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      • Elements of Planetary Rover Design
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      • 0274 / Deep learning method for IMU-based tracking of Martian rover
      • 0448 / Lunar rover discrete element method study and calibration
      • 0709 / Proposal of swarm rovers’ collaborative locomotion with expansion and contraction...
      • 0889 / Skidding suppression method using “discrete 4-wheel-drive typed rover” considering...
      • 1098 / Simulation of change in supporting force when imparting vibration by distinct element method
      • 1453 / Suppressing the reduction of the traveling displacement on loose soil for rovers with...
      • 1522 / Tractive performance of rigid wheel in granular media using coarse-scale DEM models
      • 1638 / Analysis of tire characteristics on road surface with volcanic ash fall
      • 1805 / Accelerating graph networks for real-time physics simulations
      • 2145 / Obstacle performance and wheel failure test analysis of Zhurong rover
      • 2177 / Effects of road wheel load, driving speed and track slip upon stress state in sandy...
      • 2437 / Improving predictive control methods on off-road vehicles with realistic steering preview...
      • 2765 / Obstacle detection vision system enabling autonomous mounding on clearcuts
      • 2801 / In Situ Soil Property Estimation for Autonomous Earthmoving Using Physics- Infused Neural...
      • 2936 / Moisture content impacts on soil load bearing capacity and its spectral behaviour
      • 3280 / Comparison of tweels and pneumatic tires on LTATV military vehicle
      • 3493 / Numerical modeling of a tire on undrained saturated clay using FEM, ALE, and SPH
      • 3507 / Determination of the tractive forces of a tractor based on the reconstruction of...
      • 3796 / The issue of assessing the suitability of own simulation models for testing off-road vehicles
      • 3797 / Disturbed and naturally recovered soil surface as a ground for subsequent vehicle mobility...
      • 3835 / Effect of steer angle rate upon tyre lateral force generation on two different soils
      • 4141 / Modeling and verification of a full-scale forestry vehicle real-time multi-physics digital tw
      • 4456 / Modeling soil-tool interaction of a cultivator sweep using DEM
      • 4595 / Evaluation and comparison of driving performance of a lunar exploration rover wheel in...
      • 4681 / Simplified models of terrain-vehicle interaction for real-time applications
      • 4816 / Effects of humidity on the emissions of the diesel engines
      • 5552 / Vehicle drawbar test method with improved measurement and control
      • 6027 / Digital precision planning tool for autonomous forest regeneration of mixed tree species
      • 6630 / Real-time measurement of tire sinkage using stereo cameras
      • 6690 / Comparative evaluation of methods to evaluate penetration resistance for Clegg hammer and...
      • 6736 / Ride comfort comparison between 4-poster and straight line driving simulations
      • 6861 / Research on airplane performance on a grass airfield
      • 7198 / Analysis of aircraft dynamics while overcoming obstacles on a grass runway
      • 7477 / Evaluating the pressure performance of DPF filters using engine bench analysis
      • 7523 / Assessing performance of light wheeled vehicles on GRC-1 using 3D scanned footprint...
      • 7577 / Implementation of moving loads on ice in NRMM
      • 8151 / Study on estimation of traveling states using strain information on chassis of lunar and ...
      • 8254 / Initial steps towards characterization of a new military cold weather all-terrain vehicle...
      • 8672 / Trajectory optimization for vegetation override in off-road driving
      • 9268 / Experiments of sinkage characters of wire mesh wheel under different slip ratio
      • 9992 / Soil shear strength values obtained from its colour
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  2. Preconference Professional Short Course

Elements of Planetary Rover Design

Innovative Solutions for Optimal Traction on Extraterrestrial Bodies

2 // Elements of Planetary Rover Design: Innovative Solutions for Optimal Traction on Extraterrestrial Bodies | 11.45 – 13.15 Lutz Richter, SoftServe, Inc., Munich, Germany

This talk outlines key topics in sizing and design of mobility systems for rovers for the Moon and other planets, in particular from the point of view of terramechanics. The overall discipline of planetary surface robotics involves a mix of technology domains, being i) mechatronics (electro-mechanical systems), ii) soil-machine interaction (the science of terramechanics), and iii) autonomy, the latter due to the lack of broadband, real-time remote control of planetary robots from Earth. Full description.

We are currently witnessing a surge of new rover missions, primarily because of commercial actors that now are developing rovers for technology demonstrations and science on the Moon and that range in mass between ~1 kg to ~50 kg. NASA at the same time is developing its first lunar rover since the APOLLO LRV, being the ~430 kg VIPER vehicle. China has been the only nation to have successfully landed and operated rovers on the Moon in the modern spaceflight era, having been the ~140 kg YUTU rovers on CHANG#E 3 and 4. On Mars, successful rover missions have been continuing over the last >20 years, including the Chinese ZHURONG rover and NASA’s PERSEVERANCE geoscience and sample caching rover (being part of Mars Sample Return).

A variety of performance metrics apply to the sizing of lunar and planetary rovers, mandating sound predictive models of the vehicle interaction with the terrain during the design phase. This begins with an assessment of the type of running gear (wheels, legs, tracks) and the type of suspension for handling geometric obstacles and to equalize load imposed on the terrain. Related trade-offs nowadays are performed primarily via simulations but in the past much relied on testing of prototypes.

Historically, the principles of terrestrial terramechanics have already been successfully applied to planetary rover sizing and development, most notably semi-empirical “Bekker-type” models that provided the basis for the NASA Apollo Lunar Roving Vehicle (LRV) predictive model for traction and drawbar pull which correlated extremely well with measured energy consumption during the missions. The Russian approach for the LUNOKHOD rovers on the other hand has been based more on tests on Earth, building up a database subsequently used for mission predictions, likewise correlating very well with mission data on gradeability and gross pull vs. slip. For the US Mars rovers of today, different approaches were used, most recently coupling of a multibody simulation model of the vehicles with a semi-empirical wheel-soil interaction model, very well reproducing mission data in terms of wheel motor currents and wheel sinkage. In China, semi-empirical models validated by single wheel tests were applied to the design of the wheels for the YUTU lunar rovers and the ZHURONG rover of China’s first Mars mission TIANWEN-1. In Europe, both semi-empirical and analytical models have been developed in support of various planetary rover projects, most notably the ExoMars mission. The semi-empirical model (TPM) for the ExoMars metallic flexible wheel correlates well with single wheel tests on Mars soil simulants.

In general, correlation of planetary rover mobility models with mission data is difficult to achieve, not because the models are peculiar or unusual but because instrumentation on the spaceflight systems is too rudimentary for a comprehensive model validation, due to difficulties in qualifying the required sensors (such as load cells and torque sensors) for the space environment (radiation, vacuum, temperature ranges).

A particular challenge in rover mobility system development is mobility testing at Earth gravity, as the difference in gravity not only modifies vehicle weight but also the properties of the terrain that is traversed.

New trends in planetary rovers are aimed at improving autonomy and operational robustness, to minimize chances of immobilization in weak terrain. Countermeasures now part of modern rover concepts and designs include active or “hybrid” suspensions, real-time slip estimation for the wheels, and on-board torque / slip control (pioneered on the NASA CURIOSITY Mars rover for protecting the life of its wheels). In the future, torque and slip control can also be aided via appropriate sensors that may be embedded inside the wheels. Another recent improvement is the implementation of real-rime stereo vision for faster recognition of geometric obstacles – while driving – and thus faster overall traverses, as demonstrated on the NASA PERSEVERANCE Mars rover.

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