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This paper presents a design approach for rigid wheels operating in highly variable, deformable terrain to improve the mobility, reliability, and efficiency of an autonomous vehicle driving on snow. The longstanding Bekker-Wong theory of terramechanics is used as the basis for the design changes with the wide range of terrain parameters for snow serving as inputs to the models and bounds for the problem. Modifications to the wheel width and diameter are evaluated based on their impacts to the rover as a system, with their effects on torque and drawbar pull being weighed against the resultant modifications in component sizing, rover weight, and energy use. Other factors, not included in the Bekker-Wong models but studied in single-wheel testbed experiments, such as bulldozing resistance and the observed dynamic effects of slip-sinkage, were also considered in the design decisions for the new wheel. Finally, to test these theories and assess the mobility improvements of the new design in situ, a four-wheeled rover, FrostyBoy, was developed for the new wheels and trialed in unmodified snow. While qualitatively showing an improvement in mobility on the Greenland ice sheet, the tests also uncovered dynamic modes of immobilization, in low cohesion, low stiffness snow that are not accounted for in terramechanics theory and require further investigation for trafficability to be maintained in all snow conditions.
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Incipient Immobilization Detection for Lightweight Rovers Operating in Deformable Terrain
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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- Award ID(s):
- 1824687
- PAR ID:
- 10387711
- Date Published:
- Journal Name:
- Journal of Autonomous Vehicles and Systems
- ISSN:
- 2690-702X
- Page Range / eLocation ID:
- 1 to 23
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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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.more » « less
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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.more » « less
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Abstract The Multi-terrain Amphibious ARCtic explOrer (MAARCO) rover is an amphibious arctic rover designed to traverse arctic terrains and propel through water. The MAARCO rover consists of an ellipsoid chassis with links connecting to the propulsion system. The propulsion system consists of two helical drives made up of hollow cylinder ballasts wrapped in auger or screw shaped blades in opposing helical directions parallel to each other. In this paper, a 6 degree of freedom dynamic model of the MAARCO rover is created using Kane’s method dynamic modeling to demonstrate the dynamic model capabilities for an underwater vehicle’s performance. The hydrodynamic forces considered on the underwater rover include drag, buoyancy, flow acceleration, and added mass. In addition to the hydrodynamic forces the rover will experience gravity forces, control forces, net thrust from the helical drive blades, and net buoyancy from the helical drive ballast system. The equations of motion are developed from Kane’s method to reduce computational cost and simulated in MATLAB for different cases to gain further understanding and provide a visual representation of the system underwater and the dynamic models capabilities. The results of the simulations show the MAARCO rover behavior in the hydrodynamic environment. The results reveal that the Kane’s method dynamic modeling successfully develops equations of motion of a complicated system that can be implemented into a control system.more » « less
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Abstract The diverse and heterogeneous terrains in the Arctic, consisting of snow, melting ice, permafrost, ice-covered lakes, sea ice and open ocean, pose serious challenges to locomotion and autonomous navigation capabilities of rovers deployed in the region for data collection and experimentation. The Multi-terrain Amphibious ARCtic explOrer or MAARCO rover is a proposed screw-propelled vehicle that uses helical drives (similar to Archimedes’ screws) to move seamlessly across the diverse terrains in the Arctic. The motion of a pair of helical drives operating in soft or fluid terrain is dictated by the response of the surrounding substrate to the stresses exerted by the rotating helical drives. If the substrate under the rover does not fail when it is moving in a straight line, the linear displacement of the rover (x) and the number of rotations of the helical drives (n) are related through x = P · n, where P is the pitch length of the helical drives. However, when the substrate fails, the linear displacement of the rover is less than P · n, i.e., x < P · n. Thus, “x = P · n” motion represents the optimal mode of operation for the rover when moving in a straight line. This paper represents the first ever attempt, to the best of author’s knowledge, to derive the conditions necessary for the application of the holonomic constraint x = P · n to the dynamics of a helical drives-based rover.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1115/1.4056408
