Relevant bibliographies by topics / Pose graph optimization

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Pose graph optimization'

Author: Grafiati
Published: 4 June 2021
Last updated: 17 February 2022

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Journal articles on the topic "Pose graph optimization"

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Youyang, Feng, Wang Qing, and Yang Gaochao. "Incremental 3-D pose graph optimization for SLAM algorithm without marginalization." International Journal of Advanced Robotic Systems 17, no. 3 (May 1, 2020): 172988142092530. http://dx.doi.org/10.1177/1729881420925304.

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Pose graph optimization algorithm is a classic nonconvex problem which is widely used in simultaneous localization and mapping algorithm. First, we investigate previous contributions and evaluate their performances using KITTI, Technische Universität München (TUM), and New College data sets. In practical scenario, pose graph optimization starts optimizing when loop closure happens. An estimated robot pose meets more than one loop closures; Schur complement is the common method to obtain sequential pose graph results. We put forward a new algorithm without managing complex Bayes factor graph and obtain more accurate pose graph result than state-of-art algorithms. In the proposed method, we transform the problem of estimating absolute poses to the problem of estimating relative poses. We name this incremental pose graph optimization algorithm as G-pose graph optimization algorithm. Another advantage of G-pose graph optimization algorithm is robust to outliers. We add loop closure metric to deal with outlier data. Previous experiments of pose graph optimization algorithm use simulated data, which do not conform to real world, to evaluate performances. We use KITTI, TUM, and New College data sets, which are obtained by real sensor in this study. Experimental results demonstrate that our proposed incremental pose graph algorithm model is stable and accurate in real-world scenario.
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SUZUKI, Taro. "Pose Graph Optimization using Multiple GNSS." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2020 (2020): 2P1—K12. http://dx.doi.org/10.1299/jsmermd.2020.2p1-k12.

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Liu, Tian, Yongfu Chen, Zhiyong Jin, Kai Li, Zhenting Wang, and Jiongzhi Zheng. "Spare Pose Graph Decomposition and Optimization for SLAM." MATEC Web of Conferences 256 (2019): 05003. http://dx.doi.org/10.1051/matecconf/201925605003.

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The graph optimization has become the mainstream technology to solve the problems of SLAM (simultaneous localization and mapping). The pose graph in the graph based SLAM is consisted with a series of nodes and edges that connect the adjacent or related poses. With the widespread use of mobile robots, the scale of pose graph has rapidly increased. Therefore, optimizing a large-scale pose graph is the bottleneck of application of graph based SLAM. In this paper, we propose an optimization method basing on the decomposition of pose graph, of which we have noticed the sparsity. With the extraction of the Single-chain and the Parallel-chain, the pose graph is decomposed into many small subgraphs. Compared with directly processing the original graph, the speed of calculation is accelerated by separately optimizing the subgraph, which is because the computational complexity is increasing exponentially with the increase of the graph’s scale. This method we proposed is very suitable for the current multi-threaded framework adopted in the mainstream SLAM, which separately calculate the subgraph decomposed by our method, rather than the original optimization requiring a large block of time in once may cause CPU obstruction. At the end of the paper, our algorithm is validated with the open source dataset of the mobile robot, of which the result illustrates our algorithm can reduce the one-time resource consumption and the time consumption of the calculation with the same map-constructing accuracy.
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Tian, Yulun, Alec Koppel, Amrit Singh Bedi, and Jonathan P. How. "Asynchronous and Parallel Distributed Pose Graph Optimization." IEEE Robotics and Automation Letters 5, no. 4 (October 2020): 5819–26. http://dx.doi.org/10.1109/lra.2020.3010216.

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Das, Anweshan, Jos Elfring, and Gijs Dubbelman. "Real-Time Vehicle Positioning and Mapping Using Graph Optimization." Sensors 21, no. 8 (April 16, 2021): 2815. http://dx.doi.org/10.3390/s21082815.

