Orchard simulation environment construction based on undulating terrain and SLAM algorithm testing
Terrain relief is an essential aspect of environment perception for agriculture mobile robots to operate in orchard environments.For those robots obtaining surrounding environment through 2D LiDAR(Light Detection and Ranging),terrain relief could cause the pitching and folding motions of 2D LiDAR in three-dimensional space,which would bring false information into further calculations of agriculture robots'poison in orchard world and result in an unreliable localization and map building result.Since the terrain model is hardly constructed in any existing orchard simulation environment either in the research of SLAM algorithms or navigation field,this study constructed an orchard simulation environment utilizing the terrain model with undulating features based on the 2D normal distribution function and tested it with 2D laser-based SLAM algorithms.This specific model could be generated by different fluctuation degrees,maximum altitude intercept,and density of protrusion distribution to simulate the random fluctuation characteristics of real orchard terrain.During experiments,2D LiDAR,odom-etry,and other sensors were used to obtain the mobile robot's movement data.Four classical 2D laser-based SLAM algorithms(Hector SLAM,GMapping,Karto SLAM,and Cartographer)were tested in orchard simula-tion environments with different terrain models which contracted with different terrain parameters.Localization offsets and mapping outcomes were two key aspects of evaluating SLAM results.Offset data,localization trail and global map were provided to evaluate the performance of SLAM algorithms.The experiment results which conducted in 13 different orchard simulation environments with different terrain models showed that the localiza-tion and mapping performance of the 2D laser-based SLAM algorithm decreased with the increase of fluctuation degree and maximum altitude intercept.The projection distribution density did not affect the localization accuracy or the map building ability as large as fluctuation degree and maximum altitude intercept.Hector SLAM can pro-vide more accurate localization results,but the robustness of map building was poor.GMapping can obtain more accurate environmental maps,but the robustness of localization was poor.Cartographer had good robustness of localization,as well as map building,but there were a few deviations appeared.Karto SLAM did not have ad-vantages in the orchard environment compared with other algorithms.
万方数据
维普
