农机化研究
農機化研究
농궤화연구
Journal of Agricultural Mechanization Research
2016年
7期
197-201
,共5页
人工势力场%精密播种机%遗传算法%路径规划%覆盖面积
人工勢力場%精密播種機%遺傳算法%路徑規劃%覆蓋麵積
인공세력장%정밀파충궤%유전산법%로경규화%복개면적
artificial power field%precision seeding machine%genetic algorithm%path planning%coverage area
为了提高播种机对复杂地块的自适应能力,提升播种机的播种精度和播种效率,提出了适合精播机的基于子区域的折返全区域覆盖路径规划方法,并对播种机的排肥器和排种器进行了改进,以适应自动路径规划的需要. 为了优化基于子区域的路径搜索方法,使用人工势场和遗传算法对寻优方法进行了优化,提高了算法的效率. 为了测试该方法的有效性和可靠性,将路径规划系统安装到了播种机械上,通过对播种的测试发现,该方法实现了复杂地块播种的全区域覆盖,并且可以有效地躲避障碍物. 对3 种不同的算法进行对比测试发现:基于遗传算法的子区域路径规划模型的寻优效果最佳,其覆盖面积大,转弯次数少,用时少,最短时间为11.25 min ,仅为其他算法时间的1/2,路径划分效率较高,满足智能化精密播种机的需求,可以在精密播种机的路径规划系统中使用.
為瞭提高播種機對複雜地塊的自適應能力,提升播種機的播種精度和播種效率,提齣瞭適閤精播機的基于子區域的摺返全區域覆蓋路徑規劃方法,併對播種機的排肥器和排種器進行瞭改進,以適應自動路徑規劃的需要. 為瞭優化基于子區域的路徑搜索方法,使用人工勢場和遺傳算法對尋優方法進行瞭優化,提高瞭算法的效率. 為瞭測試該方法的有效性和可靠性,將路徑規劃繫統安裝到瞭播種機械上,通過對播種的測試髮現,該方法實現瞭複雜地塊播種的全區域覆蓋,併且可以有效地躲避障礙物. 對3 種不同的算法進行對比測試髮現:基于遺傳算法的子區域路徑規劃模型的尋優效果最佳,其覆蓋麵積大,轉彎次數少,用時少,最短時間為11.25 min ,僅為其他算法時間的1/2,路徑劃分效率較高,滿足智能化精密播種機的需求,可以在精密播種機的路徑規劃繫統中使用.
위료제고파충궤대복잡지괴적자괄응능력,제승파충궤적파충정도화파충효솔,제출료괄합정파궤적기우자구역적절반전구역복개로경규화방법,병대파충궤적배비기화배충기진행료개진,이괄응자동로경규화적수요. 위료우화기우자구역적로경수색방법,사용인공세장화유전산법대심우방법진행료우화,제고료산법적효솔. 위료측시해방법적유효성화가고성,장로경규화계통안장도료파충궤계상,통과대파충적측시발현,해방법실현료복잡지괴파충적전구역복개,병차가이유효지타피장애물. 대3 충불동적산법진행대비측시발현:기우유전산법적자구역로경규화모형적심우효과최가,기복개면적대,전만차수소,용시소,최단시간위11.25 min ,부위기타산법시간적1/2,로경화분효솔교고,만족지능화정밀파충궤적수구,가이재정밀파충궤적로경규화계통중사용.
In order to improve the adaptive ability of the planter of complex block, enhance the sowing efficiency of planter seeding accuracy, it put forward suitable for precision seeding machine in sub regional exhumation of full area coverage path planning method based on the seeder row fertilizer.The seed metering device was improved so as to adapt to the need of automatic path planning.In order to optimize the path search method based on sub region, the artificial po-tential field and genetic algorithm are used to optimize the optimization method, which improves the efficiency of the algo-rithm.For the validity and reliability of the test method, path planning system is installed in the planting machinery. Through the seeding test, the method realized complex plots sown with the full area coverage and obstacle avoidance.On the three different algorithms for comparison tests,it was found that optimization effect is the best for its large coverage ar-ea based on genetic algorithm of sub regional model for path planning, turning times less, fewer, the shortest time only 11.25min, only for 1/2 of the other algorithm, path division of higher efficiency and meet the intelligent demand of pre-cision seeding machine, which can be used in path planning system in precision seeder.