Time-optimal control of multiple cooperating manipulators with trajectory and motion program constraints

Two types of problems associated with time-optimal control of multiple manipulators moving a commonly held object along specified trajectories are studied. The first problem involves finding the minimum traveling time and the optimal control torques for any desired motion programs of the given trajectory. The second problem involves finding the optimal velocity distribution along the trajectory such that the motion can be completed in the minimum time. To solve these problems, a parametric form of the generalized dynamic equation is derived. An iterative search procedure is developed for solving the first problem. During the search, the lower bound of the traveling time at any point of the given trajectory is determined by using the linear programming technique. The second problem is solved by integrating the parametric dynamic equation along the given trajectory based on the phase-plane switching curve approach. The maximum acceleration and the upper bound of the operation speed at each integration instance are determined from two linear programs. The proposed methods are applicable to various complex multi-robot systems and can handle nonlinear torque-speed characteristics of the joint actuators. © 1996 John Wiley & Sons, Inc.     

移动机器人全覆盖路径规划优化方法

从全局优化的角度出发,提出一种基于子区域分割的环境建模方法,将各个子区域缩成节点、子区域重心间距离缩成节点间连线,建立起含障区域的全连通图——广义距离矩阵模型,对Hopfield神经网络求解旅行商问题的动态规划方法进行改进后,将其用于求该模型的最优有向连通图。机器人沿最短路径完成覆盖,就是按最优顺序走过连通图中所有节点并依次覆盖各节点所代表的子区域,从而完成移动机器人在含障区域内的全覆盖路径规划问题的优化解决方案。     

An efficient algorithm for optimal routing applied to convoy merging manoeuvres in urban environments

This paper describes an innovative routing strategy for intelligent transportation units willing to perform merging manoeuvres with a moving convoy. In particular, we consider a transportation unit located inside a city (pursuer unit), and which wishes to join a convoy that is constantly moving around the city. We first describe a solution that considers idealistic conditions, i.e., the traveling time along each street is constant. We then go on to improve our first approach to deal with the realistic random nature of the traveling times experienced by the pursuer and by the convoy leader. Our search strategy applies Dynamic Programming to achieve a meeting point that is optimal in two ways: on one hand, the optimal destination is the one closest to the current pursuer??s position; on the other hand, the optimal meeting point must minimize the time that elapses until the pursuer meets the convoy (considering that the pursuer must always arrive first). Calculating the optimal path to every possible destination is highly inefficient, error prone and time consuming. On the contrary, we propose an efficient search strategy that will achieve the meeting point and the path to it, both optimally and in a very short time. This enables the real-time application of our approach either for finding new solutions or for re-planning old ones owing to unexpected real-conditions.     

Internet访问时间的混沌性解析

以CAIDA组织授权的海量数据为样本空间,利用相空间重构技术以及G-P算法,对时间维的Internet访问时间进行相空间重构,得到其混沌吸引子饱和关联维数为2.8308,证实Internet访问时间的演化过程具有混沌特征.在此基础上,根据关联维数及奇怪吸引子在相空间混沌轨道运动的特性,提出了三维微分方程组的Internet访问时间长期预测模型.     

Approximation Algorithms for the Traveling Repairman and Speeding Deliveryman Problems

Constant-factor, polynomial-time approximation algorithms are presented for two variations of the traveling salesman problem with time windows. In the first variation, the traveling repairman problem, the goal is to find a path that visits the maximum possible number of locations during their time windows. In the second variation, the speeding deliveryman problem, the goal is to find a path that uses the minimum possible speedup to visit all locations during their time windows. For both variations, the time windows are of unit length, and the distance metric is based on a weighted, undirected graph. Algorithms with improved approximation ratios are given for the case when the input is defined on a tree rather than a general graph. The algorithms are also extended to handle time windows whose lengths fall in any bounded range.     

智能吸尘器全覆盖遍历路径规划及仿真实现

分析了常用的全覆盖遍历路径算法,提出了基于区域分割的全覆盖遍历路径规划的实现方案:首先智能吸尘器沿着水平与垂直路线扫描房间,将房间分成若干无障碍的小区域,然后以图的深度优先搜索算法确定这些小区域的衔接顺序,并在这些小区域内以螺旋收缩算法进行遍历。在实验室环境内,在智能吸尘器最小系统上,通过实验验证了提出的全覆盖遍历路径规划。实验主要分为4项:走直线、直角转弯、子区域内螺旋行走、子区域衔接,实验证明智能吸尘器在给定的环境下,能够按照预想的效果进行遍历。     

A time-scaling method for near-time-optimal control of an omni-directional robot along specified paths

This paper proposes a time-scaling method to determine the near-time-optimal movement of an omnidirectional mobile robot along a given reference path. With this strategy, the positions of the trajectory after scaling are the same as the original ones such that the geometric path constraints are not violated. However, the velocities and the accelerations are adjusted to meet the dynamical constraints and to minimize the traveling time. When determining the time-scaling function, a cubic spline interpolation technique is used, in which control points for interpolation are determined simultaneously by a particle swarm optimization (PSO) method based on the integration of a time-scaling function. To show the feasibility of the proposed method, the results of a simulation example is illustrated. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Fuzzy Connected Object Delineation: Axiomatic Path Strength Definition and the Case of Multiple Seeds

