基于二重势函数法的集群航路规划

人工势场法由于其在构型组织能力上的不足,影响了该方法在集群航路规划上的应用,为此提出基于二重势函数法的集群航路规划法,通过第一重势能场形成集群到目标的可行路径,通过第二重势能场形成构型,从而实现集群航路规划.此外,针对人工势场法存在无谓避碰、陷阱问题等不足,通过引入碰撞危险度来确定障碍物影响距离以及虚拟障碍物,提出改进...     

Terrain-evaluation-based motion planning for legged locomotion on irregular terrain

The path planning of legged locomotion is complex in that path generation is based on constraints not only from body motion, but also from leg motion. A general approach to path planning will fail in generating a feasible path for walking machines when facing the huge searching space of legged locomotion. In this paper, an effective method of path planning is introduced by virtue of terrain evaluation. It maps obstacles into the robot configuration space by evaluating the obstacles' influence on the legged locomotion. The evaluation produces an index of terrain, called terrain complexity, for path planning. Using potential-guided searching, the terrain with mapped obstacles is searched to generate a feasible path.     

A path planning algorithm for industrial robots

Instead of using the tedious process of robot teaching, an off-line path planning algorithm has been developed for industrial robots to improve their accuracy and efficiency. Collision avoidance is the primary concept to achieve such goal. By use of the distance maps, the inspection of obstacle collision is completed and transformed to the configuration space in terms of the robot joint angles. On this configuration map, the relation between the obstacles and the robot arms is obvious. By checking the interference conditions, the collision points are indicated with marks and collected into the database. The path planning is obtained based on the assigned marked number of the passable region via wave expansion method. Depth-first search method is another approach to obtain minimum sequences to pass through. The proposed algorithm is experimented on a 6-DOF industrial robot. From the simulation results, not only the algorithm can achieve the goal of collision avoidance, but also save the manipulation steps.     

融合动态障碍物运动信息的路径规划算法

传统的路径规划算法只能在障碍物不发生位置变化的环境中计算最优路径。但是随着机器人在商场、医院、银行等动态环境下的普及,传统的路径规划算法容易与动态障碍物发生碰撞等危险。因此,关于随机动态障碍物条件下的机器人路径规划算法需要得到进一步改善。为了解决在动态环境下的机器人路径规划问题,提出了一种融合机器人与障碍物运动信息的改进动态窗口法来解决机器人在动态环境下的局部路径规划问题,并且与优化A*算法相结合来实现全局最优路径规划。主要内容体现为：在全局路径规划上,采用优化A*算法求解最优路径。在局部路径规划上,以动态障碍物的速度作为先验信息,通过对传统动态窗口法的评价函数进行扩展,实现机器人在动态环境下的自主智能避障。实验证明,该算法可以实现基于全局最优路径的实时动态避障,具体表现为可以在不干涉动态障碍物的条件下减少碰撞风险、做出智能避障且路径更加平滑、长度更短、行驶速度更快。     

Local path planning using a new artificial potential function composition and its analytical design guidelines

This paper presents a new framework for path planning based on artificial potential functions (APFs). In this scheme, the APFs for path planning have a multiplicative and additive composition between APFs for goal destination and APFs for obstacle avoidance, unlike conventional composition where the APF for obstacle avoidance is added to the APF for goal destination. In particular, this paper presents a set of analytical guidelines for designing potential functions to avoid local minima for a number of representative scenarios based on the proposed framework for path planning. Specifically the following cases are addressed: (i) a non-reachable goal problem (a case in which the potential of the goal is overwhelmed by the potential of an obstacle), (ii) an obstacle collision problem (a case in which the potential of the obstacle is overwhelmed by the potential of the goal) and (iii) a narrow passage problem (a case in which the potential of the goal is overwhelmed by the potential of two obstacles). The example results for each case show that the proposed scheme can effectively construct a path-planning system with the capability of reaching a goal and avoiding obstacles despite possible local minima.     

基于障碍物运动预测的移动机器人路径规划

针对移动机器人局部动态避障路径规划问题开展优化研究。基于动态障碍物当前历史位置轨迹,提出动态障碍物运动趋势预测算法。在移动机器人的动态避障路径规划过程中,考虑障碍物当前的位置,评估动态障碍物的移动轨迹;提出改进的D*Lite路径规划算法,大幅提升机器人动态避障算法的效率与安全性。搭建仿真验证环境,给出典型的单动态障碍物、多动态障碍物场景,对比验证了避障路径规划算法的有效性。     

机器人双手协调系统的躲避障碍问题

本文首先讨论了双手协调系统的位姿空间描述问题,包括确定自由度的维滕伯格法、位姿可达空间,以及双手协调系统躲避障碍的位姿空间法,最后提出了现实可行的仿真途径。     

A Generalized Real-Time Obstacle Avoidance Method Without the Cspace Calculation

An important concept proposed in the early stage of robot path planning field is the shrinking of a robot to a point and meanwhile the expanding of obstacles in the workspace as a set of new obstacles. The resulting grown obstacles are called the Configuration Space (Cspace) obstacles. The find-path problem is then transformed into that of finding a collision-free path for a point robot among the Cspace obstacles. However, the research experiences have shown that the Cspace transform is very hard when the following situations occur: 1) both the robot and obstacles are not polygons, and 2) the robot is allowed to rotate. This situation gets even worse when the robot and obstacles are three dimensional (3D) objects with various shapes. For this reason, direct path planning approaches without the Cspace transformation is quite useful and expected.Motivated by the practical requirements of robot path planning, a generalized constrained optimization problem (GCOP) with not only logic AND but also logic OR relationships was proposed and a mathematical solution developed previously. This paper inherits the fundamental ideas of inequality and optimization techniques from the previous work, converts the obstacle avoidance problem into a semi-infinite constrained optimization problem with the help of the mathematical transformation, and proposes a direct path planning approach without Cspace calculation, which is quite different from traditional methods. To show its merits, simulation results in 3D space have been presented.     

