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Journal articles on the topic 'Sensors fusion for localisation'

Author: Grafiati

Published: 25 May 2024

Last updated: 31 July 2025

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1

Zheng, ShiYu, and Xiang Jing Yu. "An Overview Study of Multi-sensor Fusion for Map Building and Localization." Advances in Research 26, no. 1 (2025): 247–56. https://doi.org/10.9734/air/2025/v26i11250.

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This paper reviews the application of multi-sensor fusion in simultaneous localisation and map construction (SLAM) technology. With the development of robotics, autonomous driving and virtual reality, there is an increasing demand for precise localisation and map construction.SLAM technology has emerged to solve the problem of autonomous robot localisation and map construction in unknown environments. However, single-sensor SLAM systems have limitations, such as limited sensing capability and susceptibility to noise interference. Multi-sensor fusion SLAM significantly improves the performance

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Ashokaraj, Immanuel, Antonios Tsourdos, Peter Silson, and Brian White. "SENSOR BASED ROBOT LOCALISATION AND NAVIGATION: USING INTERVAL ANALYSIS AND NONLINEAR KALMAN FILTERS." Transactions of the Canadian Society for Mechanical Engineering 29, no. 2 (2005): 211–27. http://dx.doi.org/10.1139/tcsme-2005-0014.

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Multiple sensor fusion for robot localisation and navigation has attracted a lot of interest in recent years. This paper describes a sensor based navigation and localisation approach for an autonomous mobile robot using an interval analysis (IA) based adaptive mechanism for the non-linear Kalman filter namely the Extended Kalman filter (EKF). The map used for this study is two-dimensional and assumed to be known a priori. The robot is equipped with inertial sensors (INS), encoders and ultrasonic sensors. A non-linear Kalman filter is used to estimate the robots position using the inertial sens

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Meng, Lijun, Zhengang Guo, and Chenglong Ma. "Research on multiple damage localisation based on fusion of the Lamb wave ellipse algorithm and RAPID algorithm." Insight - Non-Destructive Testing and Condition Monitoring 66, no. 1 (2024): 34–40. http://dx.doi.org/10.1784/insi.2024.66.1.34.

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Current damage localisation methods often require many sensors and complex signal processing methods. This paper proposes a fusion algorithm based on elliptical localisation and the reconstruction algorithm for probabilistic inspection of damage (RAPID) to locate and image multiple damages. Experimental verification of the damage algorithm was conducted. An ultrasonic probe was used to excite Lamb signals on an aluminium alloy plate, the ultrasonic response signals at different positions within the plate under multiple damages were measured and the constructed algorithm was employed to image t

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Nikitenko, Agris, Aleksis Liekna, Martins Ekmanis, Guntis Kulikovskis, and Ilze Andersone. "Single Robot Localisation Approach for Indoor Robotic Systems through Integration of Odometry and Artificial Landmarks." Applied Computer Systems 14, no. 1 (2013): 50–58. http://dx.doi.org/10.2478/acss-2013-0006.

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Abstract we present an integrated approach for robot localization that allows to integrate for the artificial landmark localization data with odometric sensors and signal transfer function data to provide means for different practical application scenarios. The sensor data fusion deals with asynchronous sensor data using inverse Laplace transform. We demonstrate a simulation software system that ensures smooth integration of the odometry-based and signal transfer - based localization into one approach.

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Tibebu, Haileleol, Varuna De-Silva, Corentin Artaud, Rafael Pina, and Xiyu Shi. "Towards Interpretable Camera and LiDAR Data Fusion for Autonomous Ground Vehicles Localisation." Sensors 22, no. 20 (2022): 8021. http://dx.doi.org/10.3390/s22208021.

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Recent deep learning frameworks draw strong research interest in application of ego-motion estimation as they demonstrate a superior result compared to geometric approaches. However, due to the lack of multimodal datasets, most of these studies primarily focused on single-sensor-based estimation. To overcome this challenge, we collect a unique multimodal dataset named LboroAV2 using multiple sensors, including camera, light detecting and ranging (LiDAR), ultrasound, e-compass and rotary encoder. We also propose an end-to-end deep learning architecture for fusion of RGB images and LiDAR laser s

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Donati, Cesare, Martina Mammarella, Lorenzo Comba, Alessandro Biglia, Paolo Gay, and Fabrizio Dabbene. "3D Distance Filter for the Autonomous Navigation of UAVs in Agricultural Scenarios." Remote Sensing 14, no. 6 (2022): 1374. http://dx.doi.org/10.3390/rs14061374.

