面对采摘作业的复杂环境,提出了一种终点区域RRT(Goal Area RRT,GA-RRT)算法,以提高路径生成的效率并降低路径成本。根据环境系数确定初始步长与终点区域,当拓展节点进入终点区域后,随机点生成范围缩小至终点区域,同时调整步长;然后,在...面对采摘作业的复杂环境,提出了一种终点区域RRT(Goal Area RRT,GA-RRT)算法,以提高路径生成的效率并降低路径成本。根据环境系数确定初始步长与终点区域,当拓展节点进入终点区域后,随机点生成范围缩小至终点区域,同时调整步长;然后,在此基础上引入目标概率偏向方法,提高路径搜索效率;最后,对生成的路径进行简化节点处理以减少路径代价,并使用三次B样条方法平滑路径。仿真实验结果表明:二维环境下,GA-RRT算法相较于RRT、RRT-Connect算法,耗时缩短85.15%、29.86%,路径代价减少19.18%、18.26%;机械臂仿真环境下,与引入目标概率偏向方法的RRT算法进行比较,耗时缩短54.70%,路径代价减少51.59°。利用IRB120机械臂实验平台,验证了算法的可行性。展开更多
针对快速搜索随机树(RRT)算法在航迹规划过程中存在采样点扩展随机性强、航迹曲折不平滑等问题,提出了一种基于约束随机采样点的RRT(Constrained Random Sampling-based RRT,CRS-RRT)算法。该算法引入人工势场法中的引力场势能函数约束...针对快速搜索随机树(RRT)算法在航迹规划过程中存在采样点扩展随机性强、航迹曲折不平滑等问题,提出了一种基于约束随机采样点的RRT(Constrained Random Sampling-based RRT,CRS-RRT)算法。该算法引入人工势场法中的引力场势能函数约束随机采样点在目标点附近采样,引导随机树朝着目标点生长,提高算法的规划速度,并结合去除冗余节点策略和Minimum Snap航迹平滑方法,在复杂三维环境中可快速生成一条安全、平滑且满足无人机动力学约束的航迹。仿真结果表明,该算法有效提高航迹规划速度并缩短航迹长度。展开更多
为解决传统方法在铁路变配电所敷设施工时完全依靠二维设计布线图纸,易发生扭绞、交叉以及浪费物料等问题,基于建筑信息模型(BIM,Building Information Modeling)技术对铁路变配电所的线缆敷设进行优化。利用改进的快速扩展随机树(RRT*,...为解决传统方法在铁路变配电所敷设施工时完全依靠二维设计布线图纸,易发生扭绞、交叉以及浪费物料等问题,基于建筑信息模型(BIM,Building Information Modeling)技术对铁路变配电所的线缆敷设进行优化。利用改进的快速扩展随机树(RRT*,Rapidly Exploring Random Tree*)算法,在三维视图下进行智能布线,解决了线缆布放规划复杂,工艺要求高,施工工艺难以掌握等问题,避免了施工过程中扭绞等问题的发生,同时实现了布线路径最优化。此外,还可以三维动画的形式对整个线缆敷设过程进行模拟和演示,并生成包含路由、长度、规格型号的线缆清单,显著提高了施工效率和工艺质量。展开更多
As autonomous underwater vehicles(AUVs)merely adopt the inductive obstacle avoidance mechanism to avoid collisions with underwater obstacles,path planners for underwater robots should consider the poor search efficien...As autonomous underwater vehicles(AUVs)merely adopt the inductive obstacle avoidance mechanism to avoid collisions with underwater obstacles,path planners for underwater robots should consider the poor search efficiency and inadequate collision-avoidance ability.To overcome these problems,a specific two-player path planner based on an improved algorithm is designed.First,by combing the artificial attractive field(AAF)of artificial potential field(APF)approach with the random rapidly exploring tree(RRT)algorithm,an improved AAF-RRT algorithm with a changing attractive force proportional to the Euler distance between the point to be extended and the goal point is proposed.Second,a twolayer path planner is designed with path smoothing,which combines global planning and local planning.Finally,as verified by the simulations,the improved AAF-RRT algorithm has the strongest searching ability and the ability to cross the narrow passage among the studied three algorithms,which are the basic RRT algorithm,the common AAF-RRT algorithm,and the improved AAF-RRT algorithm.Moreover,the two-layer path planner can plan a global and optimal path for AUVs if a sudden obstacle is added to the simulation environment.展开更多
文中提出了一种混合RRT(rapid-exploration random tree)搜索算法.算法整体上按照全局路径和局部路径的最优试探开展同步计算.在局部路径计算层面,利用RRT^(*)算法基于周边探测数据,结合前沿点信息进行小尺度路径搜索、全局路径计算层面...文中提出了一种混合RRT(rapid-exploration random tree)搜索算法.算法整体上按照全局路径和局部路径的最优试探开展同步计算.在局部路径计算层面,利用RRT^(*)算法基于周边探测数据,结合前沿点信息进行小尺度路径搜索、全局路径计算层面,利用RRT算法进行粗粒度的路径分支决策,并将已选分支的边缘信号反馈给局部路径的计算.通过RRT^(*)的重剪枝功能,能够在局部进行路径优化,而避免将其用于整体路径优化时可能带来的“选择震荡”风险.仿真实验与真实环境结果表明:将RRT*与RRT在局部和全局两种尺度上的区分使用,相较只使用RRT算法路径长度减少了16.4%.展开更多
