智能机械平台轨迹规划与避障方法研究
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摘要
为了更好地了解当前各类路径规划算法的优缺点,文章通过对当前各种智能机械平台的自主路径规划算法的分析研究,阐述了各种算法的工作原理、适用范围和优缺点等。研究结果表明,全局路径规划算法更多地应用于静态环境中,对实时性要求不高,注重路径规划最优性;而局部路径规划的大多数算法都有容易陷入局部最优解的缺点,常需要结合其他方法来优化,在动态环境中算法的难易程度普遍对规划信息量比较敏感。
In order to better understand the advantages and disadvantages of all kinds of path planning algorithms,the autonomous path planning algorithms for the intelligent mechanical platform are researched and the principle,applicable range and advantages and disadvantages of the algorithms are elaborated.It is concluded that global path planning algorithms are more frequently applied in static environment,which have low real-time requirements and focus more on the optimality of path planning.Most of local path planning algorithms are easy to fall into local optimal solution and need to be optimized combining with other methods,and the complexity of the algorithms in dynamic environment is generally sensitive to the amount of planning information.
In order to better understand the advantages and disadvantages of all kinds of path planning algorithms,the autonomous path planning algorithms for the intelligent mechanical platform are researched and the principle,applicable range and advantages and disadvantages of the algorithms are elaborated.It is concluded that global path planning algorithms are more frequently applied in static environment,which have low real-time requirements and focus more on the optimality of path planning.Most of local path planning algorithms are easy to fall into local optimal solution and need to be optimized combining with other methods,and the complexity of the algorithms in dynamic environment is generally sensitive to the amount of planning information.
引文
[1]万晓凤,胡伟方,武义,等.基于改进蚁群算法的机器人路径规划研究[J].计算机工程与应用,2014,50(18):63-66.
[2]林斌.不确定条件下U型装配线平衡模型研究[D].武汉:武汉科技大学,2015.
[3]胡荟,蔡秀珊.机器人三维路径规划问题的一种改进蚁群算法[J].计算机工程与科学,2012,34(11):153-157.
[4]刘玉娟,黄敦华,李勇,等.路径规划在移动(保洁)机器人装置中的应用[J].机电产品开发与创新,2012,25(5):4-6.
[5]张德祥.基于改进蚁群算法的机器人三维路径规划研究[D].青岛:青岛科技大学,2015.
[6] ZIMMERMANN M,KO··NIG C.Integration of a visibility graph based path planning method in the ACT/FHS rotorcraft[J].CEAS Aeronautical Journal,2016,7(3):391-403.
[7] JUNGTAE K,MUNSANG K,DAIJIN K.Variants of the quantized visibility graph for efficient path planning[J].Advanced Robotics,2011,25(18):2341-2360.
[8]李晶,陈思.浅谈最优控制[J].黑龙江科技信息,2008(27):18.
[9]王璐萍.一类不确定仿射非线性系统的最优滑模控制[D].青岛:青岛科技大学,2010.
[10] KORAYEM M H,NAZEMIZADEH M,NOHOOJI H R.Smooth Jerk-Bounded optimal path planning of tricycle wheeled mobile manipulators in the presence of environmental obstacles[J].International Journal of Advanced Robotic Systems,2012,9(4):105-118.
[11] LI P,HUANG X H,WANG M.A novel hybrid method for mobile robot path planning in unknown dynamic environment based on hybrid DSm model grid map[J].Journal of Experimental and Theoretical Artificial Intelligence,2011,23(1):5-22.
[12]毛健,赵红东,姚婧婧,等.人工神经网络的发展及应用[J].电子设计工程,2011,19(24):62-65.
[13] DJOUANI K,HAMAM Y.Ship optimal path planning and artifical neural nets for berthing.[C]//Proceedings of OCEAS’94.[S.l.]:IEEE,1994:4851410.
[14]胡荟,蔡秀珊.基于改进蚁群算法的三维空间机器人路径规划[J].计算机系统应用,2011,20(11):95-98.
[15]姬伟,程风仪,赵德安,等.基于改进人工势场的苹果采摘机器人机械手避障方法[J].农业机械学报,2013,44(11):253-259.
[16] KEISUKE S.Deadlock-free motion planning using the Laplace potential field[J].Advanced Robotics,1992,7(5):449-461.