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In precision agriculture, remote sensing is an essential phase in assessing crop status and variability when considering both the spatial and the temporal dimensions. To this aim, the use of unmanned aerial vehicles (UAVs) is growing in popularity, allowing for the autonomous performance of a variety of in-field tasks which are not limited to scouting or monitoring. To enable autonomous navigation, however, a crucial capability lies in accurately locating the vehicle within the surrounding environment. This task becomes challenging in agricultural scenarios where the crops and/or the adopted t

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Moretti, Michele, Federico Bianchi, and Nicola Senin. "Towards the development of a smart fused filament fabrication system using multi-sensor data fusion for in-process monitoring." Rapid Prototyping Journal 26, no. 7 (2020): 1249–61. http://dx.doi.org/10.1108/rpj-06-2019-0167.

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Purpose This paper aims to illustrate the integration of multiple heterogeneous sensors into a fused filament fabrication (FFF) system and the implementation of multi-sensor data fusion technologies to support the development of a “smart” machine capable of monitoring the manufacturing process and part quality as it is being built. Design/methodology/approach Starting from off-the-shelf FFF components, the paper discusses the issues related to how the machine architecture and the FFF process itself must be redesigned to accommodate heterogeneous sensors and how data from such sensors can be in

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Kozłowski, Michał, Raúl Santos-Rodríguez, and Robert Piechocki. "Sensor Modalities and Fusion for Robust Indoor Localisation." ICST Transactions on Ambient Systems 6, no. 18 (2019): 162670. http://dx.doi.org/10.4108/eai.12-12-2019.162670.

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Merfels, Christian, and Cyrill Stachniss. "Sensor Fusion for Self-Localisation of Automated Vehicles." PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science 85, no. 2 (2017): 113–26. http://dx.doi.org/10.1007/s41064-017-0008-1.

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Ciuffreda, Ilaria, Sara Casaccia, and Gian Marco Revel. "A Multi-Sensor Fusion Approach Based on PIR and Ultrasonic Sensors Installed on a Robot to Localise People in Indoor Environments." Sensors 23, no. 15 (2023): 6963. http://dx.doi.org/10.3390/s23156963.

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This work illustrates an innovative localisation sensor network that uses multiple PIR and ultrasonic sensors installed on a mobile social robot to localise occupants in indoor environments. The system presented aims to measure movement direction and distance to reconstruct the movement of a person in an indoor environment by using sensor activation strategies and data processing techniques. The data collected are then analysed using both a supervised (Decision Tree) and an unsupervised (K-Means) machine learning algorithm to extract the direction and distance of occupant movement from the mea

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Neuland, Renata, Mathias Mantelli, Bernardo Hummes, et al. "Robust Hybrid Interval-Probabilistic Approach for the Kidnapped Robot Problem." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 29, no. 02 (2021): 313–31. http://dx.doi.org/10.1142/s0218488521500141.

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For a mobile robot to operate in its environment it is crucial to determine its position with respect to an external reference frame using noisy sensor readings. A scenario in which the robot is moved to another position during its operation without being told, known as the kidnapped robot problem, complicates global localisation. In addition to that, sensor malfunction and external influences of the environment can cause unexpected errors, called outliers, that negatively affect the localisation process. This paper proposes a method based on the fusion of a particle filter with bounded-error

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Suhr, J. K., and H. G. Jung. "Sensor fusion‐based precise obstacle localisation for automatic parking systems." Electronics Letters 54, no. 7 (2018): 445–47. http://dx.doi.org/10.1049/el.2018.0196.

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Uney, Murat, Bernard Mulgrew, and Daniel E. Clark. "A Cooperative Approach to Sensor Localisation in Distributed Fusion Networks." IEEE Transactions on Signal Processing 64, no. 5 (2016): 1187–99. http://dx.doi.org/10.1109/tsp.2015.2493981.

