Relevant bibliographies by topics / Terrain vehicle

Contents

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

Academic literature on the topic 'Terrain vehicle'

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

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Journal articles on the topic "Terrain vehicle"

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EL-KABBANY, AHMED, and A. RAMIREZ-SERRANO. "TERRAIN ROUGHNESS ASSESSMENT FOR HIGH SPEED UGV NAVIGATION IN UNKNOWN HETEROGENEOUS TERRAINS." International Journal of Information Acquisition 07, no. 02 (June 2010): 165–76. http://dx.doi.org/10.1142/s0219878910002142.

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This paper addresses the problem of determining the maximum allowable speed (V) of a vehicle traversing unknown off-road terrains. The calculated maximum speed achieves the fastest navigation without exceeding an allowable range of transmitted force (Fall) to the vehicle's frame. The proposed system enables the vehicle to transit between different terrains safely. The system's input are: (i) a 3D range image of the terrain and (ii) the vehicle's dimensions and characteristics (e.g., suspension parameters). First the terrain roughness is assessed; then the corresponding maximum allowable speed is calculated. In this paper a novel Roughness Index (RI) is used to represent the terrain roughness. This index is calculated based on the standard deviation of the terrain points' elevations (3D range image). A closed form expression of the maximum allowable vehicle speed is developed (as function of the vehicle's properties, Fall, RI, and probability of not exceeding Fall). The proposed system can be used as a driver assistant system to enhance the vehicle performance, increase its life time, and reduce the maintenance cost. In addition, it is a key module in Unmanned Ground Vehicles (UGVs) navigation systems; as it provides the navigation system with necessary information for path and speed planning.
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Wei, Wei, Xin Hui Liu, and Yan Li Chen. "Research on Stability of a 2 DOF Articulated Vehicle." Advanced Materials Research 201-203 (February 2011): 2709–16. http://dx.doi.org/10.4028/www.scientific.net/amr.201-203.2709.

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In many fields’ rough-terrain vehicles, e.g., mineral exploration vehicles, military applications vehicles, vehicles that can move on rough terrains are desired. The ability of obstacle-climbing was affected by stability of vehicle. The stability of vehicle is closely related to the body attitude, which composes with a number of bodies. For this reason, in this paper, a wheeled mobile vehicle with 2 DOF articulated frame (2DWAV), for example, the new concept of correlative stability is presented. The stability of 2DWAV was analyzed based on static and dynamic in this paper, when it was driving on rough terrain. Finally, the simulation and experiment on rough terrain are carried out.
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Rahman, A., A. Yahya, and A. K. M. Mohiuddin. "Mobility investigation of a designed and developed segmented rubber track vehicle on Sepang peat terrain in Malaysia." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 221, no. 7 (July 1, 2007): 789–800. http://dx.doi.org/10.1243/09544070jauto139.

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The traction mechanics of a vehicle was developed based on the track-terrain interaction mechanism. The vehicle was tested on three different terrains: terrain I, terrain II, and terrain III. The tractive effort of the vehicle increased 14 per cent when the moisture content of the terrain increased from 59.85 per cent to 81.06 per cent. A traction coefficient of 48 per cent of the vehicle's gross weight justified the vehicle's optimum design for the Sepang peat terrain. Less variability of the vehicle's tractive effort for straight motion in the range of 7.5 per cent to 13.2 per cent and for turning motion in the range of 9 per cent to 11.5 per cent between the predicted and measured tractive effort on the peat terrain III for different loading and operating speeds substantiate the validity of the developed mathematical model.
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Waldron, K. J. "Terrain Adaptive Vehicles." Journal of Mechanical Design 117, B (June 1, 1995): 107–12. http://dx.doi.org/10.1115/1.2836442.

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Research on walking vehicles and variable configuration wheeled vehicles is reviewed. The central feature of the vehicles discussed is terrain adaptive capability. The principal elements of the technical problems of coordination and control are discussed for each vehicle type. Examples of each vehicle type are discussed and an extensive reference list is provided. Although the article is primarily a review article, it contains a new discussion of the coordination problem of robotic mechanisms.
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Waldron, K. J. "Terrain Adaptive Vehicles." Journal of Vibration and Acoustics 117, B (June 1, 1995): 107–12. http://dx.doi.org/10.1115/1.2838649.

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Research on walking vehicles and variable configuration wheeled vehicles is reviewed. The central feature of the vehicles discussed is terrain adaptive capability. The principal elements of the technical problems of coordination and control are discussed for each vehicle type. Examples of each vehicle type are discussed and an extensive reference list is provided. Although the article is primarily a review article, it contains a new discussion of the coordination problem of robotic mechanisms.
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Yang, Fan, Guoyu Lin, and Weigong Zhang. "Terrain classification for terrain parameter estimation based on a dynamic testing system." Sensor Review 35, no. 4 (September 21, 2015): 329–39. http://dx.doi.org/10.1108/sr-01-2015-0003.