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In this work, we propose and evaluate a pose-graph optimization-based real-time multi-sensor fusion framework for vehicle positioning using low-cost automotive-grade sensors. Pose-graphs can model multiple absolute and relative vehicle positioning sensor measurements and can be optimized using nonlinear techniques. We model pose-graphs using measurements from a precise stereo camera-based visual odometry system, a robust odometry system using the in-vehicle velocity and yaw-rate sensor, and an automotive-grade GNSS receiver. Our evaluation is based on a dataset with 180 km of vehicle trajectories recorded in highway, urban, and rural areas, accompanied by postprocessed Real-Time Kinematic GNSS as ground truth. We compare the architecture’s performance with (i) vehicle odometry and GNSS fusion and (ii) stereo visual odometry, vehicle odometry, and GNSS fusion; for offline and real-time optimization strategies. The results exhibit a 20.86% reduction in the localization error’s standard deviation and a significant reduction in outliers when compared with automotive-grade GNSS receivers.
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Li, Jin Liang, Ji Hua Bao, and Yan Yu. "Graph SLAM for Rescue Robots." Applied Mechanics and Materials 433-435 (October 2013): 134–37. http://dx.doi.org/10.4028/www.scientific.net/amm.433-435.134.

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This paper studied the mapping problem for rescue robots. Being able to build a map of the rescue environment and simultaneously localize within this map is an essential skill for rescue robots. We formulate the SLAM problem as a graph whose nodes correspond to the poses of the robot at different points and whose edges represent constraints between poses. Optimizing large pose graphs has been a bottleneck for mobile robots, since the computation time of direct nonlinear optimization can grow rapidly with the size of graph. In this paper, we propose an efficient method for constructing and solving a linear problem. We demonstrate its effectiveness on a large set of real-world maps.
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Carlone, Luca, and Giuseppe C. Calafiore. "Convex Relaxations for Pose Graph Optimization With Outliers." IEEE Robotics and Automation Letters 3, no. 2 (April 2018): 1160–67. http://dx.doi.org/10.1109/lra.2018.2793352.

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Jackson, James, Kevin Brink, Brendon Forsgren, David Wheeler, and Timothy McLain. "Direct Relative Edge Optimization, A Robust Alternative for Pose Graph Optimization." IEEE Robotics and Automation Letters 4, no. 2 (April 2019): 1932–39. http://dx.doi.org/10.1109/lra.2019.2896478.

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Worley, Rob, Ke Ma, Gavin Sailor, Michele M. Schirru, Rob Dwyer-Joyce, Joby Boxall, Tony Dodd, Richard Collins, and Sean Anderson. "Robot Localization in Water Pipes Using Acoustic Signals and Pose Graph Optimization." Sensors 20, no. 19 (September 29, 2020): 5584. http://dx.doi.org/10.3390/s20195584.

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One of the most fundamental tasks for robots inspecting water distribution pipes is localization, which allows for autonomous navigation, for faults to be communicated, and for interventions to be instigated. Pose-graph optimization using spatially varying information is used to enable localization within a feature-sparse length of pipe. We present a novel method for improving estimation of a robot’s trajectory using the measured acoustic field, which is applicable to other measurements such as magnetic field sensing. Experimental results show that the use of acoustic information in pose-graph optimization reduces errors by 39% compared to the use of typical pose-graph optimization using landmark features only. High location accuracy is essential to efficiently and effectively target investment to maximise the use of our aging pipe infrastructure.
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Carlone, Luca, Giuseppe C. Calafiore, Carlo Tommolillo, and Frank Dellaert. "Planar Pose Graph Optimization: Duality, Optimal Solutions, and Verification." IEEE Transactions on Robotics 32, no. 3 (June 2016): 545–65. http://dx.doi.org/10.1109/tro.2016.2544304.

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Dissertations / Theses on the topic "Pose graph optimization"