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Kalisperakis, I., T. Mandilaras, A. El Saer, et al. "A MODULAR MOBILE MAPPING PLATFORM FOR COMPLEX INDOOR AND OUTDOOR ENVIRONMENTS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B1-2020 (August 6, 2020): 243–50. http://dx.doi.org/10.5194/isprs-archives-xliii-b1-2020-243-2020.

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Abstract. In this work we present the development of a prototype, mobile mapping platform with modular design and architecture that can be suitably modified to address effectively both outdoors and indoors environments. Our system is built on the Robotics Operation System (ROS) and utilizes multiple sensors to capture images, pointclouds and 3D motion trajectories. These include synchronized cameras with wide angle lenses, a lidar sensor, a GPS/IMU unit and a tracking optical sensor. We report on the individual components of the platform, it’s architecture, the integration and the calibration

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Wu, Xinzhao, Peiqing Li, Qipeng Li, and Zhuoran Li. "Two-dimensional-simultaneous Localisation and Mapping Study Based on Factor Graph Elimination Optimisation." Sustainability 15, no. 2 (2023): 1172. http://dx.doi.org/10.3390/su15021172.

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A robust multi-sensor fusion simultaneous localization and mapping (SLAM) algorithm for complex road surfaces is proposed to improve recognition accuracy and reduce system memory occupation, aiming to enhance the computational efficiency of light detection and ranging in complex environments. First, a weighted signed distance function (W-SDF) map-based SLAM method is proposed. It uses a W-SDF map to capture the environment with less accuracy than the raster size but with high localization accuracy. The Levenberg–Marquardt method is used to solve the scan-matching problem in laser SLAM; it effe

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Sheng, Weihua, and Ravi K. Garimella. "Localisation of multiple mobile subjects using multidimensional scaling and sensor fusion." International Journal of Ad Hoc and Ubiquitous Computing 11, no. 4 (2012): 214. http://dx.doi.org/10.1504/ijahuc.2012.050431.

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Lai, Tin. "A Review on Visual-SLAM: Advancements from Geometric Modelling to Learning-Based Semantic Scene Understanding Using Multi-Modal Sensor Fusion." Sensors 22, no. 19 (2022): 7265. http://dx.doi.org/10.3390/s22197265.

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Simultaneous Localisation and Mapping (SLAM) is one of the fundamental problems in autonomous mobile robots where a robot needs to reconstruct a previously unseen environment while simultaneously localising itself with respect to the map. In particular, Visual-SLAM uses various sensors from the mobile robot for collecting and sensing a representation of the map. Traditionally, geometric model-based techniques were used to tackle the SLAM problem, which tends to be error-prone under challenging environments. Recent advancements in computer vision, such as deep learning techniques, have provided

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Butz, Tobias, Uwe Wurster, Gert F. Trommer, and Matthias Wankerl. "Simulated GPS space segment and sensor fusion for lane-level accurate localisation." ATZelektronik worldwide 7, no. 3 (2012): 10–15. http://dx.doi.org/10.1365/s38314-012-0088-z.

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Zhang, Yong, Liyi Zhang, Jianfeng Han, Yi Yang, and Xinyuan Ma. "Sensor management based on collaborative information fusion algorithm for gas source localisation." International Journal of Sensor Networks 28, no. 4 (2018): 242. http://dx.doi.org/10.1504/ijsnet.2018.096478.

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Ma, Xinyuan, Yi Yang, Jianfeng Han, Liyi Zhang, and Yong Zhang. "Sensor management based on collaborative information fusion algorithm for gas source localisation." International Journal of Sensor Networks 28, no. 4 (2018): 242. http://dx.doi.org/10.1504/ijsnet.2018.10017833.

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Liu, Chongxiao, and Bao Kha Nguyen. "Low-Cost Real-Time Localisation for Agricultural Robots in Unstructured Farm Environments." Machines 12, no. 9 (2024): 612. http://dx.doi.org/10.3390/machines12090612.

