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
针对蚁群算法运动规划收敛慢且精度不佳的问题,提出一种改进势场蚁群(improved artificial potential field ant colony optimization, IAPF-ACO)算法。斥力计算模型引入目标调节因子解决势场寻优不可达且易陷入局部最优问题。蚁群算法...针对蚁群算法运动规划收敛慢且精度不佳的问题,提出一种改进势场蚁群(improved artificial potential field ant colony optimization, IAPF-ACO)算法。斥力计算模型引入目标调节因子解决势场寻优不可达且易陷入局部最优问题。蚁群算法计算框架加入改进势场模型,即启发信息函数中增加势场信息因子。三维障碍物空间仿真规划表明:IAPF-ACO算法在离散环境与聚集环境规划路径质量较优、规划结果较为稳定。在MATLAB搭建工业机器人仿真模型,关节空间内对规划路径点平滑处理,避障仿真结果表明,工业机器人末端位移是一条安全、平滑的运动轨迹。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
针对基本的快速拓展随机树算法(rapidly-exploring random tree,RRT^(*))存在搜索随机性大、效率低、路径非最优的缺点,提出一种引入人工势场法算法(artificial potential field method,APF)和Douglas-Peucker算法的改进RRT^(*)-APF-DP...针对基本的快速拓展随机树算法(rapidly-exploring random tree,RRT^(*))存在搜索随机性大、效率低、路径非最优的缺点,提出一种引入人工势场法算法(artificial potential field method,APF)和Douglas-Peucker算法的改进RRT^(*)-APF-DP路径规划算法.在RRT*算法的采样点生成阶段引入变采样范围偏置搜索与步长自适应调整策略,融合重新设计的APF算法的引力与斥力函数,增强路径扩展导向性与绕过障碍物能力.采用重采样策略改进DP算法,优化避障代价与控制点数量.实验结果表明,本算法规划的避障路径满足机械臂的运动要求,且算法规划的避障路径代价、规划时间和路径控制节点数均得到有效改善.展开更多
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.
文摘针对蚁群算法运动规划收敛慢且精度不佳的问题,提出一种改进势场蚁群(improved artificial potential field ant colony optimization, IAPF-ACO)算法。斥力计算模型引入目标调节因子解决势场寻优不可达且易陷入局部最优问题。蚁群算法计算框架加入改进势场模型,即启发信息函数中增加势场信息因子。三维障碍物空间仿真规划表明:IAPF-ACO算法在离散环境与聚集环境规划路径质量较优、规划结果较为稳定。在MATLAB搭建工业机器人仿真模型,关节空间内对规划路径点平滑处理,避障仿真结果表明,工业机器人末端位移是一条安全、平滑的运动轨迹。
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.
文摘针对基本的快速拓展随机树算法(rapidly-exploring random tree,RRT^(*))存在搜索随机性大、效率低、路径非最优的缺点,提出一种引入人工势场法算法(artificial potential field method,APF)和Douglas-Peucker算法的改进RRT^(*)-APF-DP路径规划算法.在RRT*算法的采样点生成阶段引入变采样范围偏置搜索与步长自适应调整策略,融合重新设计的APF算法的引力与斥力函数,增强路径扩展导向性与绕过障碍物能力.采用重采样策略改进DP算法,优化避障代价与控制点数量.实验结果表明,本算法规划的避障路径满足机械臂的运动要求,且算法规划的避障路径代价、规划时间和路径控制节点数均得到有效改善.
