Relevant bibliographies by topics / Path Detection and following

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Path Detection and following'

Author: Grafiati
Published: 10 September 2021
Last updated: 17 July 2025

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Journal articles on the topic "Path Detection and following"

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Wawrzyniak, Tymon F., Ignacy D. Orłowski, and Marek A. Galewski. "Three-Dimensional Path-Following with Articulated 6DoF Robot and ToF Sensors." Applied Sciences 15, no. 6 (2025): 2917. https://doi.org/10.3390/app15062917.

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This paper presents an algorithm for 3D path-following using an articulated 6-Degree-of-Freedom (DoF) robot as well as experimental verification of the proposed approach. This research extends the classic line-following concept, typically applied in 2D spaces, into a 3D space. This is achieved by equipping a standard industrial robot with a path detection tool featuring six low-cost Time-of-Flight (ToF) sensors. The primary objective is to enable the robot to follow a physically existing path defined in 3D space. The developed algorithm allows for step-by-step detection of the path’s orientation and calculation of consecutive positions and orientations of the detection tool that are necessary for the robot arm to follow the path. Experimental tests conducted using a Nachi MZ04D robot demonstrated the reliability and effectiveness of the proposed solution.
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Ming, Li Yue, Huang Hai, Xu Yang, Zhang Guocheng, Li Jiyong, and Qin Hongde. "Cognition-based hybrid path planning for autonomous underwater vehicle target following." International Journal of Advanced Robotic Systems 16, no. 4 (2019): 172988141985755. http://dx.doi.org/10.1177/1729881419857554.

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Intelligent path planning is one of the key techniques for autonomous underwater vehicles for the purpose of target detection, environmental survey and so on. In order to realize automatic motion plan, an intelligent cognitive architecture for autonomous underwater vehicle motion planning has been proposed to realize complicated target detection and mobile target following in the disturbance environment. A novel adaptive ant colony optimization and particle swarm optimization fusion-based fuzzy rules optimization algorithm has been proposed to generate optimized fuzzy rules. Through this optimization algorithm, the preliminary fuzzy rules can be optimized to realize intelligent motion planning for complicated operation tasks. Experiments of channel following for wall detection and mobile target following in the oceanic environment have verified the validity of path planning method in the implementation of detection and operation tasks.
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Kamejima, Kohji. "Stochastic Path Generation for Anticipative Road Following Guided by Saccadic Object Detection." Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications 2010 (May 5, 2010): 277–82. http://dx.doi.org/10.5687/sss.2010.277.

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Chen, Gang, Dan Liu, Yifan Wang, Qingxuan Jia, and Xiaodong Zhang. "Path planning method with obstacle avoidance for manipulators in dynamic environment." International Journal of Advanced Robotic Systems 15, no. 6 (2018): 172988141882022. http://dx.doi.org/10.1177/1729881418820223.

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Obstacle avoidance is of great importance for path planning of manipulators in dynamic environment. To help manipulators successfully perform tasks, a method of path planning with obstacle avoidance is proposed in this article. It consists of two consecutive phases, namely, collision detection and obstacle-avoidance path planning. The collision detection is realized by establishing point-cloud model and testing intersection of axis-aligned bounding boxes trees, while obstacle-avoidance path planning is achieved through preplanning a global path and adjusting it in real time. This article has the following contributions. The point-cloud model is of high resolution while the speed of collision detection is improved, and collision points can be found exactly. The preplanned global path is optimized based on the improved D-star algorithm, which reduces inflection points and decreases collision probability. The real-time path adjusting strategy satisfies the requirement of reachability and obstacle avoidance for manipulators in dynamic environment. Simulations and experiments are carried out to evaluate the validity of the proposed method, and the method is available to manipulators of any degree of freedom in dynamic environment.
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Guo, Jinghua, Jin Wang, Ping Hu, and Linhui Li. "Robust guaranteed-cost path-following control for autonomous vehicles on unstructured roads." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 232, no. 7 (2017): 896–908. http://dx.doi.org/10.1177/0954407017713089.