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Agricultural robots have demonstrated significant potential in enhancing farm operational efficiency and reducing manual labour. However, unstructured and complex farm environments present challenges to the precise localisation and navigation of robots in real time. Furthermore, the high costs of navigation systems in agricultural robots hinder their widespread adoption in cost-sensitive agricultural sectors. This study compared two localisation methods that use the Error State Kalman Filter (ESKF) to integrate data from wheel odometry, a low-cost inertial measurement unit (IMU), a low-cost re

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Akumalla, Ravi Kiran, and Tushar Jain. "Online Tuning of Koopman Operator for Fault-Tolerant Control: A Case Study of Mobile Robot Localising on Minimal Sensor Information." Machines 13, no. 6 (2025): 454. https://doi.org/10.3390/machines13060454.

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Self-localisation is a critical concept in the context of autonomous navigation and control of mobile robots. The most prevalent method for localisation is sensor fusion. Nevertheless, there are certain situations where the robots are compelled to localise on minimal sensor information. Furthermore, the key challenge is determining how to localise if this minimal sensor information fails. This paper proposes a data-driven analytical redundancy technique to address this challenge in wheeled mobile robots. Initially, the localisation of the robot is performed using the encoder information alone

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Liu, Ang, Shiwei Lin, Jianguo Wang, and Xiaoying Kong. "A Novel Loosely Coupling Fusion Approach of Ultra-Wideband and Wheel Odometry for Indoor Localisation." Electronics 12, no. 21 (2023): 4499. http://dx.doi.org/10.3390/electronics12214499.

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Ultra-wideband (UWB) systems promise centimetre-level accuracy for indoor positioning, yet they remain susceptible to non-line-of-sight (NLOS) errors due to complex indoor environments. A fusion mechanism that integrates the UWB with an odometer sensor is introduced to address this challenge and achieve a high positioning accuracy. A sliding window method is applied to identify NLOS anchors effectively. The modified UWB-only positioning has an average error under 13 cm with an RMSE of 16 cm. Then, a loosely coupled approach named Dynamic Dimension Fusion (DDF) is designed to mitigate the odome

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Ochoa-de-Eribe-Landaberea, Aitor, Leticia Zamora-Cadenas, Oier Peñagaricano-Muñoa, and Igone Velez. "UWB and IMU-Based UAV’s Assistance System for Autonomous Landing on a Platform." Sensors 22, no. 6 (2022): 2347. http://dx.doi.org/10.3390/s22062347.

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This work presents a novel landing assistance system (LAS) capable of locating a drone for a safe landing after its inspection mission. The location of the drone is achieved by a fusion of ultra-wideband (UWB), inertial measurement unit (IMU) and magnetometer data. Unlike other typical landing assistance systems, the UWB fixed sensors are placed around a 2 × 2 m landing platform and two tags are attached to the drone. Since this type of set-up is suboptimal for UWB location systems, a new positioning algorithm is proposed for a correct performance. First, an extended Kalman filter (EKF) algori

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Shamsfakhr, Farhad, Andrea Motroni, Luigi Palopoli, Alice Buffi, Paolo Nepa, and Daniele Fontanelli. "Robot Localisation Using UHF-RFID Tags: A Kalman Smoother Approach †." Sensors 21, no. 3 (2021): 717. http://dx.doi.org/10.3390/s21030717.

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Autonomous vehicles enable the development of smart warehouses and smart factories with an increased visibility, flexibility and efficiency. Thus, effective and affordable localisation methods for indoor vehicles are attracting interest to implement real-time applications. This paper presents an Extended Kalman Smoother design to both localise a mobile agent and reconstruct its entire trajectory through a sensor-fusion employing the UHF-RFID passive technology. Extensive simulations are carried out by considering the smoother optimal-window length and the effect of missing measurements from re

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Yuan, Chuanqian, Ye Wang, and Jun Liu. "Research on multi-sensor fusion-based AGV positioning and navigation technology in storage environment." Journal of Physics: Conference Series 2378, no. 1 (2022): 012052. http://dx.doi.org/10.1088/1742-6596/2378/1/012052.

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Abstract Aiming at the problems of low positioning accuracy and large trajectory deviation when AGVs work in dynamic storage environments, an AGV positioning and navigation method based on multi-sensor data fusion is studied. The method is based on traceless Kalman filter (UKF) and adaptive Monte Carlo localisation (AMCL) algorithms to fuse three kinds of sensor data, namely LiDAR, inertial guidance system and ultra-wideband positioning system, to finally output the accurate attitude of the AGV [1]. Remoting data communication between the AGV and the host computer through TCP protocol, and the

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Bosse, Stefan, Dennis Weiss, and Daniel Schmidt. "Supervised Distributed Multi-Instance and Unsupervised Single-Instance Autoencoder Machine Learning for Damage Diagnostics with High-Dimensional Data—A Hybrid Approach and Comparison Study." Computers 10, no. 3 (2021): 34. http://dx.doi.org/10.3390/computers10030034.