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Lao, Beyer Lukas C. "Multi-modal motion planning using composite pose graph optimization." Thesis, Massachusetts Institute of Technology, 2021. https://hdl.handle.net/1721.1/130697.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, February, 2021
Cataloged from the official PDF of thesis.
Includes bibliographical references (pages 30-31).
This work presents a motion planning framework for multi-modal vehicle dynamics. An approach for transcribing cost function, vehicle dynamics, and state and control constraints into a sparse factor graph is introduced. By formulating the motion planning problem in pose graph form, the motion planning problem can be addressed using efficient optimization techniques, similar to those already widely applied in dual estimation problems, e.g., pose graph optimization for simultaneous localization and mapping (SLAM). Optimization of trajectories for vehicles under various dynamics models is demonstrated. The motion planner is able to optimize the location of mode transitions, and is guided by the pose graph optimization process to eliminate unnecessary mode transitions, enabling efficient discovery of optimized mode sequences from rough initial guesses. This functionality is demonstrated by using our planner to optimize multi-modal trajectories for vehicles such as an airplane which can both taxi on the ground or fly. Extensive experiments validate the use of the proposed motion planning framework in both simulation and real-life flight experiments using a vertical take-off and landing (VTOL) fixed-wing aircraft that can transition between hover and horizontal flight modes.
by Lukas C. Lao Beyer.
M. Eng.
M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
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Balabanska, Nadya L. "Motion planning with dynamic constraints through pose graph optimization." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/129129.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, September, 2020
Cataloged from student-submitted PDF of thesis.
Includes bibliographical references (pages 20-21).
This contribution is an optimization-based method for robotic path-planning that is able to recover vehicle controls in addition to discovering an optimized, feasible trajectory from start to goal for vehicles with arbitrary dynamics. The motion planner extends the application of factor-graph optimization commonly used in simultaneous localization and mapping tasks to the path-planning task, specifically the "timed elastic band" trajectory optimization approach [1] for control input extraction functionality. This is achieved by the introduction of control input-dependent vertices into the factor-graph along with a way to systematically design dynamics violation costs without relying on hand-picked geometric parameters. An implementation of the planner successfully recovers vehicle control inputs and produces feasible trajectories in simulation testing.
by Nadya L. Balabanska.
M. Eng.
M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
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Harr, Maximilian [Verfasser], and C. [Akademischer Betreuer] Stiller. "Fail-Safe Vehicle Pose Estimation in Lane-Level Maps Using Pose Graph Optimization / Maximilian Harr ; Betreuer: C. Stiller." Karlsruhe : KIT-Bibliothek, 2019. http://d-nb.info/1195049153/34.

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Sünderhauf, Niko. "Robust Optimization for Simultaneous Localization and Mapping." Doctoral thesis, Universitätsbibliothek Chemnitz, 2012. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-86443.

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SLAM (Simultaneous Localization And Mapping) has been a very active and almost ubiquitous problem in the field of mobile and autonomous robotics for over two decades. For many years, filter-based methods have dominated the SLAM literature, but a change of paradigms could be observed recently. Current state of the art solutions of the SLAM problem are based on efficient sparse least squares optimization techniques. However, it is commonly known that least squares methods are by default not robust against outliers. In SLAM, such outliers arise mostly from data association errors like false positive loop closures. Since the optimizers in current SLAM systems are not robust against outliers, they have to rely heavily on certain preprocessing steps to prevent or reject all data association errors. Especially false positive loop closures will lead to catastrophically wrong solutions with current solvers. The problem is commonly accepted in the literature, but no concise solution has been proposed so far. The main focus of this work is to develop a novel formulation of the optimization-based SLAM problem that is robust against such outliers. The developed approach allows the back-end part of the SLAM system to change parts of the topological structure of the problem\'s factor graph representation during the optimization process. The back-end can thereby discard individual constraints and converge towards correct solutions even in the presence of many false positive loop closures. This largely increases the overall robustness of the SLAM system and closes a gap between the sensor-driven front-end and the back-end optimizers. The approach is evaluated on both large scale synthetic and real-world datasets. This work furthermore shows that the developed approach is versatile and can be applied beyond SLAM, in other domains where least squares optimization problems are solved and outliers have to be expected. This is successfully demonstrated in the domain of GPS-based vehicle localization in urban areas where multipath satellite observations often impede high-precision position estimates.
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Jackson, James Scott. "Enabling Autonomous Operation of Micro Aerial Vehicles Through GPS to GPS-Denied Transitions." BYU ScholarsArchive, 2019. https://scholarsarchive.byu.edu/etd/8709.