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This paper deals with the problem of automatic path-following control for a class of autonomous vehicle systems with parametric uncertainties and external disturbances in cross-country conditions. In the unstructured environments, the unevenness, the discontinuity and the variability of the terrain greatly increase the parametric uncertainties and the external perturbations of autonomous vehicles. To overcome these difficulties, a novel automatic path-following control scheme of vision-based autonomous vehicles is presented by utilizing the guaranteed-cost control theory. First, a new road detection algorithm used for segmenting and extracting the traversable path in unstructured terrains is achieved by using a combination consisting of multiple sensors, and the local relative position information between the vehicles and the desired trajectories can be acquired by the proposed detected algorithm in real time. Then, an optimal guaranteed-cost path-following control system is proposed, which can deal with the parametric uncertainties of autonomous vehicles and ensure the stability of the closed-loop control system. Finally, both simulation tests and experimental results demonstrate that the proposed control scheme can guarantee high path-tracking accuracy irrespective of the parametric uncertainties.
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Arnab, Saha. "Obstacle Avoidance & Light Following Robot." International Journal of Advances In Scientific Research and Engineering (IJASRE) 3, no. 4 (2017): 162–75. https://doi.org/10.5281/zenodo.583843.

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<em>Obstacle avoidance &amp; light following robot can be used for Industrial purpose &amp; Military operation. The major components include an Arduino Uno R3, Servo motor, BO motor, L298N motor driver, LDR module, Ultrasonic HCSR-04 sensor &amp; holder, Chassis body, Battery &amp; battery holder. The system is controlled by the Arduino Uno R3 module which is an advance version of a microcontroller and a part of embedded system. In this work, we have designed a robot, which is compact, autonomous and fully functional. It is a proposed model which can be used in such an environment, which may be vulnerable and risky to human being. It has four types of functions. The functions are light following, obstacle detection and controlling from an android device through Bluetooth or Wi-Fi module&amp; capture the video clips of that area. Obstacle avoider light follower robot detects the light (such as the light of flashlight) and follows light on travelling path. Also it can detect the obstacles while it is moving and make the passes by the obstacles. The robot has two light detection sensors which are prepared with LDRs and an infrared obstacle detecting sensor. The sensitivity of the light sensor can be set by using the trim pots.</em> <strong><em>K</em></strong><strong><em>eywords</em>: </strong><em>Robot </em><em>Sensing System DC motors, Smart Phones, Motor Driver.</em>
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Huang, Peichen, Lixue Zhu, Zhigang Zhang, and Chenyu Yang. "Row End Detection and Headland Turning Control for an Autonomous Banana-Picking Robot." Machines 9, no. 5 (2021): 103. http://dx.doi.org/10.3390/machines9050103.

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A row-following system based on machine vision for a picking robot was designed in our previous study. However, the visual perception could not provide reliable information during headland turning according to the test results. A complete navigation system for a picking robot working in an orchard needs to support accurate row following and headland turning. To fill this gap, a headland turning method for an autonomous picking robot was developed in this paper. Three steps were executed during headland turning. First, row end was detected based on machine vision. Second, the deviation was further reduced before turning using the designed fast posture adjustment algorithm based on satellite information. Third, a curve path tracking controller was developed for turning control. During the MATLAB simulation and experimental test, different controllers were developed and compared with the designed method. The results show that the designed turning method enabled the robot to converge to the path more quickly and remain on the path with lower radial errors, which eventually led to reductions in time, space, and deviation during headland turning.
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Kurashiki, Keita, Kazuki Kono, and Takanori Fukao. "LiDAR Based Road Detection and Control for Agricultural Vehicles." Journal of Robotics and Mechatronics 36, no. 6 (2024): 1516–26. https://doi.org/10.20965/jrm.2024.p1516.