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Purpose – This paper aims to gain the real-time terrain parameters of the battlefield for the evaluation of military vehicle trafficability. In military missions, improvements in vehicle mobility have the potential to greatly increase the military operational capacity, in which vehicle trafficability plays a significant role. Design/methodology/approach – In this framework, an online terrain parameter estimation method based on the Gauss-Newton algorithm is proposed to estimate the primary terrain mechanical parameters. Good estimation results are indicated, unless the initial values involved are properly selected. Correspondingly, a method of terrain classification is then presented to contribute to the selection of the initial values. This method uses the wavelet packet transform technique for feature extraction and adopts the support vector machine algorithm for terrain classification. Once the terrain type is identified, advices can be given on the initial value selection referring to the empirical terrain parameters. Findings – On the basis of a dynamic testing system suitable for real military vehicles, the proposed algorithms are validated. High estimation accuracy of the terrain parameters is indicated on sandy loam, and good classification performance is demonstrated on four tested terrains. Originality/value – The presented algorithm outperforms the existing methods, which not only realizes the online terrain parameter estimation but also develops the estimation accuracy. Moreover, its effectiveness is confirmed by real vehicle tests in practice.
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Taghavifar, Hamid, and Subhash Rakheja. "A methodology to analyze the vehicle vibration response to deformable terrain stiffness and damping properties." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 234, no. 4 (July 21, 2019): 1123–36. http://dx.doi.org/10.1177/0954407019863610.

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A dynamic soil–wheel interaction model that considers energy loss due to soil compaction during multiple trafficking can potentially yield an enhanced understanding of vibration responses of a vehicle traversing the deformable terrains. This article presents a practical methodology for modeling the vehicle ride vibration responses, while interacting with deformable terrain irregularities. The proposed formulations incorporate adaptive contact patch and tire deflection in addition to soil sinkage using the Bekker’s pressure–sinkage relationship. The effect of repeated passes of the driven as well as driving wheels on effective stiffness and damping of the soil is also incorporated in the proposed formulations considering a tire slip term by adoption of the Holm’s theory. An in-plane 4-degrees-of-freedom vehicle model is formulated considering a generic compliant tire coupled with the deformable soil model and MSC ADAMS multibody dynamic model is employed for the co-simulations and validation purpose. The coupled terrain–vehicle is analyzed to determine chassis vibration responses together with variations in the dynamic tire–terrain contact force in the time and frequency domains. The results suggested that the root mean square vertical and pitch chassis acceleration responses of the vehicle operating on a deformable terrain are lower than those obtained for the undeformable terrain. The ratio of the dynamic tire force to the static load, a measure of road holding of the vehicle, however, tends to be higher for the deformable terrain. Both the road holding and root mean square chassis acceleration responses, invariably, show a significant increase with increase in the vehicle forward speed. The proposed methodology may serve as an important tool for assessing the vibration exposure of operators and for deriving optimal suspension designs for vehicles operating on deformable terrains.
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Kale, Yogesh S., S. V. Rathkanthiwar, Bhagyashree Sharma, Janhavi Ghuguskar, Kireet Deshmukh, Rushikesh Kate, and Pranay Thakre. "Autonomous Terrain Vehicle." Indian Journal of Science and Technology 14, no. 25 (July 5, 2021): 2119–27. http://dx.doi.org/10.17485/ijst/v14i25.872.

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Aghazadeh, N., and H. Taghavifar. "Study on the Track Wheeled Vehicle Designing for Off-Road Operations on Snowy and Wet Terrains." Cercetari Agronomice in Moldova 48, no. 4 (December 1, 2015): 5–12. http://dx.doi.org/10.1515/cerce-2015-0047.

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Abstract Off-road vehicle trafficking is of interesting subjects for agricultural, mining and civil engineering purposes. The traversing over snowy and wet terrain is of greater importance regarding the sinkage and terrain properties. The motion resistance, traction, sinkage, and vehicle stability are functions of wheel-terrain interactions and particularly the contact patch characteristics. As adoption of wheeled vehicles on snowy terrain is difficult, tracked wheel vehicles are of greater interest and applicability. In this paper, the designing and analysis of tracked wheel system mounted on a light weight all-terrain vehicle (ATV) is addressed. The designing considerations are based on semi-empirical models (Bekker and Mohr-Coulomb criterion) and experimentally obtained data on the snow mechanical properties for the test region. Based on the analysis, it is observed that the greatest value of total deformation for the front and rear chasses are obtained at 0.00028485 and 0.00026229 m, respectively. The von Mises yield criterion addresses that the yielding of materials starts when the second deviatoric stress invariant gets to a critical value close to failure. Furthermore, the greatest values of von Mises stress for the front and rear tracked wheel chassis are equal to 64.60 and 62.48 MPa, respectively. The similarity is that the critical point is situated at the coincidence point between the inclined and longitudinally oriented rods (joint point). It is concluded that the developed vehicle could serve as a functional vehicle to perform on different off-road operational condition particularly wet terrains.
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Feng, Yu, and Qu Xian. "Development and application of testing system for vibration and ride comfort of all-terrain vehicle." Noise & Vibration Worldwide 50, no. 8 (August 17, 2019): 239–44. http://dx.doi.org/10.1177/0957456519869930.