This paper presents an extension of previously published theory and algorithms for object definition based on fuzzy connectedness. In this approach, a strength of connectedness is assigned between every pair of image elements. This is done by finding the strongest among all possible connecting paths between the two elements in each pair. The strength assigned to a particular path is defined as the weakest affinity between successive pairs of elements along the path. Affinity specifies the degree to which elements hang together locally in the image and is determined considering how close the elements are in space and in intensity features. A fuzzy connected object containing a particular seed element specified within the object is computed via dynamic programming. In all reported works so far, the minimum of affinities has been considered to define path strength and the maximum of path strengths has been used to define fuzzy connectedness. The question thus remained all along as to whether there are other valid formulations for fuzzy connectedness. One of the main contributions of this paper is a theoretical investigation under reasonable axioms to establish that maximum of path strengths of minimum of affinities along each path is indeed the one and only valid choice for defining fuzzy connectedness. In the past, a single fuzzy connected object was specified through a single seed element indicated interactively within the object region. When many objects are to be identified in a single image, interactive seed specification becomes cumbersome. Further, selecting exactly one element in each region automatically is more difficult than identifying a set of elements. Hence the theory and algorithms for the single-element case need to be generalized to multiple elements for more effective practical use. This is the second main contribution of this paper. The importance of multiple seeded fuzzy connected object definition from the considerations of both practicality and automation in image segmentation are described and illustrated with examples taken from several real medical applications.     

A Direct Manipulation Interface for 3D Computer Animation

We present a new set of interface techniques for visualizing and editing animation directly in a single three-dimensional scene. Motion is edited using direct-manipulation tools which satisfy high-level goals such as “reach this point at this time” or “go faster at this moment”. These tools can be applied over an arbitrary temporal range and maintain arbitrary degrees of spatial and temporal continuity. We separate spatial and temporal control of position by using two curves for each animated object: the motion path which describes the 3D spatial path along which an object travels, and the motion graph, a function describing the distance traveled along this curve over time. Our direct-manipulation tools are implemented using displacement functions, a straightforward and scalable technique for satisfying motion constraints by composition of the displacement function with the motion graph or motion path. This paper will focus on applying displacement functions to positional change. However, the techniques presented are applicable to the animation of orientation, color, or any other attribute that varies over time.     

工业机器人时间最优轨迹规划及轨迹控制的理论与实验研究

提出了一种用于工业机器人时间最优轨迹规划及轨迹控制的新方法, 它可以确保在关节位移、速度、加速度以及二阶加速度边界值的约束下, 机器人手部沿笛卡尔空间中规定路径运动的时间最短. 在这种方法中, 所规划的关节轨迹都采用二次多项式加余弦函数的形式, 不仅可以保证各关节运动的位移、速度、加速度连续而且还可以保证各关节运动的二阶加速度连续. 采用这种方法, 既可以提高机器人的工作效率又可以延长机器人的工作寿命. 以PUMA 5 6 0机器人为对象进行了计算机仿真和机器人实验, 结果表明这种方法是正确和有效的. 它为工业机器人在非线性运动学约束条件下的时间最优轨迹规划及控制问题提供了一种较好的解决方案.     

各向异性传感环境下的移动对象反监控算法

研究异构传感环境下移动对象的反监控问题,提出一种暴露模型,该模型可用于近似估算移动对象穿越各向异性传感器网络时的风险.并在此基础上,结合各向异性Voronoi图提出了一种路径判定算法,该算法能够保障移动对象选择一条具有近似最小风险的路径穿越各向异性传感器网络区域.理论分析和实验结果表明,算法具有良好的反监控性能.另外,算法只需知道移动对象侦测半径之内的局部信息,因此也具有分布式和实用性等良好特性.     

可移动各向异性传感器网络的反监控算法

研究移动目标在可移动传感环境下的反监控问题,设计一种新的暴露模型,用于估计布置了大量可移动各向异性传感器节点的区域中,目标沿路径进行穿越时的暴露程度。基于该模型,利用各向异性Voronoi网格,提出一种判决算法,该算法使目标穿越监控区域时,可以选择合适的、暴露程度较小的穿越路径。理论分析和实验结果表明,该算法实用性和可靠性较高。     

面向迁移实例旅行图动态适应性的目录服务研究*

迁移工作流是一种基于迁移实例在工作位置之间连续迁移并就地利用位置服务执行任务的工作流管理模式,许可的工作位置及迁移顺序由预先规划的旅行图约定。针对一旦工作位置故障或服务发生变化,预先规划的迁移路线就不能实现,从而影响迁移工作流的可靠执行,提出了一种分布式目录服务结构。该结构通过对目录服务组件的设计,不仅支持迁移实例旅行图的静态规划,而且支持基于服务推荐的迁移路线的动态修正,从而大大提高了迁移实例旅行图的动态适应性。     

