An Investigation of Particle Image Velocimetry Techniques Applied to the Analysis of Wheel-Soil Interaction on Mars Terrain Simulant

Mobolaji Akinpelu, Dr. Carmine Senatore, Dr. Karl Iagnemma Robotic Mobility Group, Department of Mechanical Engineering, Massachusetts Institute of Technology

 Introduction In 2009, the Mars rover was on Mars and the wheel got stuck. The aim of this project is to create or modify software that will track Martian soil particle and show how the motion of the wheel affects the soil. This project simulates the motion of a wheel of the Mars Rover on a Mars soil simulant. The simulation is used to understand the forces the wheel exerts on the soil and the movement and shearing pattern of the soil particles. The overall goal of the tasks described in this poster is to investigate available PIV software for the above purpose and understand how to modify the parameters of the software, based on the cross-correlation algorithm, to give the most accurate information on the motion of the soil.

Problem Statement A sampling of common PIV software shows that they are made for particular applications like the study of fluid flow in biological and geological applications.

This project is a preliminary analysis of the:o instrumentation requirements (camera frame rate and

pixel resolution)

o software parameters (interrogation window size, degree of overlap of interrogation windows)

o physical conditions (lighting conditions and test rig

container)

and how to choose these variables so our PIV analysis gives accurate and useful data about the flow patterns in the soil.

References[1] Richard, K., and Ronald, R., 1992, "Theory of Cross-Correlation Analysis of PIV Images" Applied Scientific Research., pp. 191-215. [2] Chittiappa, M., 2006, "Particle Image Velocimetry" pp. 1-63. [3] Ronald, Adrian., and Jerry Westerweel., 2011, Particle Image Velocimetry, Cambridge University Press, Cambridge, UK, Chap. 1. 

Results A sample PIV image was rotated about its center, for one revolution, in increments of 6 degrees. This process resulted in a stack of 60 images tilted 6 degrees from the previous image .

A PIV software (matpiv) was used to process the 60 images.

The software’s accuracy was determined by comparing the value of the vectors from the software to the theoretical value of the velocity of the simulated circular motion.

After repeating the above process for the 59 vector fields produced by matpiv, the total percentage error for the x-components of velocities was found to be 0.2277 and the total percentage error for the y-components of velocities was found to be 0.2328.

 Based on these results, and the ease of use of matpiv we are comfortable with matpiv for our analysis of the motion in the test-bed.

Methods PIV images are processed by sub-dividing two consecutive images of the flow into a regular grid of sub-areas that overlap and finding the velocity vector for each sub-area by an algorithm like cross-correlation.

After a PIV analysis, the overall displacement of particles in the sub-areas is represented by a peak correlation value.

This process produces the most probable displacement vector for a particular pattern. When the process is repeated for all sub-areas of the image pair, we get a complete vector diagram of the flow studied.

AcknowledgementsI acknowledge Dr. Karl Iagnemma, Dr. Carmine Senatore and the MSRP Program for making this research possible and successful.

Sample Rotated Image

Sample Error Plot

Discussions We have begun to take a look at how the quality of our input images (image pre-processing) and the filtering tools available for each software (vector post-processing) may affect these accuracy estimates.

We are also investigating the effects of physical conditions (lighting) and instrument choice ( camera frame rate and resolution) will have on the accuracy of the vectors from our proposed experiments.

The Mars Rover

Experiments Test Bed

Sample Picture of Soil Simulant

Particle Image Velocimetry

Cross-Correlation 1

Cross-Correlation 2

Sample Image for Experiment

Sample Vector Field

Pixel Values