Prediction of Mechanical Soil Properties Based on Experimental and Computational Model of a Rocker Bogie Rover
TL;DR: In this article, a model of a six-wheeled rocker bogie rover was fabricated and was made to travel on an unknown loose soil on earth, where a known reference value of revolutions per minute (RPM) was given to the direct current motors and the corresponding linear speed of the rover was measured.
Abstract: Lack of knowledge on the mechanical soil properties have resulted in large inaccuracy of the rover’s mobility prediction in the past. This paper deals with the prediction of mechanical properties of the soil based on the experimental and computational model of a six-wheeled rocker bogie rover. The work is divided into two parts. First, a physical model of the rover was fabricated and was made to travel on an unknown loose soil on earth. For this, a known reference value of revolutions per minute (RPM) was given to the direct current (DC) motors and the corresponding linear speed of the rover was measured. Next, a terramechanics based dynamics model was developed for a nominal value of the mechanical soil properties. The RPM needed to maintain the same linear speed as the experimental value was computed for the assumed mechanical soil properties. These soil properties were altered within a range such that the RPM obtained from the experimental and the computational results were similar to maintain the same linear velocity. The results were tested and validated for different RPM values for the predicted mechanical soil properties, which proved to be satisfactory.
TL;DR: In this article, the authors analyse the basic characteristics of the distribution of radial and tangential stresses on the soil-wheel interface of a towed wheel and predict the forces required to drag it along and the degree of skid.
TL;DR: The proposed wheel-and-vehicle model demonstrates better accuracy in predicting steering maneuvers as compared to the conventional kinematics-based model.
Abstract: This paper presents analytical models to investigate the steering maneuvers of planetary exploration rovers on loose soil. The models are based on wheel-soil interaction mechanics, or terramechanics, with which the traction and disturbance forces of a wheel are evaluated for various slip conditions. These traction forces are decomposed into the longitudinal and lateral directions of the wheel. The latter component, termed the side force has a major influence in characterizing the steering maneuvers of the rover. In this paper, the wheel-soil mechanics models are developed with particular attention to the side force and the validity of the model is confirmed by using a single-wheel test bed. The motion profile of the entire rover is numerically evaluated by incorporating the wheel-soil models into an articulated multibody model that describes the motion dynamics of the vehicle’s body and chassis. Steering maneuvers are investigated under different steering angles by using a four-wheel rover test bed on simulated lunar soil regolith simulant. The experimental results are compared with the simulation results using the corresponding model parameters. The proposed wheel-and-vehicle model demonstrates better accuracy in predicting steering maneuvers as compared to the conventional kinematics-based model. ©
TL;DR: A simplified, closed-form version of the basic mechanics of a driven rigid wheel on low-cohesion deformable terrain is presented, which allows the formulation of an on-line terrain parameter estimation algorithm, which has important applications for planetary exploration rovers.
••17 Jul 2002
TL;DR: In this paper, a framework for terrain characterization and identification is briefly described, composed of 1) vision-based classification of upcoming terrain, 2) terrain parameter identification via wheel-terrain interaction analysis, and 3) terrain classification based on auditory wheelterrain contact signatures.
Abstract: High-speed unmanned ground vehicles have important potential applications, including reconnaissance, material transport, and planetary exploration. During high-speed operation, it is important for a vehicle to sense changing terrain conditions, and modify its control strategies to ensure aggressive, yet safe, operation. In this paper, a framework for terrain characterization and identification is briefly described, composed of 1) vision-based classification of upcoming terrain, 2) terrain parameter identification via wheel-terrain interaction analysis, and 3) terrain classification based on auditory wheel-terrain contact signatures. The parameter identification algorithm is presented in detail. The algorithm derives from simplified forms of classical terramechanics equations. An on-line estimator is developed to allow rapid identification of critical terrain parameters. Simulation and experimental results show that the terrain estimation algorithm can accurately and efficiently identify key terrain parameters for sand.
••05 Dec 2005
TL;DR: There is good agreement between experimental and simulation results for wheel sinkage as a function of slip ratio; however, more investigation is needed to understand the differences observed for the drawbar pull and motor torque results.
Abstract: The ability to predict rover locomotion performance is critical during the design, validation and operational phases of a planetary robotic mission. Predicting locomotion performance depends on the ability to accurately characterize the wheel-soil interactions. In this research, wheel-soil interaction experiments were carried out on a single-wheel testbed and the results were compared with a single-wheel dynamic computer simulator which was developed in Matlab and Simulink's SimMechanics toolbox using a commercially-available wheel-soil interaction computer model called AESCO Soft Soil Tire Model (AS/sup 2/TM). Two different tire treads were used and compared in this study. There is good agreement between experimental and simulation results for wheel sinkage as a function of slip ratio; however, more investigation is needed to understand the differences observed for the drawbar pull and motor torque results.
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