467. [PMID: 31947587 PMCID: PMC7013986 DOI: 10.3390/s20020467] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 12/31/2019] [Accepted: 01/10/2020] [Indexed: 11/16/2022]
Abstract
In this paper, a range-based cooperative localization method is proposed for multiple platforms of various structures. The localization system of an independent platform might degrade or fail due to various reasons such as GPS signal-loss, inertial measurement unit (IMU) accumulative errors, or emergency reboot. It is a promising approach to solve this problem by using information from neighboring platforms, thus forming a cooperative localization network that can improve the navigational robustness of each platform. Typical ranging-based ultra-wideband (UWB) cooperative localization systems require at least three auxiliary nodes to estimate the pose of the target node, which is often hard to meet especially in outdoor environment. In this work, we propose a novel IMU/UWB-based cooperative localization solution, which requires a minimum number of auxiliary nodes that is down to 1. An Adaptive Ant Colony Optimization Particle Filter (AACOPF) algorithm is customized to integrate the dead reckoning (DR) system and auxiliary nodes information with no prior information required, resulting in accurate pose estimation, while to our knowledge the azimuth have not been estimated in cooperative localization for the insufficient observation of the system. We have given the condition when azimuth and localization are solvable by analysis and by experiment. The feasibility of the proposed approach is evaluated through two filed experiments: car-to-trolley and car-to-pedestrian cooperative localization. The comparison results also demonstrate that ACOPF-based integration is better than other filter-based methods such as Extended Kalman Filter (EKF) and traditional Particle Filter (PF).
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10
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Willners JS, Toohey L, Petillot Y. Sampling-Based Path Planning for Cooperative Autonomous Maritime Vehicles to Reduce Uncertainty in Range-Only Localization. IEEE Robot Autom Lett 2019. [DOI: 10.1109/lra.2019.2926947] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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11
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Masmitja I, Gomariz S, Del-Rio J, Kieft B, O’Reilly T, Bouvet PJ, Aguzzi J. Optimal path shape for range-only underwater target localization using a Wave Glider. Int J Rob Res 2018. [DOI: 10.1177/0278364918802351] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
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.
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Affiliation(s)
- Ivan Masmitja
- SARTI Research Group, Electronics Department, Universitat Politecnica de Catalunya,Barcelona, Spain
| | - Spartacus Gomariz
- SARTI Research Group, Electronics Department, Universitat Politecnica de Catalunya,Barcelona, Spain
| | - Joaquin Del-Rio
- SARTI Research Group, Electronics Department, Universitat Politecnica de Catalunya,Barcelona, Spain
| | - Brian Kieft
- Monterey Bay Aquarium Research Institute (MBARI), California, USA
| | - Tom O’Reilly
- Monterey Bay Aquarium Research Institute (MBARI), California, USA
| | | | - Jacopo Aguzzi
- Marine Science Institute (ICM), Consejo superior de Investigaciones Cientificas (CSIC), Barcelona, Spain
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12
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Best G, Martens W, Fitch R. Path Planning With Spatiotemporal Optimal Stopping for Stochastic Mission Monitoring. IEEE T ROBOT 2017. [DOI: 10.1109/tro.2017.2653196] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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13
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Affiliation(s)
- Andrea Munafò
- NATO STO Centre for Maritime Research and Experimentation Research Department Viale San Bartolomeo 400 19126 La Spezia Italy
| | - Gabriele Ferri
- NATO STO Centre for Maritime Research and Experimentation Research Department Viale San Bartolomeo 400 19126 La Spezia Italy
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14
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Javaid N, Ejaz M, Abdul W, Alamri A, Almogren A, Niaz IA, Guizani N. Cooperative Position Aware Mobility Pattern of AUVs for Avoiding Void Zones in Underwater WSNs. SENSORS 2017; 17:s17030580. [PMID: 28335377 PMCID: PMC5375866 DOI: 10.3390/s17030580] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/02/2017] [Revised: 03/02/2017] [Accepted: 03/07/2017] [Indexed: 11/16/2022]
Abstract
In this paper, we propose two schemes; position-aware mobility pattern (PAMP) and cooperative PAMP (Co PAMP). The first one is an optimization scheme that avoids void hole occurrence and minimizes the uncertainty in the position estimation of glider’s. The second one is a cooperative routing scheme that reduces the packet drop ratio by using the relay cooperation. Both techniques use gliders that stay at sojourn positions for a predefined time, at sojourn position self-confidence (s-confidence) and neighbor-confidence (n-confidence) regions that are estimated for balanced energy consumption. The transmission power of a glider is adjusted according to those confidence regions. Simulation results show that our proposed schemes outperform the compared existing one in terms of packet delivery ratio, void zones and energy consumption.
