Journal of Terramechanics最新文献

Traversing soft terrain poses a major challenge for planetary wheeled rovers, and various studies have demonstrated ways to enhance rover mobility by transforming the wheel structure or adjusting the wheel’s stiffness, which results in a change in wheel contact area on the terrain. This paper presents a novel idea using the jamming mechanism for modulating the wheel’s stiffness. The developed wheel consists of the core body, wheel outer rim, inner flexure, and cable tension mechanism. The jamming mechanism is realized by adjusting the cable tension inserted between the outer rim of the wheel. The wheel stiffness measuement test confirms that the wheel with low stiffness can reduce its stiffness for 75% of the high stiffness configuration. The wheel’s traversability on soft terrain are also evaluated based on slip ratio and current consumption. The results demonstrate that the lower-stiffness configuration outperforms the higher-stiffness wheel under various conditions. These findings, being consistent with previous works on flexible wheels, highlight the potential benefits of the jamming-based stiffness-adjustable wheel for rough terrain traverse with various payload conditions.

Estimating the mechanical properties of snow from imagery is an essential part of over-snow vehicle autonomy. However, snow surfaces that differ widely in strength, traction, and motion resistance tend to appear a uniform bright white in visible or broadband infrared imagery, and it is difficult to determine where an oversnow vehicle should operate from imagery alone. In this work we determine the optimal fusion of filtered broadband shortwave infrared (SWIR) imagery to separate snow types with different mechanical properties by appearance. We demonstrate vastly increased discrimination skill in distinguishing snow types using a small number of SWIR cameras in both field and laboratory settings, and also identify sources of environmental context that can improve lookahead sensing for oversnow vehicles. Overall, we show that a small set of inexpensive SWIR filters is a powerful tool for over-snow autonomy and motion planning.

Wheeled mobile robots, rovers, are highly effective in lunar exploration. However, the lunar regolith can cause wheel slippage, resulting in an inability to travel for the rover. A single-wheel testbed is usually used to analyze a rover wheel’s driving performance. Our experiment can control the rotation and translation of the wheels separately, realizing experiments in any slippage condition. Moreover, this testbed can conduct experiments using regolith simulant with a cohesive property, in addition to Toyoura sand, which is non-cohesive sand collected from the earth.

This paper presents the results of a driving test on two types of loose soil: Toyoura sand and regolith simulant (FJS-1). The wheel used in the experiment is the preliminary version of the actual flight model of a 10 kg class lunar exploration microrover. The results reveal that the traction performance on both sands improves as the slip ratio increases. The performance did not depend on velocity but on vertical load. It should be noted that the cohesive simulant shows a higher difference in traction performance than Toyoura sand. These findings, measured in detail from the low-slip to the high-slip range, contribute to the actual driving operation of the rover missions.

Traction and ground pressure are key aspects of modern off-highway machinery. On the one hand, the machinery must be able to move successfully on rough terrain, on the other hand, the soil cannot be excessively ruined, particularly in agriculture fields that must be as productive as possible. In this regard, when the soil is very sensitive to ground pressure and slip efficiency, tracks are often mounted on agricultural tractors rather than wheels. Regrettably, it significantly diminishes the multi-purpose functionality of modern agricultural tractors, which is an essential feature. To offer higher pulling efficiency, reduced ground pressure, and greater multi-purpose functionality, an agricultural tractor fitted with a rear bogie axle is hereby presented. A market analysis is carried out to demonstrate the potential of such a vehicle. Subsequently, an ideal agricultural tractor is proposed for benchmarking purposes and as the baseline for designing the bogie axle application. Their pulling performance is evaluated by using a custom-made spreadsheet, while a novel coefficient named Pull on Pressure is introduced to assess off-road mobility. Ultimately, the two variations of the agricultural tractors undergo testing on vehicle dynamics simulation software to conduct an initial comparative analysis.

This paper presents a novel parameter identification method for DEM-FEM coupling model to investigate the trafficability of off-road tires on granular soils. Initially, an experimental device is developed to measure the bulk responses of granular materials i.e., angles of repose and shear. A series of numerical tests, including the Plackett-Burman tests, steepest-climbing tests and three-factor orthogonal tests, are then performed to formulate the mathematical regression and constraint equations. These equations establish the correlation between the three key model input parameters (namely, coefficients of static friction of acrylic wall-particle and particles, and coefficient of restitution of acrylic wall-particle) and the aforementioned bulk responses. After that, the non-dominated sorting genetic algorithm II (NSGA-II) is implemented to iteratively calculate the equations based on the multi-objective optimization method to obtain the optimal solution set. Finally, the effectiveness and feasibility of the parameter identification method are confirmed by comparing the results of indoor soil-bin tests and the corresponding numerical simulations in terms of tire sinkage, ruts and soil deformation and flow.