[17] CHEN Y B,LUO G C,MEI Y S,et al.UAV path planning using artificial potential field method updated by optimal control theory[J].International Journal of Systems Science,2016,47(6):1407-1420.
[18]盛四清,李婧,田文树.群智能算法在电力系统无功优化中的应用[J].电力科学与工程,2008,24(1):1-4.
[19]陈家照,罗寅生.改进粒子群三维空间路径规划研究[J].计算机工程与应用,2010,46(33):39-42.
[20]魏代俊,向长城.粒子群算法在三维空间机器人路径规划中的应用[J].南京师范大学学报(工程技术版),2008,8(3):77-81.
[21]张殿富,刘福,杨俊,等.基于多级优化的粒子群算法在航迹规划中的应用[J].海军航空工程学院学报,2013,28(1):53-57.
[22] MO H W,XU L F.Research of biogeography particle swarm optimization for robot path planning[J].Neurocomputing,2015,148:91-99.
[23]王家海,庞旭旻,张宝弟.基于遗传算法的焊接机器人三维路径规划研究[J].机电一体化,2009,15(8):85-87.
[24] HU Y,YANG S X.A knowledge based genetic algorithm for path planning of a mobile robot[J].Acta Electronica Sinica,2006,34(5):911-914.
[25] LIU G,LAO S Y,HOU L L,et al.A constrained driven Genetic Algorithm for path planning of anti-ship missile[J].Journal of Ballistics,2012,24(4):11-17.
[26]邸忆,龙飞,李卓越.一种基于改进蚁群算法的多目标跟踪数据关联方法[J].计算机应用与软件,2013,30(4):306-309.
[27]曲艳峰,蒋丹.基于动态蚁群算法的三维管路路径规划[J].东华大学学报(自然科学版),2011,37(4):387-391.
[28] SHARMAN V,GROVER A.A modified ant colony optimization algorithm(mACO)for energy efficient wireless sensor networks[J].Optik-International Journal for Light and Electron Optics,2016,127(4):2169-2172.
[29]周培培.未知环境下机器人路径规划算法研究[D].青岛:青岛科技大学,2014.
[30]MOUSTRIS G,TZAFESTAS S G.A robust fuzzy logic path tracker for non-holonomic mobile robots[J].International Journal on Artificial Intelligence Tools,2005,14(6):935-965.
[31] SONG Q L,ZhAO J B.Multi-robot path planning based on learning classifier system with policy gradient reinforcement learning and support vector machine(PGRL-SVM)[J].Applied Mechanics and Materials,2013,347/348/349/350:5-22.
[32] DONG D Y,HE B,LIU Y,et al.A novel path planning method based on extreme learning machine for autonomous underwater vehicle[C]//OCEANS 2015.[S.l.]:IEEE,2016:7401951.
[33]顾辰.改进的A*算法在机器人路径规划中的应用[J].电子设计工程,2014(19):96-98.
[34]韩丽,黄永丽.三维虚拟飞行角色的路径规划和姿态控制[J].太原理工大学学报,2013,44(2):180-184.
[35]朱国涛,周树道,吕波,等.基于气象威胁的无人机航迹规划方法研究[J].电光与控制,2011,18(6):26-30.
[36]弓晨.三维曲面上路径规划问题的研究[D].武汉:中国地质大学(武汉),2006.
[37]刘利强,于飞,戴运桃.基于蚁群算法的水下潜器三维空间路径规划[J].系统仿真学报,2008,20(14):3712-3716.
[38]吴玉香,王超.一种改进的移动机器人三维路径规划方法[J].华南理工大学学报(自然科学版),2016,44(9):53-60.
[39]李向军,霍艳丽,曾勍炜,等.三维机器人路径规划的一种变异算子蚁群算法[J].计算机仿真,2015,32(2):364-368,394.
[40]李建建.基于元胞遗传算法的避障路径规划[D].南昌:南昌航空大学,2012.
[41] OTA Y,NISHIDA S I,MIURA M,et al.A study on path planning method for exploration robot taking account of communication transmissibility[J].Journal of Materials&Metallurgy,2015,14(3):236-238.
[42] SHARON G,STERN R,FELNER A,et al.Conflict-based search for optimal multi-agent pathfinding[J].Artificial Intelligence,2015,219(C):40-66.