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All-terrain vehicles have a remarkable capacity to handle a variety of irregular pavements, demonstrating its great potential in military domain as well as in the field of sports, entertainment, and so on. For all-terrain vehicles, the ride comfort is the core skill and one of the most important performance parameters. Little researches have been done into the ride comfort of all-terrain vehicle, particularly into the comprehensive ride comfort test and evaluation system. Combing the all-terrain vehicle vibration characteristics with the standards of ISO 2631, ISO 5349, and so on, a hardware testing system was developed for evaluating the all-terrain vehicle ride comfort. At the same time, a software analysis system was also built under the help of the hardware test system, which has been used to test and analyze many all-terrain vehicles. According to the test results and drivers’ subjective evaluation, the test system was proved to be reliable, convenient, and able to effectively evaluate the all-terrain vehicle ride comfort, providing the theoretical basis for improving the ride comfort of all-terrain vehicles.
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Dissertations / Theses on the topic "Terrain vehicle"

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Becker, Carl Martin. "Profiling of rough terrain." Pretoria : [s.n.], 2008. http://upetd.up.ac.za/thesis/available/etd-11262009-171410/.

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Smith, Robert. "Terrain-aided navigation of an underwater vehicle." Thesis, University of Oxford, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.244626.

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Frisk, Alexander. "Real-Time Vehicle Trails in Deformable Terrain." Thesis, Umeå universitet, Institutionen för datavetenskap, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-136485.

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One way to make racing games more realistic is to have the vehicles in the game deform the terrain and leave permanent trails when driving them. This master thesis presents algorithms and theories about generating those trails behind the vehicles in real-time applications. The proposed trail system is based on Bézier curves to represent and store the path of the trails. All the steps in the algorithm needed to create the trail and handle some of the edge cases are explained in detail. The game called Snow Moto Racing Freedom by Zordix, which is used for testing and implementing the solutions, is covered as well. The finished trail system has both been implemented as a CPU and as a GPU based version, where the two implementations have been tested to see which one is the most effective in the game used. The report is summarized with a list of extensions which can be used to further develop and enhance the trail system. It ends with a summary of the project as a whole with some advices for a similar projects.
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Wiberg, Viktor. "Terrain machine learning : A predictive method for estimating terrain model parameters using simulated sensors, vehicle and terrain." Thesis, Umeå universitet, Institutionen för fysik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-149815.

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Predicting terrain trafficability of deformable terrain is a difficult task with applications in e.g, forestry, agriculture, exploratory missions. The currently used techniques are neither practical, efficient, nor sufficiently accurate and inadequate for certain soil types. An online method which predicts terrain trafficability is of interest for any vehicle with purpose to reduce ground damage, improve steering and increase mobility. This thesis presents a novel approach for predicting the model parameters used in modelling a virtual terrain. The model parameters include particle stiffness, tangential friction, rolling resistance and two parameters related to particle plasticity and adhesion. Using multi-body dynamics, both vehicle and terrain can be simulated, which allows for an efficient exploration of a great variety of terrains. A vehicle with access to certain sensors can frequently gather sensor data providing information regarding vehicle-terrain interaction. The proposed method develops a statistical model which uses the sensor data in predicting the terrain model parameters. However, these parameters are specified at model particle level and do not directly explain bulk properties measurable on a real terrain. Simulations were carried out of a single tracked bogie constrained to move in one direction when traversing flat, homogeneous terrains. The statistical model with best prediction accuracy was ridge regression using polynomial features and interaction terms of second degree. The model proved capable of predicting particle stiffness, tangential friction and particle plasticity, with moderate accuracy. However, it was deduced that the current predictors and training scenarios were insufficient in estimating particle adhesion and rolling resistance. Nevertheless, this thesis indicates that it should be possible to develop a method which successfully predicts terrain model properties.
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Noréus, Olof. "Modelling of six-wheeled electric transmission terrain vehicle." Licentiate thesis, KTH, Aeronautical and Vehicle Engineering, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4291.