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Recently, the population of agricultural workers in Japan has been declining and aging. As a result, labor shortages have become a serious problem in the agricultural industry. However, the strong dependence on food imports has become a problem. To address this situation, it is necessary to increase the efficiency of food production by automating agricultural work. In this study, we focus on transportation in farming, and develop an unmanned transportation truck. Farm roads are often unpaved or otherwise uneven, and the surrounding environment changes dramatically depending on road surface conditions, vegetation, weather, and season. To realize an unmanned transportation system, achieving robust environmental recognition and operational control is important. Although it is almost certain that no single method can manage all situations for this goal, as part of the system, we propose a method for generating a target path for farming environments using 3D LiDAR (Light Detection and Ranging), and apply a control law to follow the path on uneven surfaces robustly. Furthermore, we generate two types of paths, one based on the center of the drivable area and the other based on road surface geometry, and integrate them into a target path based on their reliability. A nonlinear path-following control law is designed to follow the target path. The proposed method was applied to an experimental truck, and stability was achieved on a real farm road.
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Fatkhurrahman, Januar Arif, and Puji Lestari. "Evaluation NO2 Detection Using Low-Cost Folded-Path Photometer." Journal of Mathematical and Fundamental Sciences 54, no. 3 (2023): 359–71. http://dx.doi.org/10.5614/j.math.fund.sci.2023.54.3.5.

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As it impacts both environmental and health conditions, the measurement of nitrogen dioxide (NO2) in industrial and residential areas needs comprehensive and reliable instrumentation providing long-interference-free operation and minimum maintenance and re-calibration. Differential optical absorption spectroscopy can be used as a direct measurement technique based on the specific absorption characteristics of NO2 following the Beer-Lambert law. This paper proposes a low-cost folded-path photometer to measure NO2 in the air. Cheap tubular acrylic was used as a detection cell with a 3D printed framework, making it compact, modular, and flexible. Evaluation of this differential optical absorption spectroscope (DOAS) was conducted by instrument test responses using NO2 gas. The estimated LOD was ~1263 ppb using a 2-nm resolution of the spectrometer and a 6-meter detection cell length. Deviation of the DOAS was estimated to be 0.8% at high concentration and 2.85% at low concentration based on the calibrated DOAS. Intercomparison of the results was conducted using two different instruments to evaluate the DOAS’s performance by measuring NO2 from motorcycle emissions, which indicated that there was a good correlation between the results. The coefficient correlation (R) was 0.649 for the DOAS- ASTM D1607 Griesz Saltzmann method pairing and 0.846 for the DOAS- electrochemical gas analyzer pairing.
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Seo, Dasom, Jin-Ho Won, Changju Yang, et al. "Development of Boundary Detection Methods Based on Images for Path Following of Autonomous Tractor." Journal of Korean Institute of Communications and Information Sciences 46, no. 11 (2021): 2078–87. http://dx.doi.org/10.7840/kics.2021.46.11.2078.

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Dissertations / Theses on the topic "Path Detection and following"

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Chintalapati, Veera Venkata Tarun Kartik. "Multi-Vehicle Path Following and Adversarial Agent Detection in Constrained Environments." University of Cincinnati / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1613751238253121.

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Schmiterlöw, Maria. "Autonomous Path Following Using Convolutional Networks." Thesis, Linköpings universitet, Datorseende, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-78670.

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Autonomous vehicles have many application possibilities within many different fields like rescue missions, exploring foreign environments or unmanned vehicles etc. For such system to navigate in a safe manner, high requirements of reliability and security must be fulfilled. This master's thesis explores the possibility to use the machine learning algorithm convolutional network on a robotic platform for autonomous path following. The only input to predict the steering signal is a monochromatic image taken by a camera mounted on the robotic car pointing in the steering direction. The convolutional network will learn from demonstrations in a supervised manner. In this thesis three different preprocessing options are evaluated. The evaluation is based on the quadratic error and the number of correctly predicted classes. The results show that the convolutional network has no problem of learning a correct behaviour and scores good result when evaluated on similar data that it has been trained on. The results also show that the preprocessing options are not enough to ensure that the system is environment dependent.
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Zhao, Yang. "Path-following Control of Container Ships." Cleveland State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=csu1563275115222067.

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Nordahl, Håvard. "Optimal path following for underactuated marine vessels." Thesis, Norwegian University of Science and Technology, Department of Engineering Cybernetics, 2008. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-8865.

