高速公路绿篱修剪机器人手臂避障路径规划
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摘要
针对非结构环境下高速公路绿篱修剪机器人手臂实时准确避障问题,提出一种基于扰动人工势场法的避障路径规划解决方法.根据绿篱隔离带与障碍物分布情况,设计智能修剪机器人执行机构,构建包络障碍物简化模型,分析机械臂与障碍物的碰撞条件,求解机械臂在修剪过程中的避碰空间.引入斥力场调节策略来优化势场模型,建立斥力场扰动机制调整斥力影响方式,消除传统算法中的局部极小点、目标不可达等现象.在避碰空间内,应用扰动人工势场法对机械臂进行路径规划仿真,仿真结果表明,机械臂跳出局部极小点,灵活顺利避障,成功抵达目标点,验证了该方法的有效性和可行性.
Expressway hedgerow pruning robots need be able to recognize hedgerow and position themselves real-time,to plan an obstacle avoidance trajectory from the starting point to target point based on the position relationship between hedgerows and obstacles.Compared with the traditional industry manipulator,the expressway hedgerow pruning robot manipulator frequently works in unstructured environments with unknown obstacles and irregular scales. It is difficult to establish a mathematical model of obstacles precisely and comprehensively. The problem of real-time obstacle avoidance can be solved by path planning. Thus,aiming at the problem of real-time obstacle avoidance for expressway hedgerows pruning robot manipulator in an unstructured environment,a novel path planning method to avoid obstacle based on perturbed artificial potential field( PAPF) was proposed. According to the distribution of hedgerows and obstacles,simplified models of intelligent pruning robot and sphere enveloping obstacle were established. By considering the geometric relationship between manipulator and obstacle,the collision conditions of manipulator and obstacles were analyzed,and then,the collision avoidance space of manipulator was solved. The traditional artificial potential field method was associated with some problems such as local minimum point( LMP) and goals nonreachable with obstacles nearby( GNRON). In this study,a repulsion field adjustment strategy was presented to optimize the function model of potential field,and a repulsion field perturbation mechanism was introduced to adjust the effect of repulsion in order to flexibly avoid obstacles and successfully reach the target point. The path planning simulation of the designed manipulator was carried out in the collision avoidance space using PAPF. The simulation result shows that the manipulator smoothly jumps out of the LMP and reaches the target point successfully by accurately avoiding obstacles in real time,which verifies the effectiveness and feasibility of the proposed method.
Expressway hedgerow pruning robots need be able to recognize hedgerow and position themselves real-time,to plan an obstacle avoidance trajectory from the starting point to target point based on the position relationship between hedgerows and obstacles.Compared with the traditional industry manipulator,the expressway hedgerow pruning robot manipulator frequently works in unstructured environments with unknown obstacles and irregular scales. It is difficult to establish a mathematical model of obstacles precisely and comprehensively. The problem of real-time obstacle avoidance can be solved by path planning. Thus,aiming at the problem of real-time obstacle avoidance for expressway hedgerows pruning robot manipulator in an unstructured environment,a novel path planning method to avoid obstacle based on perturbed artificial potential field( PAPF) was proposed. According to the distribution of hedgerows and obstacles,simplified models of intelligent pruning robot and sphere enveloping obstacle were established. By considering the geometric relationship between manipulator and obstacle,the collision conditions of manipulator and obstacles were analyzed,and then,the collision avoidance space of manipulator was solved. The traditional artificial potential field method was associated with some problems such as local minimum point( LMP) and goals nonreachable with obstacles nearby( GNRON). In this study,a repulsion field adjustment strategy was presented to optimize the function model of potential field,and a repulsion field perturbation mechanism was introduced to adjust the effect of repulsion in order to flexibly avoid obstacles and successfully reach the target point. The path planning simulation of the designed manipulator was carried out in the collision avoidance space using PAPF. The simulation result shows that the manipulator smoothly jumps out of the LMP and reaches the target point successfully by accurately avoiding obstacles in real time,which verifies the effectiveness and feasibility of the proposed method.