遗传算法在快速成形轮廓路径规划中的应用

以减少层片扫描中的空程运行时间为轮廓路径优化的目标,以轮廓路径与经典旅行商问题之优化的共性和不同为比对,在采用遗传算法实现快速成形轮廓路径的优化中,将轮廓路径的特点灵活应用到该算法的各个步骤中,有效地缩短了扫描路径中的空程距离,从而有利于提高成形速度和成形质量．     

Hybrid control systems and the dynamic traveling salesman problem

A new approximate algorithm for solving the dynamic traveling salesman problem (DTSP) is proposed; the traveling salesman starting from the base city visits megapoleis and cities inside megapoleis and comes back to the base city. A specific feature of this variant of DTSP is the movement of cities inside megapoleis in time. To solve this problem, a general solution theory for hybrid (complicated) systems with “combinatorial” and “continuous” path segments is developed. The general theory is based on the sufficient optimality conditions known in the theory of optimal control.     

Minimum distance collision-free path planning for industrial robots with a prismatic joint

A collision-free path is a path which an industrial robot can physically take while traveling from one location to another in an environment containing obstacles. Usually the obstacles are expanded to compensate for the body width of the robot. For robots with a prismatic joint, which allows only a translational motion along its axis, additional problems created by the long boom are handled by means of pseudoobstacles which are generated by real obstacle's edges and faces. The environment is then modified by the inclusion of pseudoobstacles which contribute to the forbidden regions. This process allows the robot itself again to be represented by a point specifying the location of its end effector in space. An algorithm for determining the shortest distance collision-free path given a sequence of edges to be traversed has been developed for the case of stationary obstacles.     

基于微粒群算法的城市公交线网模型研究

微粒群算法是求解组合优化问题的一种新的群体智能进化算法,从城市公交乘客选择出行路径的决策因素出发,以微粒群算法进化机理为核心,结合微粒群进化算法中的局部搜索与全局搜索同时进行的优点和运筹学旅行商组合优化理论,系统地建立了规划城市智能交通公交线网最短路径的数学模型进化算法,并通过MATLAB 7.0进行了实例仿真,得到了城市公交线网出行选择模型中总运输里程权重最短的优化目标。仿真结果也表明,该进化算法模型是解决城市公交线网规划的有效方法。     

传感环境下基于局部Voronoi图的启发式反监控路径发现算法

针对移动对象通过传感区域时的安全问题,提出了一种基于局部Voronoi图(VT)的启发式反监控路径发现算法.首先,给出了一种基于局部Voronoi图的路径暴露风险近似估算模型.在该模型中,移动目标可依据当前探测到的传感器节点位置信息动态生成局部Voronoi图,并可依据定义的暴露风险计算公式近似估算出局部Voronoi图中各条边所对应路径的暴露风险.然后,在此基础上设计并实现了一种启发式的反监控路径发现算法.在该算法中,移动目标可首先基于局部Voronoi图确定自己的下一跳位置点候选集,然后再基于定义的启发式代价函数从候选集中选择一个风险代价最小的位置点作为其下一跳目标位置点.最后,沿着局部Voronoi图中对应的最小暴露风险路径移动到该目标位置点.理论分析和实验结果表明,所提算法具有良好的反监控性能,针对部署有n个传感器节点的区域,能够使得移动对象在不超过O(n log n)的时间内快速找到一条具有较低暴露风险的路径来穿越整个传感区域.     

35kV输电线路故障行波特征及传输特性仿真研究

目前行波精确定位技术在35kV系统应用还不够成熟,故障行波特征及传输规律有待进一步深入研究。论文以一条35kV输电线路为研究对象,首先分析了传统解耦技术在短距不对称35kV线路上的适用性,然后建立全电磁暂态仿真模型,模拟了典型反击、绕击、金属性接地以及高阻接地故障过程,分析了行波特征及传输规律,并研究了不同传输距离下各模量行波传输衰减规律,最后分析了各模量行波在故障定位中的应用。研究结果表明,不同故障下行波特征差异明显,其中雷击波形幅值大、波尾时间小于20μs,而非雷击则大于40μs;随着传输距离增加,各模量行波幅值均呈降低,波头及波尾时间增加,且在前10km内传输衰减最快;各模量行波应用于故障定位时定位误差均小于5%。     

Evolutionary Path Planning Algorithm for Industrial Robots

This paper proposed a new methodology to solve collision free path planning problem for industrial robot using genetic algorithms. The method poses an optimization problem that aims to minimize the significant points traveling distance of the robot. The behavior of more two operational parameters – the end effector traveling distance and computational time – are analyzed. This algorithm is able to obtain the solution for any industrial robot working in the complex environments, just it needs to choose a suitable significant points for that robot. An application example has been illustrated using robot Puma 560.