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<p>This report presents two optimization problems, where three cost-functions are suggested for each. The goal for the first optimization problem is to find a time variant look-ahead distance which improves the performance of the vessel in terms of the cross-track error, relative to constant look-ahead distances. The second optimization problem is an extension of the first, where a time variant surge velocity reference is also calculated. This results in smaller cross-track errors, at the cost of increased calculation time. It is assumed that the path and the desired surge velocity on the path is supplied by some external source. Existing kappa-exponential control laws are used to track the references resulting from the calculated optimal look-ahead distance and surge velocity reference. The predictions needed to solve the optimization problem are made from a model where the control laws are inserted into the dynamics to simplify the model. The optimization problems are solved for two different approaches. The first approach uses an LTV model for predictions and a QP-solver to solve the optimization problem. The second approach forms predictions of the states by numerical integration of the system dynamics and uses an optimization problem solver for general non-linear functions to solve the optimization problem. The latter approach generally results in longer calculation times but better accuracy, while the first approach yields convexity of the optimization problem. A passive observer is used to estimate the current such that it can be included in the predictions. Four of the six suggested cost-functions lead to significantly improved performance of the vessel in terms of the cross-track error. This is true both in the case of no disturbances and in the presence of a constant irrotational current. That is, the position of the vessel converges faster to the path, the vessel stays closer to the path and has less over-shoot in the cross-track error, for the optimal inputs than for constant inputs. The cost-functions includes weights for tuning where the tuning process is easy for some of the cost-functions. One of the cost-functions where only the optimal look-ahead distance is calculated, results in calculation times shorter than the time between samples, after a few time steps. This is a promising result since the application of MPC to fast-dynamic systems such as marine vessels is desired, but often problematic due to too long calculation times for solving the optimization problem. It takes more time to solve the optimization problem when the optimal surge velocity reference is found in addition to the optimal look-ahead distance.</p>
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Norrsjö, Viktor, and Viktor Stenberg. "PID Controllers for Autonomous Vehicle Path Following." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-214711.

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Autonomous vehicles are set to create a paradigmshift. Everyone could relax on their way to work and no accidentsdue to falling asleep behind the wheel would occur. For this tohappen the autonomous vehicle requires among many differentcomponents, a lane following system. In this paper such asystem is developed. First a mathematical model that describea vehicles behaviour is derived. Then a regulator structure withcontrollers and other components is developed. Finally the systemis implemented as a complete simulator that simulates the movingvehicle. Several different scenarios are tested and the performanceof the system is evaluated. A working simulator is achieved witha vehicle following the predefined path with little deviation, thesystems behaviour is also smooth. It is concluded that the proposedsolution is sufficient for moderates vehicle speeds, but at higherspeeds the mathematical model will not be accurate and theperformance of the system will be insufficient.
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Mehrok, Parwinder Singh. "Quadrotor UAV Path Following using Trajectory Shaping." DigitalCommons@USU, 2016. https://digitalcommons.usu.edu/etd/4997.

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This research proposes to adapt the concept of trajectory shaping guidance law on a quadrotor to follow several different predefined, compact paths. Keeping the real world nonlinearities, sensor and process noise in mind, the technique is simulated using MATLAB-Simulink. This guidance concept is implemented on a real, custom built quadrotor for which a new testing platform was developed from the ground up. Also, the results obtained from the trajectory shaping concept are compared to the performance characteristics of another path following concept called differential flatness. In addition to this, root mean square of position error data is used to compare the vehicle convergence to the desired trajectory.
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Mellodge, Patricia. "Feedback Control for a Path Following Robotic Car." Thesis, Virginia Tech, 2002. http://hdl.handle.net/10919/32100.