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In vehicles with electric transmission and independent wheel stations, it is possible to have a possibility to control propulsion, steering and suspension individually for each wheel. This makes it possible to improve mobility, performance and driving safety. The long term goal of this work is to develop a methodt hat can evaluate and improve the mobility of such vehicles in terrain. This contribution concerns how a six wheeled electric transmission vehicle should be modelled to enable evaluation of the dynamic behaviour in different type of terrain. This is made by combining modelling of vehicle, transmission and tire-terrain behaviour.

For wheeled vehicles an electric transmission with hub motors provides the ability to accurately control the torque on every wheel independently, giving a great ability to improve both mobility in terrain and vehicle behaviour on road. In this work the components of a diesel-electric powertrain for off-road vehicles are modelled and a control layout with the possibility to include functions for improved performance both while driving off- and on-road is proposed.

To handle driving on soft ground, a tire/terrain model is needed. The model should include lateral deformation in order to be able to steer. A tire/terrain model is derived based on the ideas of Wong and Reece. The terrain characteristics are chosen to be described by parameters according to the Bekker model, since this data are widely available in literature.

The developed tire/terrain model has been implemented together with a vehicle model. This terrain vehicle model is shown to be able to estimate sinkage, rolling resistance, traction force and steering characteristics, of a six wheeledterrain vehicle using electric transmission.

To conclude, models of a six-wheeled vehicle with electric transmission and tire models both for soft and rigid ground have been developed. These models form a simulation platform, which makes it possible to evaluate control strategies for the electric transmission with the purpose to improve mobility.

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Noréus, Olof. "Modelling of six-wheeled electric transmission terrain vehicle /." Stockholm : Kungl. tekniska högskolan, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4291.

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Juriga, Jacob T. "Terrain aided navigation for REMUS autonomous underwater vehicle." Thesis, Monterey, California: Naval Postgraduate School, 2014. http://hdl.handle.net/10945/42654.

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Approved for public release; distribution is unlimited
This research investigates the ability to create an undersea bathymetry map and navigate relative to the map. This is known as terrain aided navigation (TAN). In our particular case, the goal was for an autonomous underwater vehicle (AUV) to reduce positional uncertainty through the use of downward-looking swath sonar and employing TAN techniques. This is considered important for undersea operations where positioning systems such as GPS are either not available or difficult to put in place. There are several challenges associated with TAN that are presented: The image processing necessary to extract altitude data from the sonar image, the initial building of the bathymetry map, incorporating a system and measurement model that takes into consideration AUV motion and sensor uncertainty and near-optimal, real-time estimation algorithms. The thesis presents a methodology coupled with analysis on datasets collected from joint Naval Postgraduate School/National Aeronautical Space Administration experimentation conducted at the Aquarius undersea habitat near Key Largo, Florida. .
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Pedreira, Carabel Carlos Javier. "Terrain Mapping for Autonomous Vehicles." Thesis, KTH, Datorseende och robotik, CVAP, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-174132.

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Autonomous vehicles have become the forefront of the automotive industry nowadays, looking to have safer and more efficient transportation systems. One of the main issues for every autonomous vehicle consists in being aware of its position and the presence of obstacles along its path. The current project addresses the pose and terrain mapping problem integrating a visual odometry method and a mapping technique. An RGB-D camera, the Kinect v2 from Microsoft, was chosen as sensor for capturing information from the environment. It was connected to an Intel mini-PC for real-time processing. Both pieces of hardware were mounted on-board of a four-wheeled research concept vehicle (RCV) to test the feasibility of the current solution at outdoor locations. The Robot Operating System (ROS) was used as development environment with C++ as programming language. The visual odometry strategy consisted in a frame registration algorithm called Adaptive Iterative Closest Keypoint (AICK) based on Iterative Closest Point (ICP) using Oriented FAST and Rotated BRIEF (ORB) as image keypoint extractor. A grid-based local costmap rolling window type was implemented to have a two-dimensional representation of the obstacles close to the vehicle within a predefined area, in order to allow further path planning applications. Experiments were performed both offline and in real-time to test the system at indoors and outdoors scenarios. The results confirmed the viability of using the designed framework to keep tracking the pose of the camera and detect objects in indoor environments. However, outdoor environments evidenced the limitations of the features of the RGB-D sensor, making the current system configuration unfeasible for outdoor purposes.
Autonoma fordon har blivit spetsen för bilindustrin i dag i sökandet efter säkrare och effektivare transportsystem. En av de viktigaste sakerna för varje autonomt fordon består i att vara medveten om sin position och närvaron av hinder längs vägen. Det aktuella projektet behandlar position och riktning samt terrängkartläggningsproblemet genom att integrera en visuell distansmätnings och kartläggningsmetod. RGB-D kameran Kinect v2 från Microsoft valdes som sensor för att samla in information från omgivningen. Den var ansluten till en Intel mini PC för realtidsbehandling. Båda komponenterna monterades på ett fyrhjuligt forskningskonceptfordon (RCV) för att testa genomförbarheten av den nuvarande lösningen i utomhusmiljöer. Robotoperativsystemet (ROS) användes som utvecklingsmiljö med C++ som programmeringsspråk. Den visuella distansmätningsstrategin bestod i en bildregistrerings-algoritm som kallas Adaptive Iterative Closest Keypoint (AICK) baserat på Iterative Closest Point (ICP) med hjälp av Oriented FAST och Rotated BRIEF (ORB) som nyckelpunktsutvinning från bilder. En rutnätsbaserad lokalkostnadskarta av rullande-fönster-typ implementerades för att få en tvådimensionell representation av de hinder som befinner sig nära fordonet inom ett fördefinierat område, i syfte att möjliggöra ytterligare applikationer för körvägen. Experiment utfördes både offline och i realtid för att testa systemet i inomhus- och utomhusscenarier. Resultaten bekräftade möjligheten att använda den utvecklade metoden för att spåra position och riktning av kameran samt upptäcka föremål i inomhusmiljöer. Men utomhus visades begränsningar i RGB-D-sensorn som gör att den aktuella systemkonfigurationen är värdelös för utomhusbruk.
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Kawale, Sujay J. "Implication of Terrain Topology Modelling on Ground Vehicle Reliability." Thesis, Virginia Tech, 2010. http://hdl.handle.net/10919/31241.