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Structural health monitoring (SHM) is a promising technique for in-service inspection of technical structures in a broad field of applications in order to reduce maintenance efforts as well as the overall structural weight. SHM is basically an inverse problem deriving physical properties such as damages or material inhomogeneity (target features) from sensor data. Often models defining the relationship between predictable features and sensors are required but not available. The main objective of this work is the investigation of model-free distributed machine learning (DML) for damage diagnost

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Tholen, Christoph, Iain Parnum, Robin Rofallski, Lars Nolle, and Oliver Zielinski. "Investigation of the Spatio-Temporal Behaviour of Submarine Groundwater Discharge Using a Low-Cost Multi-Sensor-Platform." Journal of Marine Science and Engineering 9, no. 8 (2021): 802. http://dx.doi.org/10.3390/jmse9080802.

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Submarine groundwater discharge (SGD) is an important pathway of nutrients into coastal areas. During the last decades, interest of researchers in SGDs has grown continuously. However, methods applied for SGD research usually focus on the aquifer or on the mixing processes on larger scales. The distribution of discharged water within the water column is not well investigated. Small remotely operated vehicles (ROV) equipped with environmental sensors can be used to investigate the spatial distribution of environmental parameters in the water column. Herein, a low-cost multi-sensor platform desi

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Adámek, Roman, Martin Brablc, Patrik Vávra, Barnabás Dobossy, Martin Formánek, and Filip Radil. "Analytical Models for Pose Estimate Variance of Planar Fiducial Markers for Mobile Robot Localisation." Sensors 23, no. 12 (2023): 5746. http://dx.doi.org/10.3390/s23125746.

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Planar fiducial markers are commonly used to estimate a pose of a camera relative to the marker. This information can be combined with other sensor data to provide a global or local position estimate of the system in the environment using a state estimator such as the Kalman filter. To achieve accurate estimates, the observation noise covariance matrix must be properly configured to reflect the sensor output’s characteristics. However, the observation noise of the pose obtained from planar fiducial markers varies across the measurement range and this fact needs to be taken into account during

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García Daza, Iván, Mónica Rentero, Carlota Salinas Maldonado, et al. "Fail-Aware LIDAR-Based Odometry for Autonomous Vehicles." Sensors 20, no. 15 (2020): 4097. http://dx.doi.org/10.3390/s20154097.

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Autonomous driving systems are set to become a reality in transport systems and, so, maximum acceptance is being sought among users. Currently, the most advanced architectures require driver intervention when functional system failures or critical sensor operations take place, presenting problems related to driver state, distractions, fatigue, and other factors that prevent safe control. Therefore, this work presents a redundant, accurate, robust, and scalable LiDAR odometry system with fail-aware system features that can allow other systems to perform a safe stop manoeuvre without driver medi

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Dinh, To Xuan, Nguyen Thi Thu Huong, Nguyen Ngoc Tuan, and Nguyen Thanh Tien. "Motion planning and control of an autonomous mobile robot." Ministry of Science and Technology, Vietnam 65, no. 4 (2023): 3–10. http://dx.doi.org/10.31276/vjste.65(4).03-10.

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The application of autonomous mobile robots (AMRs) has gradually become crucial in smart factories due to the advantages of improving production efficiency and reducing labour costs. Motion planning has been a key part of AMR control development. This paper presents motion planning and position tracking control systems of an omnidirectional wheel AMR powered by a hybrid fuel cell and battery power source. First, the kinematical and dynamic models of the AMR are introduced. The navigation system comprises three loops, with the first loop being motor control, the second loop being position track

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Bassiri, Amin, Mohammadreza Asghari Oskoei, and Anahid Basiri. "Particle Filter and Finite Impulse Response Filter Fusion and Hector SLAM to Improve the Performance of Robot Positioning." Journal of Robotics 2018 (November 11, 2018): 1–9. http://dx.doi.org/10.1155/2018/7806854.

