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1. Incipient Immobilization Detection for Lightweight Rovers Operating in Deformable Terrain

   https://doi.org/10.1115/1.4056408  

   Lines, Austin; Elliott, Joshua; Ray, Laura R. (December 2022, Journal of Autonomous Vehicles and Systems)

   Abstract This paper presents a new method of detecting incipient immobilization for a wheeled mobile robot operating in deformable terrain with high spatial variability. This approach uses proprioceptive sensor data from a four-wheeled, rigid chassis rover operating in poorly bonded, compressible snow to develop canonic, dynamical system models of the robot's operation. These serve as hypotheses in a multiple model estimation algorithm used to predict the robot's mobility in real-time. This prediction method eliminates the need for choosing an empirical wheel-terrain interaction model, determining terramechanics parameter values, or for collecting large training datasets needed for machine learning classification. When tested on field data, this new method warns of decreased mobility an average of 1.8 meters and 2.9 seconds before the rover is completely immobilized. This system also proves to be a reliable predictor of immobilization when evaluated in simulated scenarios of rovers with passive suspension maneuvering in more variable terrain. 

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2. Utility Truck: Morphing Boom Equipment for Terrain Mobility

   Patel, Parth Y.; Vantsevich, Vladimir V; Whitson, Jordan (October 2021, 20th International Conference and 9th Americas Conference of ISTVS 2021)

   Utility trucks with boom equipment function on environmentally sensitive areas and severe terrains where off-road conditions may cause significant damage to the trucks’ mobility and their safe operation. Indeed, considerable variations of landscape elevation and dynamic changes of terrain properties lead to extensive differences in the wheel normal reactions, drastic fluctuations of the rolling resistance at each tire, and finally, substantial changes in the total resistance to motion, which includes both the tire rolling resistance and the resistance due to the truck gravity component. Additionally, lateral forces caused by truck inclinations can lead to instability in motion, too. As a result, a utility truck can become immobilized in either longitudinal or lateral direction of movement because of one or the combination of the following events – loss of longitudinal mobility due to extensive tire slippage at some/all wheels, loss of lateral mobility due to tire side skid or rollover of the truck. To eliminate the above-listed causes that can lead to the utility truck immobilization, this study suggests a novel approach to managing the input/output factors that influence both longitudinal and lateral forces of the utility truck. In fact, the 3D morphing of the boom equipment is proposed as the input factor for managing the wheel normal reactions as the outputs. Ultimately, a changeable positioning of the boom equipment relative to the truck frame results in variable wheel normal reactions, which are the main contributors to the normal tire deformation and soil compaction, and thus, to the rolling resistance of each and all tires. This paper presents and discusses the method and results of computational simulations of the F450-based utility truck with boom equipment on medium mineral soil. The normal reaction at each wheel is evaluated under which the boom equipment morphs safely without causing roll over of the truck and, consequently, the total resistance to the motion force is determined. Modeling and simulation of the truck were conducted with the use of terramechanics-based tire-terrain models. This research study of the rolling resistance contributes to a research project on morphing utility truck, dynamics in severe terrain conditions. Keywords: Utility Truck, Morphing, Terrain Mobility 

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3. Calibration of an expeditious terramechanics model using a higher‐fidelity model, Bayesian inference, and a virtual bevameter test

   https://doi.org/10.1002/rob.22276  

   Hu, Wei; Li, Pei; Unjhawala, Huzaifa Mustafa; Serban, Radu; Negrut, Dan (December 2023, Journal of Field Robotics)

   Abstract The soil contact model (SCM) is widely used in practice for off‐road wheeled vehicle mobility studies when simulation speed is important and highly accurate results are not a main concern. In practice, the SCM parameters are obtained via a bevameter test, which requires a complex apparatus and experimental procedure. Here, we advance the idea of running a virtual bevameter test using a high‐fidelity terramechanics simulation. The latter employs the “continuous representation model” (CRM), which regards the deformable terrain as an elasto‐plastic continuum that is spatially discretized using the smoothed particle hydrodynamics method. The approach embraced is as follows: a virtual bevameter test is run in simulation using CRM terrain to generate “ground truth” data; in a Bayesian framework, this data is subsequently used to calibrate the SCM terrain. We show that (i) the resulting SCM terrain, while leading to fast terramechanics simulations, serves as a good proxy for the more complex CRM terrain; and (ii) the SCM‐over‐CRM simulation speedup is roughly one order of magnitude. These conclusions are reached in conjunction with two tests: a single wheel test, and a full rover simulation. The SCM and CRM simulations are run in the open‐source software Chrono. The calibration is performed using PyMC, which is a Python package that interactively communicates with Chrono to calibrate SCM. The models and scripts used in this contribution are available as open source for unfettered use and distribution in a public repository. 

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4. MOBILITY MODES AND CONTROL OF A PASSIVELY-ARTICULATED MULTI-SEGMENT WHEELED VEHICLE

   Elliot, Joshua; Lines, Austin; Ray, Laura (October 2021, Proceedings of the ISTVS 20th International and 9th Americas Conference)

   This paper presents mobility modes and control methods for the SnoWorm, a passively-articulated multi-segment autonomous wheeled vehicle concept for use in Earth’s polar regions. SnoWorm is based on FrostyBoy, a four-wheeled GPS guided rover built for autonomous surveys across ice sheets. Data collected from FrostyBoy were used to ground-truth a ROS/Gazebo model of vehicle-terrain interaction for simulations on snow surfaces. The first mobility mode, inchworm movement, uses active prismatic joints that link the SnoWorm’s segments, and allow them to push and pull one another. This pushing and pulling of individual segments can be coordinated to allow forward motion through terrain that would immobilize a single-segment vehicle. The second mobility mode utilizes fixed links between SnoWorm’s segments and uses the tension or compression measured in these links as a variable to control wheel speeds and achieve a targeted force distributions within the multi-segment vehicle. This ability to control force distribution can be used to distribute a towed load evenly across the entire SnoWorm. Alternatively, the proportion of the load carried by individual segments can be increased or decreased as needed based on each segment’s available drawbar pull or wheel slip. 

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5. 4x4 Hybrid Electric Vehicle vs. Fully Electric Vehicle Mobility in Drastically Changing Terrain Conditions

   Jesse Paldan, Vladimir Vantsevich (July 2020, Proceedings of the 3rd International Conference of IFToMM Italy)

   null (Ed.)

   Active driveline technologies allow vehicles to dynamically control power distribution among driving wheels to improve vehicle operational parameters that impact terrain mobility. Two 4x4 electrified drivelines are compared which provide a variable power split: a hybrid electric vehicle with a controllable power transmitting unit and a fully electric vehicle (FEV) with individual electric wheel drives. The individual e-drives have the potential to improve mobility when the left and right wheel terrain conditions are drastically different. 

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