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Micro aerial vehicles and other autonomous systems have the potential to truly transform life as we know it, however much of the potential of autonomous systems remains unrealized because reliable navigation is still an unsolved problem with significant challenges. This dissertation presents solutions to many aspects of autonomous navigation. First, it presents ROSflight, a software and hardware architure that allows for rapid prototyping and experimentation of autonomy algorithms on MAVs with lightweight, efficient flight control. Next, this dissertation presents improvments to the state-of-the-art in optimal control of quadrotors by utilizing the error-state formulation frequently utilized in state estimation. It is shown that performing optimal control directly over the error-state results in a vastly more computationally efficient system than competing methods while also dealing with the non-vector rotation components of the state in a principled way. In addition, real-time robust flight planning is considered with a method to navigate cluttered, potentially unknown scenarios with real-time obstacle avoidance. Robust state estimation is a critical component to reliable operation, and this dissertation focuses on improving the robustness of visual-inertial state estimation in a filtering framework by extending the state-of-the-art to include better modeling and sensor fusion. Further, this dissertation takes concepts from the visual-inertial estimation community and applies it to tightly-coupled GNSS, visual-inertial state estimation. This method is shown to demonstrate significantly more reliable state estimation than visual-inertial or GNSS-inertial state estimation alone in a hardware experiment through a GNSS-GNSS denied transition flying under a building and back out into open sky. Finally, this dissertation explores a novel method to combine measurements from multiple agents into a coherent map. Traditional approaches to this problem attempt to solve for the position of multiple agents at specific times in their trajectories. This dissertation instead attempts to solve this problem in a relative context, resulting in a much more robust approach that is able to handle much greater intial error than traditional approaches.
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Ellingson, Gary James. "Cooperative Navigation of Fixed-Wing Micro Air Vehicles in GPS-Denied Environments." BYU ScholarsArchive, 2019. https://scholarsarchive.byu.edu/etd/8706.

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Micro air vehicles have recently gained popularity due to their potential as autonomous systems. Their future impact, however, will depend in part on how well they can navigate in GPS-denied and GPS-degraded environments. In response to this need, this dissertation investigates a potential solution for GPS-denied operations called relative navigation. The method utilizes keyframe-to-keyframe odometry estimates and their covariances in a global back end that represents the global state as a pose graph. The back end is able to effectively represent nonlinear uncertainties and incorporate opportunistic global constraints. The GPS-denied research community has, for the most part, neglected to consider fixed-wing aircraft. This dissertation enables fixed-wing aircraft to utilize relative navigation by accounting for their sensing requirements. The development of an odometry-like, front-end, EKF-based estimator that utilizes only a monocular camera and an inertial measurement unit is presented. The filter uses the measurement model of the multi-state-constraint Kalman filter and regularly performs relative resets in coordination with keyframe declarations. In addition to the front-end development, a method is provided to account for front-end velocity bias in the back-end optimization. Finally a method is presented for enabling multiple vehicles to improve navigational accuracy by cooperatively sharing information. Modifications to the relative navigation architecture are presented that enable decentralized, cooperative operations amidst temporary communication dropouts. The proposed framework also includes the ability to incorporate inter-vehicle measurements and utilizes a new concept called the coordinated reset, which is necessary for optimizing the cooperative odometry and improving localization. Each contribution is demonstrated through simulation and/or hardware flight testing. Simulation and Monte-Carlo testing is used to show the expected quality of the results. Hardware flight-test results show the front-end estimator performance, several back-end optimization examples, and cooperative GPS-denied operations.
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Wheeler, David Orton. "Relative Navigation of Micro Air Vehicles in GPS-Degraded Environments." BYU ScholarsArchive, 2017. https://scholarsarchive.byu.edu/etd/6609.

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Most micro air vehicles rely heavily on reliable GPS measurements for proper estimation and control, and therefore struggle in GPS-degraded environments. When GPS is not available, the global position and heading of the vehicle is unobservable. This dissertation establishes the theoretical and practical advantages of a relative navigation framework for MAV navigation in GPS-degraded environments. This dissertation explores how the consistency, accuracy, and stability of current navigation approaches degrade during prolonged GPS dropout and in the presence of heading uncertainty. Relative navigation (RN) is presented as an alternative approach that maintains observability by working with respect to a local coordinate frame. RN is compared with several current estimation approaches in a simulation environment and in hardware experiments. While still subject to global drift, RN is shown to produce consistent state estimates and stable control. Estimating relative states requires unique modifications to current estimation approaches. This dissertation further provides a tutorial exposition of the relative multiplicative extended Kalman filter, presenting how to properly ensure observable state estimation while maintaining consistency. The filter is derived using both inertial and body-fixed state definitions and dynamics. Finally, this dissertation presents a series of prolonged flight tests, demonstrating the effectiveness of the relative navigation approach for autonomous GPS-degraded MAV navigation in varied, unknown environments. The system is shown to utilize a variety of vision sensors, work indoors and outdoors, run in real-time with onboard processing, and not require special tuning for particular sensors or environments. Despite leveraging off-the-shelf sensors and algorithms, the flight tests demonstrate stable front-end performance with low drift. The flight tests also demonstrate the onboard generation of a globally consistent, metric, and localized map by identifying and incorporating loop-closure constraints and intermittent GPS measurements. With this map, mission objectives are shown to be autonomously completed.
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Modrzejewski, Remigiusz. "Distribution et Stockage de Contenus dans les Réseaux." Phd thesis, Université Nice Sophia Antipolis, 2013. http://tel.archives-ouvertes.fr/tel-00917032.