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This thesis describes the current state of development of the Flexible Low-cost Automated Scaled Highway (FLASH) laboratory at the Virginia Tech Transportation Institute (VTTI). The FLASH lab and the scale model cars contained therein provide a testbed for the small scale development stage of intelligent transportation systems (ITS). In addition, the FLASH lab serves as a home to the prototype display being developed for an educational museum exhibit. This thesis also gives details of the path following lateral controller implemented on the FLASH car. The controller was developed using the kinematic model for a wheeled robot. The global model is converted into the path coordinate model so that only local variables are needed. then the path coordinate model is converted into chained form and a controller is given to perform path following. The path coordinate model introduces a new parameter to the system: the curvature of the path. Thus, it is necessary to provide the path's curvature value to the controller. Because of the environment in which the car is operating, the curvature values are known a priori. Several online methods for determining the curvature are developed. A MATLAB simulation environment was created with which to test the above algorithms. The simulation uses the kinematic model to show the car's behavior and implements the sensors and controller as closely as possible to the actual system. The implementation of the lateral controller in hardware is discussed. The vehicle platform is described and the harware and software architecture detailed. The car described is capable of operating manually and autonomously. In autonomous mode, several sensors are utilized including: infrared, magnetic, ultrasound, and image based technology. The operation of each sensor type is described and the information received by the processor from each is discussed.<br>Master of Science
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Baumann, Markus. "Newton's Method for Path-Following Problems on Manifolds." Doctoral thesis, kostenfrei, 2008. http://www.opus-bayern.de/uni-wuerzburg/volltexte/2008/2809/.

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Xu, Song. "Non-interior path-following methods for complementarity problems /." Thesis, Connect to this title online; UW restricted, 1998. http://hdl.handle.net/1773/5793.

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Lindefelt, Anna, and Anders Nordlund. "A Path Following Method with Obstacle Avoidance for UGVs." Thesis, Linköping University, Department of Electrical Engineering, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-11242.

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<p>The goal of this thesis is to make an unmanned ground vehicle (UGV) follow a given reference trajectory, without colliding with obstacles in its way. This thesis will especially focus on modeling and controlling the UGV, which is based on the power wheelchair Trax from Permobil.</p><p>In order to make the UGV follow a given reference trajectory without colliding, it is crucial to know the position of the UGV at all times. Odometry is used to estimate the position of the UGV relative a starting point. For the odometry to work in a satisfying way, parameters such as wheel radii and wheel base have to be calibrated. Two control signals are used to control the motion of the UGV, one to control the speed and one to control the steering angles of the two front wheels. By modeling the motion of the UGV as a function of the control signals, the motion can be predicted. A path following algorithm is developed in order to make the UGV navigate by maps. The maps are given in advance and do not contain any obstacles. A method to handle obstacles that comes in the way is presented.</p>
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Books on the topic "Path Detection and following"

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(Firm), Chronicle Books, ed. Hopi: Following the path of peace. Chronicle Books, 1994.

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Papa, Umberto. Embedded Platforms for UAS Landing Path and Obstacle Detection. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73174-2.

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Ariante, Gennaro, and Umberto Papa. Embedded Platforms for UAS Landing Path and Obstacle Detection II. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-59754-1.

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Gregorutti, Gustavo. Following the path from teaching to research university: Increasing knowledge productivity. Cambridge Scholars, 2011.

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Breathnach, Sarah Ban. The simple abundance companion: Following your authentic path to something more. Warner Books, 2000.

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W, Cobb Clifford, and Giacalone Joseph A, eds. The path to justice: Following in the footsteps of Henry George. Blackwell, 2001.

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M, Smith L., and United States. National Aeronautics and Space Administration., eds. Final report for grant titled: SSME propellant path leak detection real-time. National Aeronautics and Space Administration, 1994.

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Lammey, William C. Karmic tarot: A new system for finding and following your life's path. Borgo Press, 1989.

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Jorge, Galán-Vioque, Osinga Hinke M, and SpringerLink (Online service), eds. Numerical Continuation Methods for Dynamical Systems: Path following and boundary value problems. Canopus Publishing Limited, 2007.

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Washington (State). Puget Sound Water Quality Action Team. The journey home: Following the path of migrating salmon in Whatcom County. Edited by Groff Summer, Du Pré Robyn J, and Re Sources (Organization). ReSources for Sustainable Communities, 2001.

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Book chapters on the topic "Path Detection and following"

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Méot, François. "Microtron." In Particle Acceleration and Detection. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-59979-8_6.