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The accuracy of computer-based ground vehicle durability and ride quality simulations depends on accurate representation of road surface topology as an excitation to vehicle dynamics simulation software, since most of the excitation input to a vehicle as it traverses terrain is provided by the surface topology. It is not computationally efficient to utilise physically measured terrain topology for these simulations since extremely large data sets would be required to represent terrain of all desired types. Moreover, performing repeated simulations on the same set of measured data would not provide a random character typical of real world usage. There exist several methods of synthesising terrain data through the use of stochastic or mathematical models in order to capture such physical properties of measured terrain as roughness, bank angle and grade. In first part of this work, the autoregressive model and the Markov chain model have been applied to generate synthetic two-dimensional terrain profiles. The synthesised terrain profiles generated are expected to capture the statistical properties of the measured data. A methodology is then proposed; to assess the performance of these models of terrain in capturing the statistical properties of the measured terrain. This is done through the application of several statistical property tests to the measured and synthesized terrain profiles. The second part of this work describes the procedure that has been followed to assess the performance of these models in capturing the vehicle component fatigue-inducing characteristics of the measured terrain, by predicting suspension component fatigue life based on the loading conditions obtained from the measured terrain and the corresponding synthesized terrain. The terrain model assessment methodology presented in this work can be applied to any model of terrain, serving to identify which terrain models are suited to which type of terrain.
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Smail, Robert A. "Wisconsin all terrain vehicle owners : recreational motivations and attitudes toward regulation /." Link to full text, 2007. http://epapers.uwsp.edu/thesis/2007/Smail.pdf.

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Books on the topic "Terrain vehicle"

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Wang, Shifeng. Road Terrain Classification Technology for Autonomous Vehicle. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6155-5.

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Smith, Jay H. The most rugged all-terrain vehicles. Minneapolis, Minn: Capstone Press, 1995.

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Wells, Charles Arthur. Atv trails guide Arizona, Phoenix Region. Monument, CO: FunTreks, Inc, 2008.

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Guide to Moab, UT backroads & 4-wheel drive trails. Colorado Springs, CO: FunTreks, Inc., 2000.

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Guide to Arizona backroads & 4-wheel drive trails: Easy, moderate, difficult backcountry driving adventures. Colorado Springs, CO: FunTreks, 2001.

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Wells, Charles A. ATV trails guide: Colorado : Silverton, Ouray, Lake City, Telluride. Monument, Colo: FunTreks, Inc., 2009.

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Guide to Moab, UT backroads & 4-wheel drive trails. 2nd ed. Colorado Springs, CO: FunTreks, 2008.

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Wells, Charles A. Guide to Colorado backroads & 4-wheel drive trails, vol. 2. Colorado Springs, Colo: FunTreks, Inc., 1999.

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Wells, Charles A. Guide to Colorado backroads & 4-wheel drive trails. Colorado Springs, Colo: FunTreks, Inc., 1998.

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Wells, Charles A. Guide to Southern California backroads & 4-wheel drive trails. Colorado Springs, CO: FunTreks, 2003.