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Dans cette thèse, nous étudions divers problèmes dont l'objectif est de gérer la croissance d'internet plus efficacement. En effet celle-ci est très vive : 41% pour le pic en 2012. Afin de répondre aux défis posés par cette évolution aux divers acteurs du réseau, des protocoles de gestion et de communication plus intelligents sont nécessaires. Les protocoles de l'Internet furent conçus, point à point. Or, la part de la diffusion de média dans le trafic est prépondérante et en hausse tendancielle, et des projections indiquent qu'en 2016 80-90% du trafic sera engendré par de la diffusion vidéo. Cette divergence entraîne des inefficacités car les données parcourent plusieurs fois le réseau. Dans cette thèse, nous étudions comment tempérer cette inefficacité. Nos contributions sont organisées selon les couches et les phases de déploiement du réseau. Nous étudions le placement de caches lors de la conception du réseau. Ensuite, pour la gestion d'un réseau, nous regardons quand placer des appareils en veille, en utilisant un mécanisme de cache et en coopération avec des réseaux de distribution. Puis, au niveau de la couche application, nous étudions un problème de maintenance d'arbres équilibrés pour la diffusion de média. Enfin, nous analysons la probabilité de survie de données dans un système de sauvegarde distribuée. Notre travail se fonde à la fois sur des méthodes théoriques (Chaînes de Markov, Programmation Linéaire), mais aussi sur des outils empiriques tels que la simulation et l'expérimentation.
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Barrera-Cruz, Fidel. "On Schnyder's Theorm." Thesis, 2010. http://hdl.handle.net/10012/5358.

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The central topic of this thesis is Schnyder's Theorem. Schnyder's Theorem provides a characterization of planar graphs in terms of their poset dimension, as follows: a graph G is planar if and only if the dimension of the incidence poset of G is at most three. One of the implications of the theorem is proved by giving an explicit mapping of the vertices to R^2 that defines a straightline embedding of the graph. The other implication is proved by introducing the concept of normal labelling. Normal labellings of plane triangulations can be used to obtain a realizer of the incidence poset. We present an exposition of Schnyder’s theorem with his original proof, using normal labellings. An alternate proof of Schnyder’s Theorem is also presented. This alternate proof does not use normal labellings, instead we use some structural properties of a realizer of the incidence poset to deduce the result. Some applications and a generalization of one implication of Schnyder’s Theorem are also presented in this work. Normal labellings of plane triangulations can be used to obtain a barycentric embedding of a plane triangulation, and they also induce a partition of the edge set of a plane triangulation into edge disjoint trees. These two applications of Schnyder’s Theorem and a third one, relating realizers of the incidence poset and canonical orderings to obtain a compact drawing of a graph, are also presented. A generalization, to abstract simplicial complexes, of one of the implications of Schnyder’s Theorem was proved by Ossona de Mendez. This generalization is also presented in this work. The concept of order labelling is also introduced and we show some similarities of the order labelling and the normal labelling. Finally, we conclude this work by showing the source code of some implementations done in Sage.
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Book chapters on the topic "Pose graph optimization"

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Calafiore, Giuseppe C., Luca Carlone, and Frank Dellaert. "Lagrangian Duality in Complex Pose Graph Optimization." In Optimization and Its Applications in Control and Data Sciences, 139–84. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-42056-1_5.