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AbstractThis chapter introduces the microtron, and to the theoretical material needed for the simulation exercises. It begins with a brief reminder of the historical context, and continues with the beam optics and acceleration techniques that the microtron method leans on, relying in that on basic charged particle optics and acceleration concepts introduced in the previous chapters. It further addresses the following aspects: spiraling accelerated orbits tangenting at the accelerating gap, beam recirculation through an accelerating system, via return arcs, methods for periodic motion stability, harmonic number jump acceleration. The simulation of a classical microtron only requires one optical element: DIPOLE, and CAVITE for acceleration. Simulation of a racetrack microtron adds DRIFT to simulate drift sections, possibly BEND for small steering dipoles along the recirculation paths, and a series of CAVITE to simulate a linac section. Particle monitoring requires keywords introduced in the previous chapters, such as FAISCEAU, FAISTORE, PICKUPS, and some others. Beam path and optics optimization use FIT[2]. SYSTEM is used to, mostly, resort to gnuplot so as to end simulations with some nice graphs (orbits, fields, or else) obtained by reading data from output files such as zgoubi.fai (resulting from the use of FAISTORE), zgoubi.plt (resulting from IL $$=$$ = 2), or other zgoubi.*.out files resulting from a PRINT command.
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Sviatov, Kirill, Alexander Miheev, Yuriy Lapshov, Vadim Shishkin, and Sergey Sukhov. "Detection of Scenes Features for Path Following on a Local Map of a Mobile Robot Using Neural Networks." In Recent Research in Control Engineering and Decision Making. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65283-8_22.

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Monteiro, Renato, and Michael Todd. "Path-Following Methods." In International Series in Operations Research & Management Science. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4381-7_10.

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Bai, He, Murat Arcak, and John Wen. "Synchronized Path Following." In Cooperative Control Design. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0014-1_7.

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Vanderbei, Robert J. "A Path-Following Method." In International Series in Operations Research & Management Science. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-74388-2_18.

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Dieci, Luca, Maria Grazia Gasparo, and Alessandra Papini. "Path Following by SVD." In Computational Science – ICCS 2006. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11758549_92.

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Vanderbei, Robert J. "A Path-Following Method." In International Series in Operations Research & Management Science. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39415-8_18.

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Vanderbei, Robert J. "A Path-Following Method." In International Series in Operations Research & Management Science. Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-5662-3_17.

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Vanderbei, Robert J. "A Path-Following Method." In International Series in Operations Research & Management Science. Springer US, 2014. http://dx.doi.org/10.1007/978-1-4614-7630-6_18.

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Frenk, Hans, Kees Roos, Tamás Terlaky, and Shuzhong Zhang. "Polynomiality of Path-Following Methods." In Applied Optimization. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4757-3216-0_3.

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Conference papers on the topic "Path Detection and following"

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Almeida, Allan S., Tiago T. Ribeiro, and Andre G. S. Conceicao. "Transfer Learning-based Lane Line Detection System for Visual Path Following Control." In 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE). IEEE, 2024. http://dx.doi.org/10.1109/case59546.2024.10711739.

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Dikarew, Alexej, and Tobias Winkler. "Rotorcraft Guidance with Sampling based Model Predictive Control." In Vertical Flight Society 80th Annual Forum & Technology Display. The Vertical Flight Society, 2024. http://dx.doi.org/10.4050/f-0080-2024-1051.

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A key technology in automation of rotorcraft flight is collision-free guidance. Especially in operations close to the ground, detection and automatic avoidance of ground-based obstacles and aircraft is a demanding task. This paper presents a sampling-based model predictive approach for collision-free guidance of rotorcraft. The method calculates control inputs for the flight controller by predicting the closed-loop dynamics of the rotorcraft for a short time horizon and evaluating the predictions with a cost function, which can take an arbitrary form. The approach implements a simple algorithm, mitigating the need for iterative optimization and allowing for deterministic execution time. The cost function is set to ensure collision-free maneuvering while following a desired path, as well as considering constraints of the rotorcraft states and control inputs. The path following performance is tested in closed-loop simulations with a non-linear helicopter model. The algorithm is implemented on a graphics processing unit for parallel execution, strongly decreasing the computation time.
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Antunes, Duarte J. "Infinite-horizon Linear Quadratic Path-Following." In 2024 IEEE 63rd Conference on Decision and Control (CDC). IEEE, 2024. https://doi.org/10.1109/cdc56724.2024.10885993.