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Book chapters on the topic "Terrain vehicle"

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Hossain, Mohammad Quazi Raaheeb, Mehdi Azim, Tadib Chowdhury, Abhijit Saha Prince, Mashfique Ahmed, and Md Nasfikur R. Khan. "Six Wheeled All Terrain Multipurpose Vehicle." In Learning and Analytics in Intelligent Systems, 104–10. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42363-6_12.

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Hirose, Shigeo, Jun Miyake, and Sanehito Aoki. "Terrain Adaptive Tracked Vehicle HELIOS-I." In Advanced Robotics: 1989, 676–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-83957-3_46.

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Wang, Shifeng. "Acceleration-Based Road Terrain Classification." In Road Terrain Classification Technology for Autonomous Vehicle, 21–53. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6155-5_3.

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Wang, Shifeng. "Image-Based Road Terrain Classification." In Road Terrain Classification Technology for Autonomous Vehicle, 55–68. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6155-5_4.

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Wang, Shifeng. "LRF-Based Road Terrain Classification." In Road Terrain Classification Technology for Autonomous Vehicle, 69–78. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6155-5_5.

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Wang, Shifeng. "Multiple-Sensor Based Road Terrain Classification." In Road Terrain Classification Technology for Autonomous Vehicle, 79–93. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6155-5_6.

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Christou, N., K. Parthenis, B. Dimitriadis, and N. Gouvianakis. "Digital models for autonomous vehicle terrain — following." In Robotic Systems, 407–13. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2526-0_47.

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Rollins, Mark. "Creating an All-Terrain LEGO Technic Vehicle." In Practical LEGO Technics, 81–116. Berkeley, CA: Apress, 2013. http://dx.doi.org/10.1007/978-1-4302-4612-1_5.

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Economou, J. T., D. J. Purdy, D. Galvão Wall, D. Diskett, and D. Simner. "Intelligent based terrain preview controller for a 3-axle vehicle." In Advanced Vehicle Control AVEC’16, 445–50. CRC Press/Balkema, P.O. Box 11320, 2301 EH Leiden, The Netherlands, e-mail: Pub.NL@taylorandfrancis.com, www.crcpress.com – www.taylorandfrancis.com: Crc Press, 2016. http://dx.doi.org/10.1201/9781315265285-71.

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Wang, Shifeng. "Introduction." In Road Terrain Classification Technology for Autonomous Vehicle, 1–5. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6155-5_1.

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Conference papers on the topic "Terrain vehicle"

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DuPont, Edmond M., Rodney G. Roberts, Majura F. Selekwa, Carl A. Moore, and Emmanual G. Collins. "Online Terrain Classification for Mobile Robots." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-81659.

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Today’s autonomous vehicles operate in an increasingly general set of circumstances. In particular, unmanned ground vehicles (UGV’s) must be able to travel on whatever terrain the mission offers, including sand, mud, or even snow. These terrains can affect the performance and controllability of the vehicle. Like a human driver who feels his vehicle’s response to the terrain and takes appropriate steps to compensate, a UGV that can autonomously perceive its terrain can also make necessary changes to its control strategy. This article focuses on the development and application of a terrain detection algorithm based on terrain induced vehicle vibration. The dominant vibration frequencies are extracted and used by a probabilistic neural network to identify the terrain. Experimental results based on iRobot’s ATRV Jr (Fig. 1) demonstrate that the algorithm is able to identify with high accuracy multi-differentiated terrains broadly classified as sand, grass, asphalt, and gravel.
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Barthlow, Dakota, Vijitashwa Pandey, David Gorsich, and Paramsothy Jayakumar. "Off-Road Vehicle Path Planning Using Geodesics on a Multifactor Terrain Model." In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22609.

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Abstract Optimal navigation of wheeled or tracked vehicles through a particular off-road terrain is primarily governed by terrain properties, and the capabilities of the vehicle itself. Reconciling vehicle operation with a terrain’s trafficability, termed mobility mapping, is a complex and multi-faceted problem that involves geophysics, vehicle dynamics, optimization, meta-modeling, and statistical modeling. A mobility map in turn informs path planning, which is the process of creating optimal routes through the trafficable areas to successfully arrive at a destination. This optimality can be in the sense of the length of the path taken, energy consumption, or any other metric that the operator considers important. This paper presents a procedure that first models the terrain by including factors affecting trafficability, uses a kriging interpolator for terrain modeling, then utilizes an existing path planning algorithm to create a rough path between start and goal points. Subsequently, a differential geometry based algorithm is presented to optimize the path. In the proposed method, the height of the terrain is augmented with multiple factors beneficial or detrimental to mobility to define a composite surface, thereby simultaneously considering them in path planning. A geodesic connecting the start and goal points is then found on this composite surface. We present examples on terrains acquired from geospatial data gateway of the United States Geological Survey, showing the efficacy of the method. Comparisons with an existing approach are made and avenues for future work are also identified.
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Akcabay, Deniz T., N. C. Perkins, and Zheng-Dong Ma. "Predicting the Mobility of Tracked Robotic Vehicles." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-60877.

