针对传统路径规划算法在三维复杂障碍物环境下规划效率低和搜索路径质量不足的缺点,提出一种自适应APF-RRT^(*)路径规划方法。在势力场作用下引导路径节点以不同步长动态生长,以解决传统快速扩展随机树(rapidly-exploring random tree s...针对传统路径规划算法在三维复杂障碍物环境下规划效率低和搜索路径质量不足的缺点,提出一种自适应APF-RRT^(*)路径规划方法。在势力场作用下引导路径节点以不同步长动态生长,以解决传统快速扩展随机树(rapidly-exploring random tree star, RRT^(*))算法盲目搜索和人工势场法(artificial potential field, APF)易陷入局部最优的问题;通过定义父节点重选流程和引入动态偏向采样概率,优化算法迭代过程;对已有路径进行贪心算法迭代优化与平滑处理,减少路径冗余节点,增强实际使用效果。经过实验验证,对比其他2种算法,自适应APF-RRT^(*)算法在不同环境上的迭代次数、耗时、路径长度均得到减少;将该方法用于UR5机械臂上进行仿真验证,机械臂能够实现良好的避障功能,平稳完成路径规划任务。展开更多
Rapidly-exploring Random Tree(RRT)and its variants have become foundational in path-planning research,yet in complex three-dimensional off-road environments their uniform blind sampling and limited safety guarantees l...Rapidly-exploring Random Tree(RRT)and its variants have become foundational in path-planning research,yet in complex three-dimensional off-road environments their uniform blind sampling and limited safety guarantees lead to slow convergence and force an unfavorable trade-off between path quality and traversal safety.To address these challenges,we introduce HS-APF-RRT*,a novel algorithm that fuses layered sampling,an enhanced Artificial Potential Field(APF),and a dynamic neighborhood-expansion mechanism.First,the workspace is hierarchically partitioned into macro,meso,and micro sampling layers,progressively biasing random samples toward safer,lower-energy regions.Second,we augment the traditional APF by incorporating a slope-dependent repulsive term,enabling stronger avoidance of steep obstacles.Third,a dynamic expansion strategy adaptively switches between 8 and 16 connected neighborhoods based on local obstacle density,striking an effective balance between search efficiency and collision-avoidance precision.In simulated off-road scenarios,HS-APF-RRT*is benchmarked against RRT*,GoalBiased RRT*,and APF-RRT*,and demonstrates significantly faster convergence,lower path-energy consumption,and enhanced safety margins.展开更多
为加快末端物流配送的效率,提出一种配送无人机的航迹规划问题。针对传统快速搜索随机树(rapidlysearch random tree,RRT)算法在航迹规划中存在的盲目性和路径不平滑等问题,将人工势场法(artificial potential field,APF)与Informed-RRT...为加快末端物流配送的效率,提出一种配送无人机的航迹规划问题。针对传统快速搜索随机树(rapidlysearch random tree,RRT)算法在航迹规划中存在的盲目性和路径不平滑等问题,将人工势场法(artificial potential field,APF)与Informed-RRT^(*)算法融合,提出一种自适应步长增长策略的改进APF-Informed-RRT^(*)算法。首先在选择新节点时,考虑到障碍物和目标点的影响,提出一种自适应步长增长策略来解决采样的盲目性;其次采用三次B样条对拐点处进行平滑处理;最后分别采用RRT^(*)算法、Informed-RRT^(*)算法和改进APF-Informed-RRT^(*)算法在两种环境中进行仿真实验。结果表明,改进APF-Informed-RRT^(*)算法相较于RRT^(*)算法和Informed-RRT^(*)算法,在运行时间、迭代次数以及路径平滑上都得到提升。展开更多