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Jiang, Weihao. "Surface Vehicle Path-Following Control Considering Uncertainties." In 2024 11th International Forum on Electrical Engineering and Automation (IFEEA). IEEE, 2024. https://doi.org/10.1109/ifeea64237.2024.10878758.

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Namorato Pusssente, Guilherme Augusto, Tiago Henrique Santa Maria, Andre Luis Marques Marcato, and Eduardo Pestana de Aguiar. "Trajectory Detection Method for Transmission Line Path Following Control." In 2021 Latin American Robotics Symposium (LARS), 2021 Brazilian Symposium on Robotics (SBR), and 2021 Workshop on Robotics in Education (WRE). IEEE, 2021. http://dx.doi.org/10.1109/lars/sbr/wre54079.2021.9605373.

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Xing, Wang, Yan Wang, and Haitao Wang. "Three-dimensional unwrapping algorithm based on reliability sorting following a path with added threshold." In Seventh Symposium on Novel Photoelectronic Detection Technology and Application 2020, edited by Junhao Chu, Qifeng Yu, Huilin Jiang, and Junhong Su. SPIE, 2021. http://dx.doi.org/10.1117/12.2586418.

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Fan, Liuyi, Jizhou Lai, Pin Lyu, and Cheng Yuan. "Visual Path Following Method for Quadrotors Based on Structured Edge Detection*." In 2018 IEEE CSAA Guidance, Navigation and Control Conference (GNCC). IEEE, 2018. http://dx.doi.org/10.1109/gncc42960.2018.9019154.

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Fleischmann, Patrick, Johannes Kneip, and Karsten Berns. "An adaptive detection approach for autonomous forest path following using stereo vision." In 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV). IEEE, 2016. http://dx.doi.org/10.1109/icarcv.2016.7838670.

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Heidari, F., and R. Fotouhi. "Point to-Point and Path Following Navigation of Mobile Robot in Farm Settings." In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-35435.

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A fully integrated navigation strategy of a wheeled mobile robot in farm settings and off-road terrains is described here. The proposed strategy is composed of four main actions which are: sensor data analysis, obstacle detection, obstacle avoidance, and goal seeking. Using these actions, the navigation approach is capable of autonomous row-detection, row-following and path planning motion in outdoor settings such as farms. In order to drive the robot in off-road terrain, it must detect holes or ground depressions (negative obstacles), that are inherent parts of these environments, in real-time at a safe distance from the robot. Key originalities of the proposed approach are its capability to accurately detect both positive (over ground) and negative obstacles, and accurately identify the end of the rows of trees/bushes in farm/orchard and enter the next row. Experimental evaluations were carried out using a differential wheeled mobile robot in different farm settings. The mobile robot, used for experiments, utilizes a tilting unit which carries a laser range finder to detect objects in the environment, and a RTK-DGPS unit for localization. The experiments demonstrate that the proposed technique is capable of successfully detecting and following rows (path following) as well as robust navigation of the robot for point-to-point motion.
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Tang, Jinxun, Xuanyu Chen, Weinan Chen, et al. "Collision-Free Edge-Following Path Planner based on Adaptive Sampling Continuous Collision Detection." In 2024 IEEE International Conference on Industrial Technology (ICIT). IEEE, 2024. http://dx.doi.org/10.1109/icit58233.2024.10540807.

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Reports on the topic "Path Detection and following"

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Wright, S. J. A path-following interior-point algorithm for linear and quadratic problems. Office of Scientific and Technical Information (OSTI), 1993. http://dx.doi.org/10.2172/432434.

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Dwyer, Matthew B., Suzette Person, and Sebastian Elbaum. Controlling Factors in Evaluating Path-sensitive Error Detection Techniques. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada459081.

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Rocha, Guilherme V., Peng Zhao, and Bin Yu. A Path Following Algorithm for Sparse Pseudo-Likelihood Inverse Covariance Estimation (SPLICE). Defense Technical Information Center, 2008. http://dx.doi.org/10.21236/ada487557.