[43] WANGT K,DANG Q,PAN P Y.Path planning approach in unknown environment[J].International Journal of Automation and Computing,2010,7(3):310-316.
[44] PERTRES C,PAILHAS Y,PATRON P,et al.Path planning for autonomous underwater vehicles[J].IEEE Transactions on Robotics,2007,23(2):331-341.
[45]石鸿雁,孙茂相,孙昌志,等.未知环境下移动机器人路径规划方法[J].沈阳工业大学学报,2005,27(1):63-69.
[46]张捍东,郑睿,岑豫皖,等.移动机器人路径规划技术的现状与展望[J].系统仿真学报,2005,17(2):439-443.
[47]房亚群.移动机器人路径规划的现状和发展[J].科技传播,2009(11):67-68.
[48]陈洋,赵新刚,韩建达,等.移动机器人3维路径规划方法综述[J].机器人,2010,32(4):568-576.
[2]林斌.不确定条件下U型装配线平衡模型研究[D].武汉:武汉科技大学,2015.
[3]胡荟,蔡秀珊.机器人三维路径规划问题的一种改进蚁群算法[J].计算机工程与科学,2012,34(11):153-157.
[4]刘玉娟,黄敦华,李勇,等.路径规划在移动(保洁)机器人装置中的应用[J].机电产品开发与创新,2012,25(5):4-6.
[5]张德祥.基于改进蚁群算法的机器人三维路径规划研究[D].青岛:青岛科技大学,2015.
[6] ZIMMERMANN M,KO··NIG C.Integration of a visibility graph based path planning method in the ACT/FHS rotorcraft[J].CEAS Aeronautical Journal,2016,7(3):391-403.
[7] JUNGTAE K,MUNSANG K,DAIJIN K.Variants of the quantized visibility graph for efficient path planning[J].Advanced Robotics,2011,25(18):2341-2360.
[8]李晶,陈思.浅谈最优控制[J].黑龙江科技信息,2008(27):18.
[9]王璐萍.一类不确定仿射非线性系统的最优滑模控制[D].青岛:青岛科技大学,2010.
[10] KORAYEM M H,NAZEMIZADEH M,NOHOOJI H R.Smooth Jerk-Bounded optimal path planning of tricycle wheeled mobile manipulators in the presence of environmental obstacles[J].International Journal of Advanced Robotic Systems,2012,9(4):105-118.
[11] LI P,HUANG X H,WANG M.A novel hybrid method for mobile robot path planning in unknown dynamic environment based on hybrid DSm model grid map[J].Journal of Experimental and Theoretical Artificial Intelligence,2011,23(1):5-22.
[12]毛健,赵红东,姚婧婧,等.人工神经网络的发展及应用[J].电子设计工程,2011,19(24):62-65.
[13] DJOUANI K,HAMAM Y.Ship optimal path planning and artifical neural nets for berthing.[C]//Proceedings of OCEAS’94.[S.l.]:IEEE,1994:4851410.
[14]胡荟,蔡秀珊.基于改进蚁群算法的三维空间机器人路径规划[J].计算机系统应用,2011,20(11):95-98.
[15]姬伟,程风仪,赵德安,等.基于改进人工势场的苹果采摘机器人机械手避障方法[J].农业机械学报,2013,44(11):253-259.
[16] KEISUKE S.Deadlock-free motion planning using the Laplace potential field[J].Advanced Robotics,1992,7(5):449-461.
[17] CHEN Y B,LUO G C,MEI Y S,et al.UAV path planning using artificial potential field method updated by optimal control theory[J].International Journal of Systems Science,2016,47(6):1407-1420.
[18]盛四清,李婧,田文树.群智能算法在电力系统无功优化中的应用[J].电力科学与工程,2008,24(1):1-4.
[19]陈家照,罗寅生.改进粒子群三维空间路径规划研究[J].计算机工程与应用,2010,46(33):39-42.
[20]魏代俊,向长城.粒子群算法在三维空间机器人路径规划中的应用[J].南京师范大学学报(工程技术版),2008,8(3):77-81.
[21]张殿富,刘福,杨俊,等.基于多级优化的粒子群算法在航迹规划中的应用[J].海军航空工程学院学报,2013,28(1):53-57.
[22] MO H W,XU L F.Research of biogeography particle swarm optimization for robot path planning[J].Neurocomputing,2015,148:91-99.