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Affiliation(s)
- Nadeem Javaid
- COMSATS Institute of Information Technology, Islamabad 44000, Pakistan.
| | - Mudassir Ejaz
- COMSATS Institute of Information Technology, Islamabad 44000, Pakistan.
| | - Wadood Abdul
- Research Chair of Pervasive and Mobile Computing, College of Computer and Information Sciences, King Saud University, Riyadh 11633, Saudi Arabia.
| | - Atif Alamri
- Research Chair of Pervasive and Mobile Computing, College of Computer and Information Sciences, King Saud University, Riyadh 11633, Saudi Arabia.
| | - Ahmad Almogren
- Research Chair of Pervasive and Mobile Computing, College of Computer and Information Sciences, King Saud University, Riyadh 11633, Saudi Arabia.
| | | | - Nadra Guizani
- Department of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA.
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15
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Yang J, Dani A, Chung SJ, Hutchinson S. Vision-based Localization and Robot-centric Mapping in Riverine Environments. J FIELD ROBOT 2015. [DOI: 10.1002/rob.21606] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Junho Yang
- Department of Mechanical Science and Engineering; University of Illinois at Urbana-Champaign; Urbana Illinois 61801
| | - Ashwin Dani
- Department of Aerospace Engineering; University of Illinois at Urbana-Champaign; Urbana Illinois 61801
| | - Soon-Jo Chung
- Department of Aerospace Engineering; University of Illinois at Urbana-Champaign; Urbana Illinois 61801
| | - Seth Hutchinson
- Department of Electrical and Computer Engineering; University of Illinois at Urbana-Champaign; Urbana Illinois 61801
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16
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Robust Huber-based iterated divided difference filtering with application to cooperative localization of autonomous underwater vehicles. SENSORS 2014; 14:24523-42. [PMID: 25536004 PMCID: PMC4299124 DOI: 10.3390/s141224523] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/02/2014] [Revised: 11/20/2014] [Accepted: 12/15/2014] [Indexed: 11/17/2022]
Abstract
A new algorithm called Huber-based iterated divided difference filtering (HIDDF) is derived and applied to cooperative localization of autonomous underwater vehicles (AUVs) supported by a single surface leader. The position states are estimated using acoustic range measurements relative to the leader, in which some disadvantages such as weak observability, large initial error and contaminated measurements with outliers are inherent. By integrating both merits of iterated divided difference filtering (IDDF) and Huber's M-estimation methodology, the new filtering method could not only achieve more accurate estimation and faster convergence contrast to standard divided difference filtering (DDF) in conditions of weak observability and large initial error, but also exhibit robustness with respect to outlier measurements, for which the standard IDDF would exhibit severe degradation in estimation accuracy. The correctness as well as validity of the algorithm is demonstrated through experiment results.
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17
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18
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Walls JM, Eustice RM. An origin state method for communication constrained cooperative localization with robustness to packet loss. Int J Rob Res 2014. [DOI: 10.1177/0278364914532390] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
This paper reports on an exact, real-time solution for server–client cooperative localization over a faulty and extremely bandwidth-limited underwater communication channel. Our algorithm, termed the origin state method, enables a ‘server’ vehicle to broadcast its navigation information to multiple ‘client’ vehicles over a bandwidth-limited and faulty communication channel. The server’s broadcasted pose-graph can be used in conjunction with an estimator on the client to exactly reproduce the corresponding server–client centralized estimate. We present an evaluation over an extensive real-time field implementation of the proposed algorithm for a multi-agent autonomous underwater vehicle network using underwater acoustic modems to communicate in a synchronous-clock transmission framework.
