Lunar soil strength estimation based on Chang’E-3 images

Gao, Yang; Spiteri, Conrad; Li, Chunlai; Zheng, Yongchun

doi:10.1016/j.asr.2016.07.017

Cited by 17 publications

(21 citation statements)

References 19 publications

(17 reference statements)

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“…However, the results produced are better than local methods. Local methods are simpler but only provide an approximation of the 3-D shape [28,29]. The SfS reconstruction process assumes the reflectance map is known a priori and the albedo map is homogeneous.…”

Section: Terrain Perception Onboard Planetary Roversmentioning

confidence: 99%

“…For terrestrial applications homogeneity of albedos may not always be the case due to non-linearity in natural scenes. However, surfaces on the Moon and Mars tend to have a restricted range of albedos with distinct variations that can be easily detected [28,29]. Furthermore, since the technique relies on the direction of the light source, for example the sun, this can be easily deduced from the rover’s onboard sun sensor.…”

Section: Terrain Perception Onboard Planetary Roversmentioning

confidence: 99%

“…All of these characteristics make it an ideal method for reconstructing the visual scene environment. In fact, recently this technique has been applied to high resolution images from Chang’E-3 (CE-3) lunar mission for lunar soil physical properties analysis [29] and object detection of planetary surficial rocks for autonomous navigation and mapping [28]. Figure 4 illustrates an example of a digital terrain model (DTM) generated using SfS technique.…”

Section: Terrain Perception Onboard Planetary Roversmentioning

confidence: 99%

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Towards Camera-LIDAR Fusion-Based Terrain Modelling for Planetary Surfaces: Review and Analysis

Shaukat

Blacker

Spiteri

et al. 2016

Sensors

Self Cite

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In recent decades, terrain modelling and reconstruction techniques have increased research interest in precise short and long distance autonomous navigation, localisation and mapping within field robotics. One of the most challenging applications is in relation to autonomous planetary exploration using mobile robots. Rovers deployed to explore extraterrestrial surfaces are required to perceive and model the environment with little or no intervention from the ground station. Up to date, stereopsis represents the state-of-the art method and can achieve short-distance planetary surface modelling. However, future space missions will require scene reconstruction at greater distance, fidelity and feature complexity, potentially using other sensors like Light Detection And Ranging (LIDAR). LIDAR has been extensively exploited for target detection, identification, and depth estimation in terrestrial robotics, but is still under development to become a viable technology for space robotics. This paper will first review current methods for scene reconstruction and terrain modelling using cameras in planetary robotics and LIDARs in terrestrial robotics; then we will propose camera-LIDAR fusion as a feasible technique to overcome the limitations of either of these individual sensors for planetary exploration. A comprehensive analysis will be presented to demonstrate the advantages of camera-LIDAR fusion in terms of range, fidelity, accuracy and computation.

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Section: Terrain Perception Onboard Planetary Roversmentioning

confidence: 99%

Section: Terrain Perception Onboard Planetary Roversmentioning

confidence: 99%

Section: Terrain Perception Onboard Planetary Roversmentioning

confidence: 99%

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Towards Camera-LIDAR Fusion-Based Terrain Modelling for Planetary Surfaces: Review and Analysis

Shaukat

Blacker

Spiteri

et al. 2016

Sensors

Self Cite

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“…Currently, the estimation methods of some lunar soil properties can be divided into two main categories; the first is the traditional contact measurement method [7]. In detail, the traditional method allows measurement tasks to be performed using a cone penetrometer.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, to explore lunar soil information, the rutting images collected by the vision system provide significant reference value [3]. Practically, Gao et al [7] have already used wheel sinkage to estimate the soil strength, and the method was verified with in situ soil penetrometer data from planet rovers. However, studies that have measured lunar soil hardness parameter are still relatively rare.…”

Section: Introductionmentioning

confidence: 99%

Measurement of Simulated Lunar Soil Information Using Rutting Images

Gao¹,

Zhou²,

Jiang³

et al. 2020

IEEE Access

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Research on lunar soil has great value, and soil hardness is one of the essential parameters to be measured. Currently, the existing method involves contact measurement using special instruments. To reduce the self-weight and increase the scientific payloads of lunar rovers, reanalysis of the data obtained from existing sensors provides a great solution for achieving different tasks. Therefore, a vision-based and noncontact method via rutting images is proposed to estimate soil hardness. The proposed approach generally includes two parts: rutting depth measurement and soil hardness measurement. To simulate a complex lunar environment, a variety of simulated lunar soil preparation schemes to achieve different soil states are designed in this paper. More importantly, this paper summarizes the empirical formulas of the simulated lunar soil in different states and the judgment conditions for defining the soil states based on the rutting depth. Finally, the accuracy, feasibility, and applicability of this method are verified by experiments, which demonstrate the capability of the proposed method to effectively estimate soil hardness in simulated environments, as well as in the real lunar environment.

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Improving Limitations of Rover Missions in the Moon and Planets by Unifying Vehicle–Terrain Interaction Models

Lopez-Arreguin

Montenegro

2020

Adv. Astronaut. Sci. Technol.

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This paper extends the analysis of empirical methods for describing vehicle-terrain interactions in lunar terrain. Given analytical formulation to predict mobility performance in extraterrestrial environments requires reliable in situ testing campaigns, this imposes fundamental restrictions to conceive a more consolidated theory, and further any possibility to use improved empirical methods to design better space hardware. Hence, we propose an analytical approach to extrapolate data taken in parabolic flights to model vehicle performance in multiple gravity regimes. The extrapolation technique and respective reported uncertainties can be used, therefore, to tune fitting parameters of a set of general formulas in the domain of Terramechanics, allowing to have empirical estimates of the wheel mobility in cases where testing is inherently very complex. Finally, by the analysis of previous Moon and Mars rover missions with the fitted equations, we report an empirical design criterion that allows to generate first estimates of the optimal wheel dimensions, taking into account the eventual longitudinal slip of the rover and including the desired mass of the payload. The introduced rules for geometry optimization can be important for future space rover missions in remote soils.

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Lunar soil strength estimation based on Chang’E-3 images

Cited by 17 publications

References 19 publications

Towards Camera-LIDAR Fusion-Based Terrain Modelling for Planetary Surfaces: Review and Analysis

Towards Camera-LIDAR Fusion-Based Terrain Modelling for Planetary Surfaces: Review and Analysis

Measurement of Simulated Lunar Soil Information Using Rutting Images

Improving Limitations of Rover Missions in the Moon and Planets by Unifying Vehicle–Terrain Interaction Models

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