[23]王家海,庞旭旻,张宝弟.基于遗传算法的焊接机器人三维路径规划研究[J].机电一体化,2009,15(8):85-87.
[24] HU Y,YANG S X.A knowledge based genetic algorithm for path planning of a mobile robot[J].Acta Electronica Sinica,2006,34(5):911-914.
[25] LIU G,LAO S Y,HOU L L,et al.A constrained driven Genetic Algorithm for path planning of anti-ship missile[J].Journal of Ballistics,2012,24(4):11-17.
[26]邸忆,龙飞,李卓越.一种基于改进蚁群算法的多目标跟踪数据关联方法[J].计算机应用与软件,2013,30(4):306-309.
[27]曲艳峰,蒋丹.基于动态蚁群算法的三维管路路径规划[J].东华大学学报(自然科学版),2011,37(4):387-391.
[28] SHARMAN V,GROVER A.A modified ant colony optimization algorithm(mACO)for energy efficient wireless sensor networks[J].Optik-International Journal for Light and Electron Optics,2016,127(4):2169-2172.
[29]周培培.未知环境下机器人路径规划算法研究[D].青岛:青岛科技大学,2014.
[30]MOUSTRIS G,TZAFESTAS S G.A robust fuzzy logic path tracker for non-holonomic mobile robots[J].International Journal on Artificial Intelligence Tools,2005,14(6):935-965.
[31] SONG Q L,ZhAO J B.Multi-robot path planning based on learning classifier system with policy gradient reinforcement learning and support vector machine(PGRL-SVM)[J].Applied Mechanics and Materials,2013,347/348/349/350:5-22.
[32] DONG D Y,HE B,LIU Y,et al.A novel path planning method based on extreme learning machine for autonomous underwater vehicle[C]//OCEANS 2015.[S.l.]:IEEE,2016:7401951.
[33]顾辰.改进的A*算法在机器人路径规划中的应用[J].电子设计工程,2014(19):96-98.
[34]韩丽,黄永丽.三维虚拟飞行角色的路径规划和姿态控制[J].太原理工大学学报,2013,44(2):180-184.
[35]朱国涛,周树道,吕波,等.基于气象威胁的无人机航迹规划方法研究[J].电光与控制,2011,18(6):26-30.
[36]弓晨.三维曲面上路径规划问题的研究[D].武汉:中国地质大学(武汉),2006.
[37]刘利强,于飞,戴运桃.基于蚁群算法的水下潜器三维空间路径规划[J].系统仿真学报,2008,20(14):3712-3716.
[38]吴玉香,王超.一种改进的移动机器人三维路径规划方法[J].华南理工大学学报(自然科学版),2016,44(9):53-60.
[39]李向军,霍艳丽,曾勍炜,等.三维机器人路径规划的一种变异算子蚁群算法[J].计算机仿真,2015,32(2):364-368,394.
[40]李建建.基于元胞遗传算法的避障路径规划[D].南昌:南昌航空大学,2012.
[41] OTA Y,NISHIDA S I,MIURA M,et al.A study on path planning method for exploration robot taking account of communication transmissibility[J].Journal of Materials&Metallurgy,2015,14(3):236-238.
[42] SHARON G,STERN R,FELNER A,et al.Conflict-based search for optimal multi-agent pathfinding[J].Artificial Intelligence,2015,219(C):40-66.
[43] WANGT K,DANG Q,PAN P Y.Path planning approach in unknown environment[J].International Journal of Automation and Computing,2010,7(3):310-316.
[44] PERTRES C,PAILHAS Y,PATRON P,et al.Path planning for autonomous underwater vehicles[J].IEEE Transactions on Robotics,2007,23(2):331-341.
[45]石鸿雁,孙茂相,孙昌志,等.未知环境下移动机器人路径规划方法[J].沈阳工业大学学报,2005,27(1):63-69.
[46]张捍东,郑睿,岑豫皖,等.移动机器人路径规划技术的现状与展望[J].系统仿真学报,2005,17(2):439-443.
[47]房亚群.移动机器人路径规划的现状和发展[J].科技传播,2009(11):67-68.
[48]陈洋,赵新刚,韩建达,等.移动机器人3维路径规划方法综述[J].机器人,2010,32(4):568-576.