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Robotic vehicles are an attractive alternative to manned vehicles in hazardous or dangerous off road and urban environments. Present designs of robot vehicles employ wheels or tracks as the running gears and, in general, tracks provide superior mobility on rough or uneven terrain. This paper presents a multibody dynamics model of a tracked robotic vehicle for the purpose of predicting mobility in two different scenarios: 1) steep terrains, and 2) urban terrains in the form of staircases. In both scenarios we study the physical limitations on vehicle mobility imposed by key vehicle design variables and vehicle operating conditions. Example vehicle design variables include the location of the mass center, grouser penetration, and track/terrain friction. Example vehicle operating conditions include climbing under full versus partial track/terrain contact, and climbing on straight versus switch back courses.
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Sreenivasan, S. V., and P. Nanua. "Kinematic Geometry of Wheeled Vehicle Systems." In ASME 1996 Design Engineering Technical Conferences and Computers in Engineering Conference. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/96-detc/mech-1137.

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Abstract This paper addresses instantaneous motion characteristics of wheeled vehicles systems on even and uneven terrain. A thorough kinematic geometric approach which utilizes screw system theory is used to investigate vehicle-terrain combinations as spatial mechanisms that possess multiple closed kinematic chains. It is shown that if the vehicle-terrain combination satisfies certain geometric conditions, for instance when the vehicle operates on even terrain, the system becomes singular or non-Kutzbachian — it possesses finite range mobility that is different from the one obtained using Kutzbach criterion. An application of this geometric approach to the study of rate kinematics of various classes of wheeled vehicles is also included. This approach provides an integrated framework to study the kinematic effects of varying the vehicle and/or terrain geometric parameters from their nominal values. In addition, design enhancements of existing vehicles are suggested using this approach. This kinematic study is closely related to the force distribution characteristics of wheeled vehicles which is the subject of the companion paper [SN96].
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Larson, A. C., R. M. Voyles, and G. K. Demir. "Terrain classification through weakly-structured vehicle/terrain interaction." In IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004. IEEE, 2004. http://dx.doi.org/10.1109/robot.2004.1307154.

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Wasfy, Tamer M., Hatem M. Wasfy, and Jeanne M. Peters. "High-Fidelity Multibody Dynamics Vehicle Model Coupled With a Cohesive Soil Discrete Element Model for Predicting Vehicle Mobility." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47134.

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Multibody dynamics and the discrete element method (DEM) are integrated into one solver for predicting the mobility characteristics (including the no-go condition, maximum speed, and required engine torque/power) of ground vehicles on rough off-road soft soil (such as mud and snow) terrains. High fidelity multibody dynamics models are used for the various vehicle systems including: suspension system, wheels, steering system, axle, differential, and engine. A penalty technique is used to impose joint and normal contact constraints. An asperity-based friction model is used to model joint and contact friction. A DEM model of the soil with a cohesive soft soil material model is used. The material model can account for the soil compressibility, plasticity, fracture, friction, viscosity, gain in cohesive strength due to compression, and loss in cohesive strength due to tension. The governing equations of motion are solved along with joint/constraint equations using a time-accurate explicit solution procedure. The model can be used to predict the mobility of ground vehicles as a function of soil type, terrain long slope, and terrain side slope. Typical simulations of a Humvee-type vehicle are provided to demonstrate the model.
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Cortner, Alex, James M. Conrad, and Nabila A. BouSaba. "Autonomous all-terrain vehicle steering." In SOUTHEASTCON 2012. IEEE, 2012. http://dx.doi.org/10.1109/secon.2012.6196932.

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Gulden, Florian, and Metin Seyrek. "M.A.T.V - Mars All Terrain Vehicle." In International Conference On Environmental Systems. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2003. http://dx.doi.org/10.4271/2003-01-2433.

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Jones, Jack A., and Ralph D. Lorenz. "Titan aerover all-terrain vehicle." In SPACE TECHNOLOGY AND APPLICATIONS INTERNATIONAL FORUM- STAIF 2002. AIP, 2002. http://dx.doi.org/10.1063/1.1449784.

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Sun, T. C., K. Alyass, Jinfeng Wei, D. Gorsich, M. Chaika, and J. Ferris. "Time Series Modeling of Terrain Profiles." In 2005 SAE Commercial Vehicle Engineering Conference. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2005. http://dx.doi.org/10.4271/2005-01-3561.

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Reports on the topic "Terrain vehicle"

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Hodgdon, Taylor, Anthony Fuentes, Jason Olivier, Brian Quinn, and Sally Shoop. Automated terrain classification for vehicle mobility in off-road conditions. Engineer Research and Development Center (U.S.), April 2021. http://dx.doi.org/10.21079/11681/40219.