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Chen, Chunxu, Ling Pei, Changqing Xu, Danping Zou, Yuhui Qi, Yifan Zhu, and Tao Li. "Trajectory Optimization of LiDAR SLAM Based on Local Pose Graph." In Lecture Notes in Electrical Engineering, 360–70. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7751-8_36.

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Jung, Jongdae, and Hyun Myung. "Pose-Sequence-Based Graph Optimization Using Indoor Magnetic Field Measurements." In Advances in Intelligent Systems and Computing, 731–39. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16841-8_66.

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Fujisawa, Katsuki, Toyotaro Suzumura, Hitoshi Sato, Koji Ueno, Yuichiro Yasui, Keita Iwabuchi, and Toshio Endo. "Advanced Computing and Optimization Infrastructure for Extremely Large-Scale Graphs on Post Peta-Scale Supercomputers." In Optimization in the Real World, 1–13. Tokyo: Springer Japan, 2015. http://dx.doi.org/10.1007/978-4-431-55420-2_1.

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Fujisawa, Katsuki, Toyotaro Suzumura, Hitoshi Sato, Koji Ueno, Satoshi Imamura, Ryo Mizote, Akira Tanaka, Nozomi Hata, and Toshio Endo. "Advanced Computing and Optimization Infrastructure for Extremely Large-Scale Graphs on Post-peta-scale Supercomputers." In Advanced Software Technologies for Post-Peta Scale Computing, 207–26. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1924-2_11.

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Fujisawa, Katsuki, Toshio Endo, and Yuichiro Yasui. "Advanced Computing and Optimization Infrastructure for Extremely Large-Scale Graphs on Post Peta-Scale Supercomputers." In Mathematical Software – ICMS 2016, 265–74. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-42432-3_33.

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Gautam, Usha, and Tarun Kumar Rawat. "Analysis of Wideband Second-Order Microwave Integrators." In Innovations in Ultra-Wideband Technologies. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.94843.

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This chapter presents the implementation of stable, accurate, and wideband second-order microwave integrators (SOMIs). These SOMI designs are obtained by the use of various cascading combinations of transmission line sections and shunt stubs. In order to obtain the optimal values of the characteristic impedances of these line elements, the particle swarm optimization (PSO), cuckoo search algorithm (CSA) and gravitational search algorithm (GSA) are used to approximate the magnitude response of the ideal second-order integrator (SOI). Based on magnitude response, absolute magnitude error, phase response, convergence rate, pole-zero plot, and improvement graph, the performance measure criteria for the proposed SOMIs are performed. The results of the simulation and statistical analysis reveal that GSA exceeds the PSO and CSA in order to approximate the ideal SOI in all state-of-the-art eligible for wide-band microwave integrator. The designed SOMI is compact and suitable for applications covering ultra-wideband (UWB). The designed SOMI structure is also simulated on Advanced Design Software (ADS) in the form of a microstrip line on a dielectric constant 2.2 RT/Duroid substrate with a height of 0.762 mm. In the 3–15 GHz frequency range, the simulated magnitude result agrees well with the ideal one.
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Bogataj, David, and Damjana Drobne. "Control of Perishable Goods in Cold Logistic Chains by Bionanosensors." In Materials Science and Engineering, 471–97. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-1798-6.ch019.