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Indoor position estimation is essential for navigation; however, it is a challenging task mainly due to the indoor environments’ (a) high noise to signal ratio and (b) low sampling rate and (c) sudden changes to the environments. This paper uses a hybrid filter algorithm for the indoor positioning system for robot navigation integrating Particle Filter (PF) algorithm and Finite Impulse Response (FIR) filter algorithm to assure the continuity of the positioning solution. Additionally, the Hector Simultaneous Localisation and Mapping (Hector SLAM) algorithm is used to map the environment and imp

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George, Anand, Niko Koivumäki, Teemu Hakala, Juha Suomalainen, and Eija Honkavaara. "Visual-Inertial Odometry Using High Flying Altitude Drone Datasets." Drones 7, no. 1 (2023): 36. http://dx.doi.org/10.3390/drones7010036.

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Positioning of unoccupied aerial systems (UAS, drones) is predominantly based on Global Navigation Satellite Systems (GNSS). Due to potential signal disruptions, redundant positioning systems are needed for reliable operation. The objective of this study was to implement and assess a redundant positioning system for high flying altitude drone operation based on visual-inertial odometry (VIO). A new sensor suite with stereo cameras and an inertial measurement unit (IMU) was developed, and a state-of-the-art VIO algorithm, VINS-Fusion, was used for localisation. Empirical testing of the system w

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Wei, Zhe, Sen Wang, Kangyelin Chen, and Fang Wang. "ROS-Based Navigation and Obstacle Avoidance: A Study of Architectures, Methods, and Trends." Sensors 25, no. 14 (2025): 4306. https://doi.org/10.3390/s25144306.

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With the widespread adoption of the Robot Operating System (ROS), technologies for autonomous navigation in mobile robots have advanced considerably. ROS provides a modular navigation stack that integrates essential components, such as SLAM, localisation, global path planning, and obstacle avoidance, forming the foundation for applications including service robotics and autonomous driving. Nonetheless, achieving safe and reliable navigation in complex and dynamic environments remains a formidable challenge, due to the need for real-time perception of moving obstacles, sensor fusion requirement

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Schwarz, D., R. H. Rasshofer, and E. M. Biebl. "Optimized tracking for cooperative sensor systems in multipath environments." Advances in Radio Science 6 (May 26, 2008): 71–75. http://dx.doi.org/10.5194/ars-6-71-2008.

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Abstract. In a cooperative sensor system for pedestrian protection, a pedestrian and other road users exchange data by means of radio frequency communication. In the proposed system, the pedestrian carries a transponder which is interrogated by a vehicle and sends an anonymous identification (ID) sequence. By decoding the ID, the interrogation unit in the vehicle detects the presence of the transponder. Evaluating the incident wave of the transponder's answer, a localisation is possible. In the proposed localization system, the measurement results can be distorted by multipath propagation. Mul

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Zhao, Zhongyi, Yongzhi Cui, and Shenyu Wang. "High-Precision Positioning Simulation and Experimental Research of Special Operation Vehicles Based on Network RTK." Computational Intelligence and Neuroscience 2023 (February 2, 2023): 1–15. http://dx.doi.org/10.1155/2023/2911846.

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In terms of driverless systems, high-precision positioning technology is one among the critical aspects of driverless cars to achieve driverlessness. This study analyzed the working principles of GNSS (global navigation satellite system) and SINS (strapdown inertial navigation system) and elaborated the principles of the least square method and LAMBDA algorithm in the integer ambiguity resolution. Based on the network RTK positioning technology and the abovementioned theory, the unmanned automatic work vehicle was used as the research object, and the fusion positioning algorithm of the BDS/GPS

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Wijayathunga, Liyana, Alexander Rassau, and Douglas Chai. "Challengesand Solutions for Autonomous Ground Robot Scene Understanding and Navigation in Unstructured Outdoor Environments: A Review." Applied Sciences 13, no. 17 (2023): 9877. http://dx.doi.org/10.3390/app13179877.