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The U.S. Army is increasingly interested in autonomous vehicle operations, including off-road autonomous ground maneuver. Unlike on-road, off-road terrain can vary drastically, especially with the effects of seasonality. As such, vehicles operating in off-road environments need to be in-formed about the changing terrain prior to departure or en route for successful maneuver to the mission end point. The purpose of this report is to assess machine learning algorithms used on various remotely sensed datasets to see which combinations are useful for identifying different terrain. The study collected data from several types of winter conditions by using both active and passive, satellite and vehicle-based sensor platforms and both supervised and unsupervised machine learning algorithms. To classify specific terrain types, supervised algorithms must be used in tandem with large training datasets, which are time consuming to create. However, unsupervised segmentation algorithms can be used to help label the training data. More work is required gathering training data to include a wider variety of terrain types. While classification is a good first step, more detailed information about the terrain properties will be needed for off-road autonomy.
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Rushing, John, and Daniel Harder. Improved vehicle mobility by using terrain surfacing systems. Engineer Research and Development Center (U.S.), April 2020. http://dx.doi.org/10.21079/11681/36357.

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Creighton, Daniel C., George B. McKinley, Randolph A. Jones, and Richard B. Ahlvin. Terrain Mechanics and Modeling Research Program: Enhanced Vehicle Dynamics Module. Fort Belvoir, VA: Defense Technical Information Center, May 2009. http://dx.doi.org/10.21236/ada500759.

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Rasmussen, S. J., M. W. Orr, D. Carlos, A. F. Deglopper, and B. R. Griffith. Simulating Multiple Micro-Aerial Vehicles and a Small Unmanned Aerial Vehicle in Urban Terrain Using MultiUAV2. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada446221.

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Shneier, Michael, Tsai Hong, Tommy Chang, Harry Scott, Steve Legowik, Gerry Cheok, Chuck Giauque, David Gilsinn, and Christopher Witzgall. Terrain characterization for TRL-6 evaluation of an unmanned ground vehicle. Gaithersburg, MD: National Institute of Standards and Technology, 2004. http://dx.doi.org/10.6028/nist.ir.7186.

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Sakamoto, Moriyuki, Eiichi Yagi, Tetsuya Kubota, Hiroshi Takata, and Takeshi Tadokoro. Analysis on Sport All-Terrain Vehicle Jumping with Multibody Dynamic Simulations. Warrendale, PA: SAE International, October 2005. http://dx.doi.org/10.4271/2005-32-0013.

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Kelly, Alonzo, Ammar Husain, and Venkat Rajagopalan. Real-Time Identification of Wheel Terrain Interaction Models for Enhanced Autonomous Vehicle Mobility. Fort Belvoir, VA: Defense Technical Information Center, April 2014. http://dx.doi.org/10.21236/ada617349.

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Reid, Alexander. Compaction-Based Deformable Terrain Model as an Interface for Real-Time Vehicle Dynamics Simulations. Fort Belvoir, VA: Defense Technical Information Center, April 2013. http://dx.doi.org/10.21236/ada573959.

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Bodie, Mark, Michael Parker, Alexander Stott, and Bruce Elder. Snow-covered obstacles’ effect on vehicle mobility. Engineer Research and Development Center (U.S.), November 2020. http://dx.doi.org/10.21079/11681/38839.

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The Mobility in Complex Environments project used unmanned aerial systems (UAS) to identify obstacles and to provide path planning in forward operational locations. The UAS were equipped with remote-sensing devices, such as photogrammetry and lidar, to identify obstacles. The path-planning algorithms incorporated the detected obstacles to then identify the fastest and safest vehicle routes. Future algorithms should incorporate vehicle characteristics as each type of vehicle will perform differently over a given obstacle, resulting in distinctive optimal paths. This study explored the effect of snow-covered obstacles on dynamic vehicle response. Vehicle tests used an instrumented HMMWV (high mobility multipurpose wheeled vehicle) driven over obstacles with and without snow cover. Tests showed a 45% reduction in normal force variation and a 43% reduction in body acceleration associated with a 14.5 cm snow cover. To predict vehicle body acceleration and normal force response, we developed two quarter-car models: rigid terrain and deformable snow terrain quarter-car models. The simple quarter models provided reasonable agreement with the vehicle test data. We also used the models to analyze the effects of vehicle parameters, such as ground pressure, to understand the effect of snow cover on vehicle response.
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Affleck, Rosa T. Disturbance Measurements From Off-Road Vehicles on Seasonal Terrain. Fort Belvoir, VA: Defense Technical Information Center, July 2005. http://dx.doi.org/10.21236/ada464712.

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