Estimation Method Of Monthly Soil Hardness Based On Lunar Rover Rut Image

In the exploration of the planet,the rover needs to carry a variety of payload is order to achieve a variety parameters of the unknown environment detection.In the moon and Mars exploration,soil hardness values are one of the key parameters to be tested.At present,the common method of soil hardness measurement is contact-type,through the hardness tester and other equipment for contact measurement.Aiming at the Chang'e lunar exploration project which is currently being carried out,the method of simulating lunar soil hardness based on rut image is presented in this paper,which is a non-contact measurement method based on machine vision.The method is mainly by measuring the rut sink depth to estimate simulated lunar hardness.The system energy consumption is reduced and the other payloads are increased for this program.Firstly,the calibration method of binocular vision system and the rutting pre-processing algorithm are studied.The measurement process of rutting depth based on binocular vision is discussed.The binocular vision image matching algorithm and3 D reconstruction algorithm are studied and realized,and through experimental verification.Secondly,the lunar soil hardness test platform was constructed.This platform has two parts: software and hardware.the image processing process is realized by software part through VS2013,and the experimental data analyzed is realized by MATLAB.The simulated lunar rover,the binocular camera platform,the soil hardness instruments and the prepare tool have formed the hardware part,which is verified the algorithm's realization in the lunar environment.The method of estimating the hardness of simulated lunar soil under different conditions is discussed and the empirical formula is given.Finally,the simulation rut image on ground and the "Moon Rabbit" rut image are respectively calculated by pre-processing and 3D reconstruction,and put them into the corresponding soil empirical formula to calculate.The experimental results has proved the proposed scheme is feasible and effective.