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The capabilities of autonomous mobile robotic systems have been steadily improving due to recent advancements in computer science, engineering, and related disciplines such as cognitive science. In controlled environments, robots have achieved relatively high levels of autonomy. In more unstructured environments, however, the development of fully autonomous mobile robots remains challenging due to the complexity of understanding these environments. Many autonomous mobile robots use classical, learning-based or hybrid approaches for navigation. More recent learning-based methods may replace the

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Thorsager, Mathias, Sune Kroeyer, Adham Taha, et al. "Automated Room-Level Localisation Using Building Plan Information." Sensors 24, no. 17 (2024): 5753. http://dx.doi.org/10.3390/s24175753.

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Building Management Systems (BMSs) are transitioning from utilising wired installations to wireless Internet of Things (IoT) sensors and actuators. This shift introduces the requirement of robust localisation methods which can link the installed sensors to the correct Control Units (CTUs) which will facilitate continued communication. In order to lessen the installation burden on the technicians, the installation process should be made more complicated by the localisation method. We propose an automated version of the fingerprinting-based localisation method which estimates the location of sen

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Hoppenot, Philippe, Etienne Colle, and Christian Barat. "Off-line localisation of a mobile robot using ultrasonic measurements." Robotica 18, no. 3 (2000): 315–23. http://dx.doi.org/10.1017/s0263574799002180.

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Regarding assistance to disabled people for object manipulation and carrying, the paper focuses on the localisation for mobile robot autonomy. In order to respect strong low-cost constraints, the perception system of the mobile robot uses sensors of low metrological quality, ultrasonic ring and odometry. That poses new problems for localisation, in particular. Among different localisation techniques, we present only off-line localisation. With poor perception means, it is necessary to introduce a priori knowledge on sensors and environment models. To solve the localisation problem, the ultraso

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Jurdak, Raja, Branislav Kusy, and Alban Cotillon. "Group-based Motion Detection for Energy-Efficient Localisation." Journal of Sensor and Actuator Networks 1, no. 3 (2012): 183–216. http://dx.doi.org/10.3390/jsan1030183.

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Long-term outdoor localization remains challenging due to the high energy profiles of GPS modules. Duty cycling the GPS module combined with inertial sensors can improve energy consumption. However, inertial sensors that are kept active all the time can also drain mobile node batteries. This paper proposes duty cycling strategies for inertial sensors to maintain a target position accuracy and node lifetime. We present a method for duty cycling motion sensors according to features of movement events, and evaluate its energy and accuracy profile for an empirical data trace of cattle movement. We

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Pan, Lei, Xi Zheng, Philip Kolar, and Shaun Bangay. "Object localisation through clustering unreliable ultrasonic range sensors." International Journal of Sensor Networks 27, no. 4 (2018): 268. http://dx.doi.org/10.1504/ijsnet.2018.093965.

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Zheng, Xi, Philip Kolar, Shaun Bangay, and Lei Pan. "Object localisation through clustering unreliable ultrasonic range sensors." International Journal of Sensor Networks 27, no. 4 (2018): 268. http://dx.doi.org/10.1504/ijsnet.2018.10014898.

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White, P. R., T. G. Leighton, D. C. Finfer, C. Powles, and O. N. Baumann. "Localisation of sperm whales using bottom-mounted sensors." Applied Acoustics 67, no. 11-12 (2006): 1074–90. http://dx.doi.org/10.1016/j.apacoust.2006.05.002.

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Narita, Masaki, Keisuke Kamada, Kanayo Ogura, Bhed Bahadur Bista, and Toyoo Takata. "Countermeasures against darknet localisation attacks with packet sampling." Indonesian Journal of Electrical Engineering and Computer Science 19, no. 2 (2020): 1036. http://dx.doi.org/10.11591/ijeecs.v19.i2.pp1036-1047.

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<p>The darknet monitoring system consists of network sensors widely deployed on the Internet to capture incoming unsolicited packets. A goal of this system is to analyse captured malicious packets and provide effective information to protect regular nonmalicious Internet users from malicious activities. To provide effective and reliable information, the location of sensors must be concealed. However, attackers launch localisation attacks to detect sensors in order to evade them. If the actual location of sensors is revealed, it is almost impossible to identify the latest tactics used by

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Masaki, Narita, Kamada Keisuke, Ogura Kanayo, Bahadur Bista Bhed, and Takata Toyoo. "Countermeasures against darknet localisation attacks with packet sampling." Indonesian Journal of Electrical Engineering and Computer Science (IJEECS) 19, no. 2 (2020): 1036–47. https://doi.org/10.11591/ijeecs.v19i2.pp1036-1047.

