Research On Passing Ability Of Autonomous Prospecting Vehicle Based On Binocular Vision

Autonomous prospecting equipment plays a very important role in exploration work. Atthe same time, autonomous prospecting vehicle comes into being. Binocular stereo visiontechnology is one of common environment perception technology. It is widely used inintelligent driving, precision measurement, spatial exploration and other fields.This paper uses binocular stereo vision technology to perceive driving environment ofautonomous prospecting vehicle. It introduces binocular stereo vision principle and relatedtechnologies in detail, including binocular system calibration, image pre-processing, stereomatching and three-dimensional information recovery. Then some experiments arecompleted to show the feasibility of using this technology to perceive driving environment.Then it uses the three-dimensional data to establish a digital terrain map of drivingenvironment. According to the neighborhood analysis method, the terrain slope, ruggednessand other factors are extracted. Besides, terrain passing measurement is put forward toevaluate the ease of traffic capacity. According to road roughness curve, the passing area isdivided into step road, slope road and smooth road. Then the smooth road is also divided intothree levels by road roughness coefficient. Through the irregular road grading, it gives someguidance for the subsequent research.This paper also analyzes climbing obstacle model and climbing obstacle stability modelto get the vehicle climbing limit size. According to vibration requirements of prospectingvehicle and prospecting equipment in the process of moving, the seven degrees of freedomvehicle vibration model is analyzed. Then corresponding passing control strategy is putforward by the requirements of passing ability and ride comfort.Finally, one mine vehicle is selected to carry out simulation analysis. This paper usesMatlAB/Simulink software to build vehicle model and off-road model. It verifies thecorrectness of these models by comparing simulation results with other documents. Then ituses the off-road data as input to simulate analysis in order to get the limit driving speed at all levels of the road. Finally, it uses binocular stereo camera to take some roads with a step,slope and smooth pavement. These scenes’ three-dimensional information are restored andanalyzed to evaluate the passing ability. As can be seen, the recovered scene point cloudimages and digital elevation models are accurate. They can reflect the reality of the scene.From the terrain passing measurement map, we can see that smooth area’s passingmeasurement is large. It shows the passing ability is high. However, the large bumps or thesteep slope area’s passing measurement is relatively small. So these areas are hard to pass.Then it uses the limit driving speed to simulate the three scenes. According to the simulationresult, for the smooth off-road, the vehicle’s centroid acceleration rms is0.24m/s2. For thestep road and the slope road, the vehicle’s centroid maximum vertical acceleration is2.26m/s2and2.32m/s2. They all meet the requirements. This shows the limit driving speed ofautonomous prospecting vehicle has a certain significance to its trafficability at all levels ofthe road. It also shows that using binocular stereo vision technology to perceive drivingenvironment and give anticipation to the passing ability are feasible.Research ideas in this paper can provide a reference for the following study on thepassing ability of autonomous prospecting vehicle. It also has a certain engineeringsignificance.