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Affiliation(s)
- Jeffrey M. Walls
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Ryan M. Eustice
- Department of Naval Architecture and Marine Engineering, University of Michigan, Ann Arbor, MI, USA
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19
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Abstract
The paper addresses observability issues related to the general problem of single and multiple Autonomous Underwater Vehicle (AUV) localization using only range measurements. While an AUV is submerged, localization devices, such as Global Navigation Satellite Systems, are ineffective, due to the attenuation of electromagnetic waves. AUV localization based on dead reckoning techniques and the use of affordable motion sensor units is also not practical, due to divergence caused by sensor bias and drift. For these reasons, localization systems often build on trilateration algorithms that rely on the measurements of the ranges between an AUV and a set of fixed transponders using acoustic devices. Still, such solutions are often expensive, require cumbersome calibration procedures and only allow for AUV localization in an area that is defined by the geometrical arrangement of the transponders. A viable alternative for AUV localization that has recently come to the fore exploits the use of complementary information on the distance from the AUV to a single transponder, together with information provided by on-board resident motion sensors, such as, for example, depth, velocity and acceleration measurements. This concept can be extended to address the problem of relative localization between two AUVs equipped with acoustic sensors for inter-vehicle range measurements. Motivated by these developments, in this paper, we show that both the problems of absolute localization of a single vehicle and the relative localization of multiple vehicles can be treated using the same mathematical framework, and tailoring concepts of observability derived for nonlinear systems, we analyze how the performance in localization depends on the types of motion imparted to the AUVs. For this effect, we propose a well-defined observability metric and validate its usefulness, both in simulation and by carrying out experimental tests with a real marine vehicle during which the performance of an Extended Kalman Filter state observer is shown to depend on the types of motion imparted to the vehicle.
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20
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Webster SE, Walls JM, Whitcomb LL, Eustice RM. Decentralized Extended Information Filter for Single-Beacon Cooperative Acoustic Navigation: Theory and Experiments. IEEE T ROBOT 2013. [DOI: 10.1109/tro.2013.2252857] [Citation(s) in RCA: 97] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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21
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Wolbrecht E, Anderson M, Canning J, Edwards D, Frenzel J, Odell D, Bean T, Stringfield J, Feusi J, Armstrong B, Folk A, Crosbie B. Field Testing of Moving Short-baseline Navigation for Autonomous Underwater Vehicles using Synchronized Acoustic Messaging. J FIELD ROBOT 2013. [DOI: 10.1002/rob.21460] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
| | | | | | | | - Jim Frenzel
- Dept. of Electrical Eng. University of Idaho
| | - Doug Odell
- Naval Surface Warfare Center Carderock Division; Acoustic Research Detachment
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22
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Webster SE, Eustice RM, Singh H, Whitcomb LL. Advances in single-beacon one-way-travel-time acoustic navigation for underwater vehicles. Int J Rob Res 2012. [DOI: 10.1177/0278364912446166] [Citation(s) in RCA: 134] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
This paper reports the formulation and evaluation of a centralized extended Kalman filter designed for a novel navigation system for underwater vehicles. The navigation system employs Doppler sonar, depth sensors, synchronous clocks, and acoustic modems to achieve simultaneous acoustic communication and navigation. The use of a single moving reference beacon eliminates the requirement for the underwater vehicle to remain in a bounded navigable area; the use of underwater modems and synchronous clocks enables range measurements based on one-way time-of-flight information from acoustic data-packet broadcasts. The acoustic data packets are broadcast from a single, moving reference beacon and can be received simultaneously by multiple vehicles within acoustic range. We report results from a simulated deep-water survey and real field data collected from an autonomous underwater vehicle survey in 4000 m of water on the southern Mid-Atlantic Ridge with an independent long-baseline navigation system for ground truth.
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Affiliation(s)
- Sarah E Webster
- Department of Mechanical Engineering, Johns Hopkins University
- Consortium for Ocean Leadership, Washington D.C
| | - Ryan M Eustice
- Department of Naval Architecture & Marine Engineering, University of Michigan
| | - Hanumant Singh
- Department of Applied Ocean Physics & Engineering, Woods Hole Oceanographic Institution
| | - Louis L Whitcomb
- Department of Mechanical Engineering, Johns Hopkins University
- Department of Applied Ocean Physics & Engineering, Woods Hole Oceanographic Institution
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Kemna S, Hamilton MJ, Hughes DT, LePage KD. Adaptive autonomous underwater vehicles for littoral surveillance. INTEL SERV ROBOT 2011. [DOI: 10.1007/s11370-011-0097-4] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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