Picking Robot Obstacle Information Detection And Obstacle Avoidance Technique Research

With the rapid development of agricultural production, the cost of agriculture labor force will become more and more costly. In recent years, the agricultural application of robot technique have already become popular issue, because of the shortage of the agriculture labor force both in developed countries and developing countries. Different from industrial robot, which works in particular environment, the agriculture robot mainly works in the natural environment, and the agriculture robot has to face more complicated and uncertain circumstance, thus there are more problems to be resolved.As a part of research on citrus picking robots, this research used binocular stereo vision to researching on recognition and location mature citrus, obstacle (branches) detection under natural environment. The main contents and methods are as follows:1. Ultrasonic range-finding sensorsTo solve the uncertain problem, this paper study and design a special Ultrasonic range-finding sensors. Using 8-bit STC12LE4052 microcontroller as the sensor, the control of data acquisition and processing unit, the design of hardware circuit ultrasonic ranging system and procedures, and distance measuring system for the location experiment, the experimental results show that the ultrasonic range-finding sensors measuring error is small, suitable for picking robot obstacle distance sensor..2. Obstacle detectionTo ensure executable of algorithms, the steps of obstacle detection are the same as that of mature fruit location. Used iterate on 2R-G-B and 2G-R-B chromatist component, combined with gray threshold method to segment image quickly and effectively. Got the branch regions by image binaryzation, morphological processing, region labeling and filling. Extracted skeleton of obstacle by thinning and did some processes so as to pruning the skeleton and recovering the occluded skeleton. Then obtained the feature points such as endpoints and branch points of the skeleton, recorded their connecting relationship. Finally the 3D information of obstacle was restored by stereo matching on feature points. Experimental results show that the identification accuracy of obstacle can reach 67.3%, the identification error ratio was increased when the actual distance of obstacle is more than 1.5m.3. Obstacle avoidance technique studyA single-query bi-directional probabilistic roadmap planner with lazy collision checking was adopted for citrus picking robot real-time path planning in dynamic and unstructured environments. Simulation of the planner was carried out in two cases of picking exposed and overlapped fruits. The effects of maximum number of milestones S, neighboring threshold, local path checking threshold and path smoother steps N on average time and success rate of planning were analyzed. When S,ρ,ε, and N were 3000, 0.6, 0.03,10 respectively, simulation results indicated that the average planning time was about 1ms for picking exposed fruits and 60 ms for picking overlapped ones, and the success rates of planning were both 100%.The simulation experiment shows that SBL-PRM is effective in the citrus picking robot real-time path planning.Through the research, some achievements have been made. Such as mature fruit recognition, match and location. This research also provides a method for fruit harvest robot to detect obstacle. The research results of this research have reference value for the study on visual recognition in the field of harvest robot in our country. They also provide a basis for further study and have important economic significance to enhance international competitive power of our country's agricultural.