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Nanotechnology can contribute to food security in supply chains of agri production-consumption systems. The unique properties of nanoparticles have stimulated the increasing interest in their application as biosensing. Biosensing devices are designed for the biological recognition of events and signal transduction. Many types of nanoparticles can be used as biosensors, but gold nanoparticles have sparked most interest. In the work presented here, we will address the problem of fruit and vegetable decay and rotting during transportation and storage, which could be easily generalized also onto post-harvest loss prevention in general. During the process of rotting, different compounds, including different gasses, are released into the environment. The application of sensitive bionanosensors in the storage/transport containers can detect any changes due to fruit and vegetable decay and transduce the signal. The goal of this is to reduce the logistics cost for this items. Therefore, our approach requires a multidisciplinary and an interdisciplinary approach in science and technology. The cold supply chain is namely a science, a technology and a process which combines applied bio-nanotechnology, innovations in the industrial engineering of cooling processes including sensors for temperature and humidity measurements, transportation, and applied mathematics. It is a science, since it requires the understanding of chemical and biological processes linked to perishability and the systems theory which enables the developing of a theoretical framework for the control of systems with perturbed time-lags. Secondly, it is a technology developed in engineering which relies on the physical means to assure appropriate temperature conditions along the CSC and, thirdly, it is also a process, since a series of tasks must be performed to prepare, store, and transport the cargo as well as monitor the temperature and humidity of sensitive cargo and give proper feedback control, as it will be outlined in this chapter. Therefore, we shall discuss how to break the silos of separated knowledge to build an interdisciplinary and multidisciplinary science of post-harvest loss prevention. Considering the sensors as floating activity cells, modelled as floating nodes, in a graph of such a system, an extended Material Requirement Planning (MRP) theory will be described which will make it possible to determine the optimal feedback control in post-harvest loss prevention, based on bionanosensors. Therefore, we present also a model how to use nanotechnology from the packaging facility to the final retail. Any changes in time, distance, humidity or temperature in the chain could cause the Net Present Value (NPV) of the activities and their added value in the supply chain to be perturbed, as presented in the subchapter. In this chapter we give the answers to the questions, how to measure the effects of some perturbations in a supply chain on the stability of perishable agricultural goods in such systems and how nanotechnology can contribute with the appropriate packaging and control which preserves the required level of quality and quantity of the product at the final delivery. The presented model will not include multicriteria optimization but will stay at the NPV approach. But the annuity stream achieved by improved sensing and feedback control could be easily combined with environmental and medical/health criteria. An interdisciplinary perspective of industrial engineering and management demonstrates how the development of creative ideas born in separate research fields can be liaised into an innovative design of smart control devices and their installation in trucks and warehouses. These innovative technologies could contribute to an increase in the NPV of activities in the supply chains of perishable goods in general.
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Conference papers on the topic "Pose graph optimization"

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Tang, Hengbo, Yunhui Liu, and Luyang Li. "Pose graph optimization with hierarchical conditionally independent graph partitioning." In 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2016. http://dx.doi.org/10.1109/iros.2016.7759502.

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Virgolino Soares, João Carlos, and Marco Antonio Meggiolaro. "A Pose-Graph Optimization tool for MATLAB." In X Congresso Nacional de Engenharia Mecânica. ABCM, 2018. http://dx.doi.org/10.26678/abcm.conem2018.con18-0341.

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Segal, Aleksandr V., and Ian D. Reid. "Hybrid Inference Optimization for robust pose graph estimation." In 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014). IEEE, 2014. http://dx.doi.org/10.1109/iros.2014.6942928.

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Li, Yang, Yoshitaka Ushiku, and Tatsuya Harada. "Pose Graph optimization for Unsupervised Monocular Visual Odometry." In 2019 International Conference on Robotics and Automation (ICRA). IEEE, 2019. http://dx.doi.org/10.1109/icra.2019.8793706.

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Bai, Fang, Teresa Vidal-Calleja, Shoudong Huang, and Rong Xiong. "Predicting Objective Function Change in Pose-Graph Optimization." In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2018. http://dx.doi.org/10.1109/iros.2018.8594248.

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Wang, John, and Edwin Olson. "Robust pose graph optimization using stochastic gradient descent." In 2014 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2014. http://dx.doi.org/10.1109/icra.2014.6907482.

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Boroson, Elizabeth R., Robert Hewitt, Nora Ayanian, and Jean-Pierre de la Croix. "Inter-Robot Range Measurements in Pose Graph Optimization." In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2020. http://dx.doi.org/10.1109/iros45743.2020.9341227.

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Briales, Jesus, and Javier Gonzalez-Jimenez. "Initialization of 3D pose graph optimization using Lagrangian duality." In 2017 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2017. http://dx.doi.org/10.1109/icra.2017.7989600.

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Burguera, Antoni. "Underwater Localization using Probabilistic Sonar Registration and Pose Graph Optimization." In 2018 IEEE/OES Autonomous Underwater Vehicle Workshop (AUV). IEEE, 2018. http://dx.doi.org/10.1109/auv.2018.8729739.

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Moreira, Gabriel, Manuel Marques, and Joao Paulo Costeira. "Fast Pose Graph Optimization via Krylov-Schur and Cholesky Factorization." In 2021 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE, 2021. http://dx.doi.org/10.1109/wacv48630.2021.00194.

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