Research On Path Planning Of Orchard Soil Sampling Robot

Orchard soil sampling robots help improve labor efficiency.Path planning is a key technology to orchard soil sampling robot research and development that directly influences on-spot performance effectiveness and efficiency.In accordance to typical orchard environments,the paper further studies on collision-free path planning using the particle swarm algorithm and the ant colony algorithm.In order to improve global optimal path planning to preset destination for orchard robots,a fusion algorithm of ant colony and particle swam optimization is proposed to modify problems on solving for optimal paths.Ant colony algorithm is applied to obtain the global optimal path,since particle swarm optimization is prone to local optimization;sets the identity grid and improves path reliability;brings in active factor to promote particle velocity diversity.The pheromone distribution on the path is adjusted according to the optimal solution of the particle swarm optimization algorithm to solve the problem of initial pheromone deficiency in the ant colony algorithm.Simplified operator is incorporated to further optimize the path length.The simulation results show that the fusion algorithm has a satisfactory reliability and upgrades the optimization performance.Most algorithm methods underperform on large turning angle under grid maps.To modify the integrated algorithm and optimize the global pheromone renewing mechanism,one application suggested is using a modified integrated algorithm to solve for the global optimal path,and next applies Cubic B-spline Curve that smooths the path spikes.Simulation results show that the modified integrated algorithm effectively decreases the number of path spikes.While orchard robots have to circumvent random obstacles and move on the global optimal path,adjustments followed are: using a hybrid path planning algorithm to remain orchard robots moving along the global optimal path as the modified integrated algorithm goes;when the built-in sensor alarms off possible collisions of dynamic obstacles,the modified ant-colony algorithm starts off setting a local destination and searching for an obstacle-free path along the direction major pheromones distributed on;when no obstacles on way,mobile robots move straight to the designation along the global optimal path.Through the experimental platform,wheeled mobile robots complete the path planning mission fairly.