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The darknet monitoring system consists of network sensors widely deployed on the Internet to capture incoming unsolicited packets. A goal of this system is to analyse captured malicious packets and provide effective information to protect regular nonmalicious Internet users from malicious activities. To provide effective and reliable information, the location of sensors must be concealed. However, attackers launch localisation attacks to detect sensors in order to evade them. If the actual location of sensors is revealed, it is almost impossible to identify the latest tactics used by attackers

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Jose, Diniya, and Shoney Sebastian. "Taylor series method in TDOA approach for indoor positioning system." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 5 (2019): 3927. http://dx.doi.org/10.11591/ijece.v9i5.pp3927-3933.

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Localisation technologies have always remained in the limelight of positioning-science as researchers have ever shown keen interest to know the exact positions of things. Ultrasonic sensors are mainly used for localisation of mobile robots since they provide high accuracy. This paper presents Taylor Series Method in Time Difference of Arrival approach using ultrasonic sensors.Signals are send from the sensors periodically.The time difference of arrival of signals from the ultrasonic sensors is used by the receiver unit to estimate the location of the mobile unit. The equations formed by using

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Diniya, Jose, and Sebastian Shoney. "Taylor series method in TDOA approach for indoor positioning system." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 5 (2019): 3927–33. https://doi.org/10.11591/ijece.v9i5.pp3927-3933.

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Abstract:

Localisation technologies have always remained in the limelight of positioning-science as researchers have ever shown keen interest to know the exact positions of things. Ultrasonic sensors are mainly used for localisation of mobile robots since they provide high accuracy. This paper presents Taylor Series Method in Time Difference of Arrival approach using ultrasonic sensors.Signals are send from the sensors periodically. The time difference of arrival of signals from the ultrasonic sensors is used by the receiver unit to estimate the location of the mobile unit. The equations formed by using

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Kudela, Pawel, Wiesław M. Ostachowicz, and Arkadiusz Zak. "Sensor Triangulation for Damage Localisation in Composite Plates." Key Engineering Materials 413-414 (June 2009): 55–62. http://dx.doi.org/10.4028/www.scientific.net/kem.413-414.55.

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The aim of this paper is development of an algorithm for damage localisation in composite plates based on wave propagation signals registered by sensors. It is proposed to distribute the sensors uniformly over the area of a plate-like structure performing triangulation. Next the registered signals are processed and a damage influence map is created in each triangle separately in order to avoid problems connected with reflections from boundaries of the structure. The proposed procedure has been verified on numerical signals as well as experimental signals.

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Sabra, Adham, and Wai-Keung Fung. "A Fuzzy Cooperative Localisation Framework for Underwater Robotic Swarms." Sensors 20, no. 19 (2020): 5496. http://dx.doi.org/10.3390/s20195496.

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This article proposes a holistic localisation framework for underwater robotic swarms to dynamically fuse multiple position estimates of an autonomous underwater vehicle while using fuzzy decision support system. A number of underwater localisation methods have been proposed in the literature for wireless sensor networks. The proposed navigation framework harnesses the established localisation methods in order to provide navigation aids in the absence of acoustic exteroceptive sensors navigation aid (i.e., ultra-short base line) and it can be extended to accommodate newly developed localisatio

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Levy dit Vehel, Victor, Ange Haddjeri, and Osvanny Ramos. "Acoustic localisation in a two-dimensional granular medium." EPJ Web of Conferences 249 (2021): 15005. http://dx.doi.org/10.1051/epjconf/202124915005.

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We focus on localizing the source of acoustic emissions within a compressed two-dimensional granular ensemble of photoelastic disks, having as main information the arrival times of the acoustic signal to 6 sensors located in the boundaries of the system. By estimating, thanks to the photoelasticity of the grains, the wave speed at every point of the structure, we are able to compute the arrival times from every point of the system to the sensors. A comparison between the arrival time differences between every set of computed values to those from the actual measurements allows finding the sourc

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