由于微电网中分布式电源的间歇性、非线性负荷增减频繁等原因,导致谐波能量变化较大,采用多台并联运行的有源电力滤波器APF(active power filter)能够对微电网谐波进行有效治理。然而,多台APF并联运行会因各APF补偿的电流不均而形成环流...由于微电网中分布式电源的间歇性、非线性负荷增减频繁等原因,导致谐波能量变化较大,采用多台并联运行的有源电力滤波器APF(active power filter)能够对微电网谐波进行有效治理。然而,多台APF并联运行会因各APF补偿的电流不均而形成环流,从而导致系统损耗增加。为此,本文提出1种基于电能信息一体化传输技术的均流控制方法,通过在逆变器功率调制环节加入信息调制,实现电能变换的同时传递关键信息,完成并联系统的均流控制。相较于传统的集中式、主从式控制方法,本文提出的方法无需额外的通信设备和通信线路,可进一步提高系统的可靠性、灵活性和可扩展性。通过RT-LAB仿真实验验证了所提均流控制方法的可行性与有效性。展开更多
文摘针对传统路径规划算法在三维复杂障碍物环境下规划效率低和搜索路径质量不足的缺点,提出一种自适应APF-RRT^(*)路径规划方法。在势力场作用下引导路径节点以不同步长动态生长,以解决传统快速扩展随机树(rapidly-exploring random tree star, RRT^(*))算法盲目搜索和人工势场法(artificial potential field, APF)易陷入局部最优的问题;通过定义父节点重选流程和引入动态偏向采样概率,优化算法迭代过程;对已有路径进行贪心算法迭代优化与平滑处理,减少路径冗余节点,增强实际使用效果。经过实验验证,对比其他2种算法,自适应APF-RRT^(*)算法在不同环境上的迭代次数、耗时、路径长度均得到减少;将该方法用于UR5机械臂上进行仿真验证,机械臂能够实现良好的避障功能,平稳完成路径规划任务。
基金supported in part by 14th Five Year National Key R&D Program Project(Project Number:2023YFB3211001)the National Natural Science Foundation of China(62273339,U24A201397).
文摘Rapidly-exploring Random Tree(RRT)and its variants have become foundational in path-planning research,yet in complex three-dimensional off-road environments their uniform blind sampling and limited safety guarantees lead to slow convergence and force an unfavorable trade-off between path quality and traversal safety.To address these challenges,we introduce HS-APF-RRT*,a novel algorithm that fuses layered sampling,an enhanced Artificial Potential Field(APF),and a dynamic neighborhood-expansion mechanism.First,the workspace is hierarchically partitioned into macro,meso,and micro sampling layers,progressively biasing random samples toward safer,lower-energy regions.Second,we augment the traditional APF by incorporating a slope-dependent repulsive term,enabling stronger avoidance of steep obstacles.Third,a dynamic expansion strategy adaptively switches between 8 and 16 connected neighborhoods based on local obstacle density,striking an effective balance between search efficiency and collision-avoidance precision.In simulated off-road scenarios,HS-APF-RRT*is benchmarked against RRT*,GoalBiased RRT*,and APF-RRT*,and demonstrates significantly faster convergence,lower path-energy consumption,and enhanced safety margins.
文摘为加快末端物流配送的效率,提出一种配送无人机的航迹规划问题。针对传统快速搜索随机树(rapidlysearch random tree,RRT)算法在航迹规划中存在的盲目性和路径不平滑等问题,将人工势场法(artificial potential field,APF)与Informed-RRT^(*)算法融合,提出一种自适应步长增长策略的改进APF-Informed-RRT^(*)算法。首先在选择新节点时,考虑到障碍物和目标点的影响,提出一种自适应步长增长策略来解决采样的盲目性;其次采用三次B样条对拐点处进行平滑处理;最后分别采用RRT^(*)算法、Informed-RRT^(*)算法和改进APF-Informed-RRT^(*)算法在两种环境中进行仿真实验。结果表明,改进APF-Informed-RRT^(*)算法相较于RRT^(*)算法和Informed-RRT^(*)算法,在运行时间、迭代次数以及路径平滑上都得到提升。
文摘由于微电网中分布式电源的间歇性、非线性负荷增减频繁等原因,导致谐波能量变化较大,采用多台并联运行的有源电力滤波器APF(active power filter)能够对微电网谐波进行有效治理。然而,多台APF并联运行会因各APF补偿的电流不均而形成环流,从而导致系统损耗增加。为此,本文提出1种基于电能信息一体化传输技术的均流控制方法,通过在逆变器功率调制环节加入信息调制,实现电能变换的同时传递关键信息,完成并联系统的均流控制。相较于传统的集中式、主从式控制方法,本文提出的方法无需额外的通信设备和通信线路,可进一步提高系统的可靠性、灵活性和可扩展性。通过RT-LAB仿真实验验证了所提均流控制方法的可行性与有效性。
