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
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
针对六自由度工业机器人在复杂的分拣环境中分拣速度慢、避障效果差等问题,提出了一种融合人工势场(Artificial Potential Field,APF)算法的快速扩展随机树(Rapidly-exploring Random Tree,RRT)改进算法。传统RRT算法路径规划随机性强...针对六自由度工业机器人在复杂的分拣环境中分拣速度慢、避障效果差等问题,提出了一种融合人工势场(Artificial Potential Field,APF)算法的快速扩展随机树(Rapidly-exploring Random Tree,RRT)改进算法。传统RRT算法路径规划随机性强、收敛速度慢,在该算法中引入APF机制引导其向目标点进行有效扩展,减少路径搜索过程中的无效分支,提高搜索效率;优化对父系节点的选择策略,对原路径局部节点进行优化重连,提高路径质量及平滑性。根据实际分拣中可能出现的状况,在MATLAB软件中建立了3个不同的仿真场景,并将所提出的改进APF-RRT算法与传统RRT算法、APF-RRT算法进行对比仿真实验。结果表明,改进APF-RRT算法于不同分拣环境中,在路径长度、搜索时间、节点个数和迭代次数4个指标上均有一定提升,能以更高的效率搜索到更高质量的路径。展开更多
很多工业企业因为负荷的原因导致电能质量很差,对自己的生产造成影响的同时也对公共电网造成污染。APF设备不仅可以治理企业自身的电能质量,同时也会给企业的节能降耗带来经济效益,帮助企业绿色低碳转型和高质量发展。APF(Active Power ...很多工业企业因为负荷的原因导致电能质量很差,对自己的生产造成影响的同时也对公共电网造成污染。APF设备不仅可以治理企业自身的电能质量,同时也会给企业的节能降耗带来经济效益,帮助企业绿色低碳转型和高质量发展。APF(Active Power Filter有源电力滤波器)。展开更多
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。
文摘针对六自由度工业机器人在复杂的分拣环境中分拣速度慢、避障效果差等问题,提出了一种融合人工势场(Artificial Potential Field,APF)算法的快速扩展随机树(Rapidly-exploring Random Tree,RRT)改进算法。传统RRT算法路径规划随机性强、收敛速度慢,在该算法中引入APF机制引导其向目标点进行有效扩展,减少路径搜索过程中的无效分支,提高搜索效率;优化对父系节点的选择策略,对原路径局部节点进行优化重连,提高路径质量及平滑性。根据实际分拣中可能出现的状况,在MATLAB软件中建立了3个不同的仿真场景,并将所提出的改进APF-RRT算法与传统RRT算法、APF-RRT算法进行对比仿真实验。结果表明,改进APF-RRT算法于不同分拣环境中,在路径长度、搜索时间、节点个数和迭代次数4个指标上均有一定提升,能以更高的效率搜索到更高质量的路径。