文摘面对采摘作业的复杂环境,提出了一种终点区域RRT(Goal Area RRT,GA-RRT)算法,以提高路径生成的效率并降低路径成本。根据环境系数确定初始步长与终点区域,当拓展节点进入终点区域后,随机点生成范围缩小至终点区域,同时调整步长;然后,在此基础上引入目标概率偏向方法,提高路径搜索效率;最后,对生成的路径进行简化节点处理以减少路径代价,并使用三次B样条方法平滑路径。仿真实验结果表明:二维环境下,GA-RRT算法相较于RRT、RRT-Connect算法,耗时缩短85.15%、29.86%,路径代价减少19.18%、18.26%;机械臂仿真环境下,与引入目标概率偏向方法的RRT算法进行比较,耗时缩短54.70%,路径代价减少51.59°。利用IRB120机械臂实验平台,验证了算法的可行性。
文摘针对快速搜索随机树(RRT)算法在航迹规划过程中存在采样点扩展随机性强、航迹曲折不平滑等问题,提出了一种基于约束随机采样点的RRT(Constrained Random Sampling-based RRT,CRS-RRT)算法。该算法引入人工势场法中的引力场势能函数约束随机采样点在目标点附近采样,引导随机树朝着目标点生长,提高算法的规划速度,并结合去除冗余节点策略和Minimum Snap航迹平滑方法,在复杂三维环境中可快速生成一条安全、平滑且满足无人机动力学约束的航迹。仿真结果表明,该算法有效提高航迹规划速度并缩短航迹长度。
文摘为解决传统方法在铁路变配电所敷设施工时完全依靠二维设计布线图纸,易发生扭绞、交叉以及浪费物料等问题,基于建筑信息模型(BIM,Building Information Modeling)技术对铁路变配电所的线缆敷设进行优化。利用改进的快速扩展随机树(RRT*,Rapidly Exploring Random Tree*)算法,在三维视图下进行智能布线,解决了线缆布放规划复杂,工艺要求高,施工工艺难以掌握等问题,避免了施工过程中扭绞等问题的发生,同时实现了布线路径最优化。此外,还可以三维动画的形式对整个线缆敷设过程进行模拟和演示,并生成包含路由、长度、规格型号的线缆清单,显著提高了施工效率和工艺质量。
基金Supported by Zhejiang Key R&D Program 558 No.2021C03157the“Construction of a Leading Innovation Team”project by the Hangzhou Munic-559 ipal government,the Startup funding of New-joined PI of Westlake University with Grant No.560(041030150118)the funding support from the Westlake University and Bright Dream Joint In-561 stitute for Intelligent Robotics.
文摘As autonomous underwater vehicles(AUVs)merely adopt the inductive obstacle avoidance mechanism to avoid collisions with underwater obstacles,path planners for underwater robots should consider the poor search efficiency and inadequate collision-avoidance ability.To overcome these problems,a specific two-player path planner based on an improved algorithm is designed.First,by combing the artificial attractive field(AAF)of artificial potential field(APF)approach with the random rapidly exploring tree(RRT)algorithm,an improved AAF-RRT algorithm with a changing attractive force proportional to the Euler distance between the point to be extended and the goal point is proposed.Second,a twolayer path planner is designed with path smoothing,which combines global planning and local planning.Finally,as verified by the simulations,the improved AAF-RRT algorithm has the strongest searching ability and the ability to cross the narrow passage among the studied three algorithms,which are the basic RRT algorithm,the common AAF-RRT algorithm,and the improved AAF-RRT algorithm.Moreover,the two-layer path planner can plan a global and optimal path for AUVs if a sudden obstacle is added to the simulation environment.
文摘文中提出了一种混合RRT(rapid-exploration random tree)搜索算法.算法整体上按照全局路径和局部路径的最优试探开展同步计算.在局部路径计算层面,利用RRT^(*)算法基于周边探测数据,结合前沿点信息进行小尺度路径搜索、全局路径计算层面,利用RRT算法进行粗粒度的路径分支决策,并将已选分支的边缘信号反馈给局部路径的计算.通过RRT^(*)的重剪枝功能,能够在局部进行路径优化,而避免将其用于整体路径优化时可能带来的“选择震荡”风险.仿真实验与真实环境结果表明:将RRT*与RRT在局部和全局两种尺度上的区分使用,相较只使用RRT算法路径长度减少了16.4%.