引文
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[7] Lin C J,Li T H S,Kuo P H,et al. Integrated particle swarm optimization algorithm based obstacle avoidance control design for home service robot. Comput Electr Eng,2016,56:748
[8] Chou W S,Wang S. Research on obstacle avoidance by virtual force for redundant robot. China Mech Eng,2011,22(24):2899)(丑武胜,王朔.基于虚拟力的的冗余度机器人自主避障研究.中国机械工程,2011,22(24):2899)
[9] Xie B Y,Zhao J,Liu Y. Motion planning of reaching point movements for 7R robotic manipulators in obstacle environment based on rapidly-exploring random tree algorithm. J Mech Eng,2012,48(3):63(谢碧云,赵京,刘宇.基于快速扩展随机树的7R机械臂避障达点运动规划.机械工程学报,2012,48(3):63)
[10] Wang S K,Zhu L,Wang J Z. Path plan of 6-DOF robot manipulators in obstacle environment based on navigation potential function. Trans Beijing Inst Technol,2015,35(2):186(汪首坤,朱磊,王军政.基于导航势函数法的六自由度机械臂避障路径规划.北京理工大学学报,2015,35(2):186)
[11] Ji W,Cheng F Y,Zhao D A,et al. Obstacle avoidance method of apple harvesting robot manipulator. Trans Chin Soc Agric Mach,2013,44(11):253(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.农业机械学报,2013,44(11):253)
[12] Qi R L,Zhou W J,Wang T J. An obstacle avoidance trajectory planning scheme for space manipulators based on genetic algorithm. Robot,2014,36(3):263(祁若龙,周维佳,王铁军.一种基于遗传算法的空间机械臂避障轨迹规划方法.机器人,2014,36(3):263)
[13] Machmudah A,Parman S,Zainuddin A,et al. Polynomial joint angle arm robot motion planning in complex geometrical obstacles. Appl Soft Comput,2013,13(2):1099
[14] Toshani H,Farrokhi M. Real-time inverse kinematics of redundant manipulators using neural networks and quadratic programming:a Lyapunow-based approach. Rob Autonom Syst,2014,62(6):766
[15] Hasan A T,Ismail N,Hamouda A M S,et al. Artificial neural network-based kinematics Jacobian solution for serial manipulator passing through singular configurations. Adv Eng Software,2010,41(2):359
[16] Jia Q X,Chen G,Sun H X,et al. Path planning for space manipulator to avoid obstacle based on A*algorithm. J Mech Eng,2010,46(13):109(贾庆轩,陈钢,孙汉旭,等.基于A*算法的空间机械臂避障路径规划.机械工程学报,2010,46(13):109)
[17] Khatib O. Real-time obstacle avoidance for manipulators and mobile robots. Int J Rob Res,1986,5(1):90
[2] Yin J J,Wu C Y,Yang S X,et al. Obstacle-avoidance path planning of robot arm for tomato-picking robot. Trans Chin Soc Agric Mach,2012,43(12):171(尹建军,武传宇,Yang Simon X,等.番茄采摘机器人机械臂避障路径规划.农业机械学报,2012,43(12):171)
[3] Jia Q X,Zhang Q R,Gao X,et al. Dynamic obstacle avoidance algorithm for redundant robots with pre-selected minimum distance index. Robot,2013,35(1):17(贾庆轩,张倩茹,高欣,等.预选择最小距离指标的冗余机器人动态避障算法.机器人,2013,35(1):17)
[4] Flacco F,De Luca A,Khatib O. Motion control of redundant robots under joint constraints:saturation in the null space//Proceedings of 2012 IEEE International Conference on Robotics and Automation. Saint Paul,2012:285
[5] Chyan G S,Ponnambalam S G. Obstacle avoidance control of redundant robots using variants of particle swarm optimization. Rob Comput Integr Manuf,2012,28(2):147
[6] Wang S K,Di Z,Wang J Z,et al. Path planning method for manipulator to avoid obstacle based on advanced A*algorithm. Trans Beijing Inst Technol,2011,31(11):1302(汪首坤,邸智,王军政,等.基于A*改进算法的机械臂避障路径规划.北京理工大学学报,2011,31(11):1302)
[7] Lin C J,Li T H S,Kuo P H,et al. Integrated particle swarm optimization algorithm based obstacle avoidance control design for home service robot. Comput Electr Eng,2016,56:748
[8] Chou W S,Wang S. Research on obstacle avoidance by virtual force for redundant robot. China Mech Eng,2011,22(24):2899)(丑武胜,王朔.基于虚拟力的的冗余度机器人自主避障研究.中国机械工程,2011,22(24):2899)
[9] Xie B Y,Zhao J,Liu Y. Motion planning of reaching point movements for 7R robotic manipulators in obstacle environment based on rapidly-exploring random tree algorithm. J Mech Eng,2012,48(3):63(谢碧云,赵京,刘宇.基于快速扩展随机树的7R机械臂避障达点运动规划.机械工程学报,2012,48(3):63)
[10] Wang S K,Zhu L,Wang J Z. Path plan of 6-DOF robot manipulators in obstacle environment based on navigation potential function. Trans Beijing Inst Technol,2015,35(2):186(汪首坤,朱磊,王军政.基于导航势函数法的六自由度机械臂避障路径规划.北京理工大学学报,2015,35(2):186)
[11] Ji W,Cheng F Y,Zhao D A,et al. Obstacle avoidance method of apple harvesting robot manipulator. Trans Chin Soc Agric Mach,2013,44(11):253(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.农业机械学报,2013,44(11):253)
[12] Qi R L,Zhou W J,Wang T J. An obstacle avoidance trajectory planning scheme for space manipulators based on genetic algorithm. Robot,2014,36(3):263(祁若龙,周维佳,王铁军.一种基于遗传算法的空间机械臂避障轨迹规划方法.机器人,2014,36(3):263)
[13] Machmudah A,Parman S,Zainuddin A,et al. Polynomial joint angle arm robot motion planning in complex geometrical obstacles. Appl Soft Comput,2013,13(2):1099
[14] Toshani H,Farrokhi M. Real-time inverse kinematics of redundant manipulators using neural networks and quadratic programming:a Lyapunow-based approach. Rob Autonom Syst,2014,62(6):766
[15] Hasan A T,Ismail N,Hamouda A M S,et al. Artificial neural network-based kinematics Jacobian solution for serial manipulator passing through singular configurations. Adv Eng Software,2010,41(2):359
[16] Jia Q X,Chen G,Sun H X,et al. Path planning for space manipulator to avoid obstacle based on A*algorithm. J Mech Eng,2010,46(13):109(贾庆轩,陈钢,孙汉旭,等.基于A*算法的空间机械臂避障路径规划.机械工程学报,2010,46(13):109)
[17] Khatib O. Real-time obstacle avoidance for manipulators and mobile robots. Int J Rob Res,1986,5(1):90
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