针对复杂输电环境下机械臂多目标点路径规划效率低、路径代价高的问题,提出了基于改进的人工势场引导的知情快速扩展随机树算法(improved artificial potential field-informed rapidly-exploring random trees star,IAPF-IRRT^(*))来...针对复杂输电环境下机械臂多目标点路径规划效率低、路径代价高的问题,提出了基于改进的人工势场引导的知情快速扩展随机树算法(improved artificial potential field-informed rapidly-exploring random trees star,IAPF-IRRT^(*))来提升路径规划的性能。首先引入长方体斥力场模型改进传统人工势场中球形斥力场模型,建立输电环境下复杂障碍物的斥力场。然后采用位置均匀分布的椭球域改进IAPF-IRRT*算法中的椭圆域,避免复杂输电环境下采样点出现局部冗余,提高搜索效率。最后引入三角寻优法优化路径中的冗余节点并结合三次样条插曲线对路径平滑处理。在三维简单、三维复杂和复杂输电环境这三组不同复杂程度的障碍物地图上进行验证,其结果表明:IAPF-IRRT*算法与标准RRT、RRT*算法相比,时间效率分别提升了44.8%~83.8%、68.3%~95.2%、26.5%~71.8%;路径代价分别降低了15.5%~35.0%、14.1%~35.3%、31.5%~43.5%;路径中的节点数量分别减少了75.6%~78.8%、75.0%~78.0%、70.4%~72.0%。展开更多
For accurate trajectory tracking and obstacle avoidance in finite time of a nonholonomic mobile robot,a trajectory tracking controller based on global fast terminal sliding mode method is proposed,which has the advant...For accurate trajectory tracking and obstacle avoidance in finite time of a nonholonomic mobile robot,a trajectory tracking controller based on global fast terminal sliding mode method is proposed,which has the advantages of chattering-free and adjustable convergence time.First of all,the kinematics model of the robot is established in mobile carrier coordinates.Secondly,the global structure including terminal attractor and exponential convergence of the fast terminal sliding mode trajectory tracking controller is proved by Lyapunov stability theory,ensuring that the trajectory and heading angle tracking error converges to a smaller zero range in finite time.Finally,the artificial potential field obstacle avoidance method is introduced to make the robot not only track the reference trajectory strictly,but also avoid the obstacles.The simulation results show that the proposed method can achieve a stable tracking control in finite time for a given reference trajectory.展开更多
Mobile robot path planning is an important research branch in the field of mobile robots.The main disadvantage of the traditional artificial potential field(APF)method is prone to local minima problems.Improved artifi...Mobile robot path planning is an important research branch in the field of mobile robots.The main disadvantage of the traditional artificial potential field(APF)method is prone to local minima problems.Improved artificial potential field(IAPF)method is presented in this paper to solve the problem in the traditional APF method for robot path planning in different conditions.We introduce the distance between the robot and the target point to the function of the original repulsive force field and change the original direction of the repulsive force to avoid the trap problem caused by the local minimum point.The IAPF method is suitable for mobile robot path planning in the complicated environment.Simulation and experiment results at the robot platform illustrated the superiority of the modified IAPF method.展开更多
A novel method is proposed to dynamically control the path following of a ground Ackerman steering robot to avoid a collision.The method consists of collision prediction module,collision avoidance module and global pa...A novel method is proposed to dynamically control the path following of a ground Ackerman steering robot to avoid a collision.The method consists of collision prediction module,collision avoidance module and global path following module.The elliptic repulsive potential field method（ER-PFM）and the enhanced vector polar histogram method（VPH＋）based on the Ackerman steering model are proposed to predict the collision in a dynamic environment.The collision avoidance is realized by the proposed cost function and speed control law.The global path following process is achieved by pure pursuit.Experiments show that the robot can fulfill the dynamic path following task safely and efficiently using the proposed method.展开更多
文摘针对复杂输电环境下机械臂多目标点路径规划效率低、路径代价高的问题,提出了基于改进的人工势场引导的知情快速扩展随机树算法(improved artificial potential field-informed rapidly-exploring random trees star,IAPF-IRRT^(*))来提升路径规划的性能。首先引入长方体斥力场模型改进传统人工势场中球形斥力场模型,建立输电环境下复杂障碍物的斥力场。然后采用位置均匀分布的椭球域改进IAPF-IRRT*算法中的椭圆域,避免复杂输电环境下采样点出现局部冗余,提高搜索效率。最后引入三角寻优法优化路径中的冗余节点并结合三次样条插曲线对路径平滑处理。在三维简单、三维复杂和复杂输电环境这三组不同复杂程度的障碍物地图上进行验证,其结果表明:IAPF-IRRT*算法与标准RRT、RRT*算法相比,时间效率分别提升了44.8%~83.8%、68.3%~95.2%、26.5%~71.8%;路径代价分别降低了15.5%~35.0%、14.1%~35.3%、31.5%~43.5%;路径中的节点数量分别减少了75.6%~78.8%、75.0%~78.0%、70.4%~72.0%。
基金National Natural Science Foundation of China(No.61673042)Shanxi Province Science Foundation for Youths(No.201701D221123)。
文摘For accurate trajectory tracking and obstacle avoidance in finite time of a nonholonomic mobile robot,a trajectory tracking controller based on global fast terminal sliding mode method is proposed,which has the advantages of chattering-free and adjustable convergence time.First of all,the kinematics model of the robot is established in mobile carrier coordinates.Secondly,the global structure including terminal attractor and exponential convergence of the fast terminal sliding mode trajectory tracking controller is proved by Lyapunov stability theory,ensuring that the trajectory and heading angle tracking error converges to a smaller zero range in finite time.Finally,the artificial potential field obstacle avoidance method is introduced to make the robot not only track the reference trajectory strictly,but also avoid the obstacles.The simulation results show that the proposed method can achieve a stable tracking control in finite time for a given reference trajectory.
基金the National Nature Science Foundation of China(Nos.51579024,61374114)the Fundamental Research Funds for the Central Universities(DMU No.3132016311).
文摘Mobile robot path planning is an important research branch in the field of mobile robots.The main disadvantage of the traditional artificial potential field(APF)method is prone to local minima problems.Improved artificial potential field(IAPF)method is presented in this paper to solve the problem in the traditional APF method for robot path planning in different conditions.We introduce the distance between the robot and the target point to the function of the original repulsive force field and change the original direction of the repulsive force to avoid the trap problem caused by the local minimum point.The IAPF method is suitable for mobile robot path planning in the complicated environment.Simulation and experiment results at the robot platform illustrated the superiority of the modified IAPF method.
基金Supported by the National Natural Science Foundation of China(91420203)
文摘A novel method is proposed to dynamically control the path following of a ground Ackerman steering robot to avoid a collision.The method consists of collision prediction module,collision avoidance module and global path following module.The elliptic repulsive potential field method（ER-PFM）and the enhanced vector polar histogram method（VPH＋）based on the Ackerman steering model are proposed to predict the collision in a dynamic environment.The collision avoidance is realized by the proposed cost function and speed control law.The global path following process is achieved by pure pursuit.Experiments show that the robot can fulfill the dynamic path following task safely and efficiently using the proposed method.