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Chuangyin, Dang, Herings P. Jean-Jacques, and Li Peixuan. An Interior-Point Path-Following Method to Compute Stationary Equilibria in Stochastic Games. Maastricht University, Graduate School of Business and Economics, 2020. http://dx.doi.org/10.26481/umagsb.20001.

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Mirsky, G., J. Tantsura, I. Varlashkin, and M. Chen. Bidirectional Forwarding Detection (BFD) Reverse Path for MPLS Label Switched Paths (LSPs). RFC Editor, 2024. http://dx.doi.org/10.17487/rfc9612.

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Laughlin, Madison, Natasha Antonova, John Boetsch, Brian Harvey, and Joshua Lawler. Landscape disturbance status and trend analysis report for the North Coast and Cascades Inventory and Monitoring Network, 1987–2017. National Park Service, 2025. https://doi.org/10.36967/2313366.

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Disturbance is a key characteristic of landscapes that significantly influences ecosystem functions such as carbon storage, water storage, and nutrient cycling, as well as ecosystem structure and productivity. This report summarizes disturbance patterns and trends for three national parks—North Cascades National Park Service Complex, Olympic National Park, and Mount Rainier National Park—and adjacent federally protected wilderness areas in the Pacific Northwest. We assessed changes greater than 0.8 ha across a 31-year period from 1987 through 2017 as detected using freely available satellite imagery, an automated change detection algorithm, and human review to identify and label disturbance areas in the following categories: Fire, Riparian Change, Avalanche, Defoliation, Mass Movement, Blowdown, Coastal Change, Ice Damage, Development, and Clearing. Fire was the predominant disturbance category for all parks combined, affecting 78% of cumulative disturbed area, followed by Defoliation which affected approximately 12% of total disturbed area. Generalized linear models indicated significant increases of annual disturbed area affected by Fire at Mount Rainier and Olympic National Park. Mean disturbance patch size also increased for Mount Rainier and all park study areas combined. Additionally, the number of Defoliation disturbance events at North Cascades National Park Service Complex and in all park study areas combined increased in the latter half of the study period (2000 to 2017) compared with the first half, as well as annual area affected by Defoliation in the eastern portion of North Cascades. These results, maps, and summaries provide useful baseline information about the frequency, extent, and magnitude of landscape change processes in and adjacent to our parks that can be used for guiding natural resource planning and understanding disturbance patterns in remote wilderness areas.
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Petersen, James H. Compensatory Feeding Following a Predator Removal Program : Detection and Mechanisms, 1982-1996 Progress Report. Office of Scientific and Technical Information (OSTI), 2002. http://dx.doi.org/10.2172/797030.

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Bartels, Ludwig. Surface Reactions Following Ultra Fast Substrate Excitation: A Path Towards Atomic Scale Resolution of High-temperature Reactions at Metal Surfaces. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada564034.

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Ziolkowski, Christopher J. DTPH56-06-T-005 Differential Impedance Obstacle Detection Sensor (DIOD) - Phase 2. Pipeline Research Council International, Inc. (PRCI), 2007. http://dx.doi.org/10.55274/r0011978.

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The objective of the Phase 2 project is to develop a tool that can be coupled with a pipeline drill rig to detect pipeline obstacles in the drill path. This project is also referred to as Differential Impedance Obstacle Detection. The physical size of the prototype sensor must be such as to minimally impact the design of commercial drill heads.
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Moorehead, Stewart. Unsettled Topics in Obstacle Detection for Autonomous Agricultural Vehicles. SAE International, 2021. http://dx.doi.org/10.4271/epr2021029.

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Agricultural vehicles often drive along the same terrain day after day or year after year. Yet, they still must detect if a moveable object, such as another vehicle or an animal, happens to be on their path or if environmental conditions have caused muddy spots or washouts. Obstacle detection is one of the major missing pieces that can remove humans from highly automated agricultural machines today and enable the autonomous vehicles of the future. Unsettled Topics in Obstacle Detection for Autonomous Agricultural Vehicles examines the challenges of environmental object detection and collision prevention, including air obscurants, holes and soft spots, prior maps, vehicle geometry, standards, and close contact with large objects.
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