Path Planning And Ripeness Detection For A Lychee Garden Based On Image Processing

This dissertation concerns path planning and ripeness detection for an autonomous robot operating in a two-dimensional environment equipped for an imaginary map.This thesis provides the robot and computer employed in it with a relatively simple method for determining paths in a Lychee garden and detecting ripe Lychee from images.This study builds up a picture guided versatile automated robotic path planning for the Lychee garden.The focal point of the research is on rapid image processing,simplest robot path planning,and remote checking and control of a robot for ripe Lychee detection.The precision of recognizing ripe Lychee fruits in regular surroundings is a notable advance for the precision process of an autonomous robot.Notwithstanding all this,low precision vigor currently limits calculations of the visual location of ripe Lychee fruits in the standard environment.The ripe Lychee fruit is identified using the computer-vision method.The Lychee regions are divided by RGB integrating chromatic red/green mapping with color space thresholding.This thesis addresses the use ideally required by a search algorithm in optimal path forecasting with its route control of an autonomous robot guidance system.The use of the BFS(Breadth-First Search)algorithm along with its route control method to decide the best way for an autonomous robot.The results of the simulation show that applying the BFS algorithm in a known framework explores the other path-based algorithms a lot quicker than heuristic.The correct identification rate was 92.8% and falsely detected 7.14%.This system for path planning was successfully tested on Open CV-Python platform,and the tests show that the task of path search and detection is accomplished with assured coordination between sensing,planning,and execution.