A dynamic priority based path planning for cooperation of multiple mobile robots in formation forming

Robots that work in a proper formation show several advantages compared to a single complex robot, such as a reduced cost, robustness, efficiency and improved performance. Existing researches focused on the method of keeping the formation shape during the motion, but usually neglect collision constraints or assume a simplified model of obstacles. This paper investigates the path planning of forming a target robot formation in a clutter environment containing unknown obstacles. The contribution lies in proposing an efficient path planner for the multiple mobile robots to achieve their goals through the clutter environment and developing a dynamic priority strategy for cooperation of robots in forming the target formation. A multirobot system is set up to verify the proposed method of robot path planning. Simulations and experiments results demonstrate that the proposed method can successfully address the collision avoidance problem as well as the formation forming problem.     

An analytically tractable potential field model of free space andits application in obstacle avoidance

An analytically tractable potential field model of free space is presented. The model assumes that the border of every two dimensional (2D) region is uniformly charged. It is shown that the potential and the resulting repulsion (force and torque) between polygonal regions can he calculated in closed form. By using the Newtonian potential function, collision avoidance between object and obstacle thus modeled is guaranteed in a path planning problem. A local planner is developed for finding object paths going through narrow areas of free space where the obstacle avoidance is most important. Simulation results show that not only does individual object configuration of a path obtained with the proposed approach avoid obstacles effectively, the configurations also connect smoothly into a path.     

基于改进蚁群算法的四足机器人步态规划

四足机器人关节众多、运动方式复杂,步态规划是四足机器人运动控制的基础。传统的算法多基于仿生原理,缺乏广泛适应性。 在建立运动学方程的基础上,提出了一种基于改进蚁群算法的步态规划算法。该算法利用了四足机器人4条腿运动的线性无关性,将步态规划问题转换为在四维空间里求取最长路径问题。仿真结果表明,该算法得出了满足约束条件的所有步态,最后通过机器人样机检验,验证了该算法求取结果的有效性和合理性。     

基于几何法的移动机器人路径规划

旨在解决动态环境中移动机器人与障碍物发生碰撞可能性的判断和避开障碍的路径规划。提出了采用几何计算的方法判断机器人和障碍物之间发生碰撞的条件,规划出机器人沿着收敛曲线运动到安全圆周,在安全圆周上作动态圆周运动,最后沿着圆弧退出圆周到达预定的避障路径。将基本的避开障碍的理论和几何算法有机地结合起来,获得了光滑的路径,提高了机器人避开障碍的效率。     

Autonomous multi-mobile robot system: simulation and implementation using fuzzy logic

In an autonomous multi-mobile robot environment, path planning and collision avoidance are important functions used to perform a given task collaboratively and cooperatively. This study considers these important and challenging problems. The proposed approach is based on a potential field method and fuzzy logic system. First, a global path planner selects the paths of the robots that minimize the potential value from each robot to its own target using a potential field. Then, a local path planner modifies the path and orientation from the global planner to avoid collisions with static and dynamic obstacles using a fuzzy logic system. In this paper, each robot independently selects its destination and considers other robots as dynamic obstacles, and there is no need to predict the motion of obstacles. This process continues until the corresponding target of each robot is found. To test this method, an autonomous multi-mobile robot simulator (AMMRS) is developed, and both simulation-based and experimental results are given. The results show that the path planning and collision avoidance strategies are effective and useful for multi-mobile robot systems.     

面向未知地图的六足机器人路径规划算法

针对移动机器人路径规划中无法准确得知全局地图的问题,提出了一种基于模糊规则和人工势场法的局部路径规划算法。首先,利用测距组与模糊规则,进行障碍物的形状分类,构建局部地图;其次,在人工势场法中引入了一种修正的斥力函数,基于局部地图,利用人工势场法进行局部路径规划;最后,随着机器人的运动,设置时间断点,以减少路径震荡。针对随机障碍物和凹凸障碍物的地图,分别采用传统人工势场法和改进的人工势场法进行仿真,其结果表明：在遇到随机障碍物时,相比传统人工势场法,改进的人工势场法能够显著减少与障碍物的碰撞;在遇到凹凸障碍物时,改进的人工势场法能够很好地完成路径规划的目标。所提算法对地形变化适应能力强,能够实现在未知地图下的六足机器人路径规划。     

Velocity potential approach to path planning for avoiding moving obstacles

This paper describes the theory and an experiment of a velocity potential approach to path planning and avoiding moving obstacles for an autonomous mobile robot by use of the Laplace potential. This new navigation function for path planning is feasible for guiding a mobile robot avoiding arbitrarily moving obstacles and reaching the goal in real time. The essential feature of the navigation function comes from the introduction of fluid flow dynamics into the path planning. The experiment is conducted to verify the effectiveness of the navigation function for obstacle avoidance in a real world. Two examples of the experiment are presented; first, the avoidance of a moving obstacle in parallel line-bounded space, and second, the avoidance of one moving obstacle and another standing obstacle. The robot can reach the goal after successfully avoiding the obstacles in these cases.     

Generic Motion Planner for Robot Multi-fingered Manipulation

This paper addresses the dexterous manipulation planning problem, which deals with motion planning for a multi-fingered hand manipulating objects among static obstacles, under quasi-static movement assumption. We propose a general manipulation approach able to compute object and finger trajectories, as well as the finger relocation sequence, in order to link any two given configurations of the composite system hand + object. It relies on a topological property that characterizes the existence of solutions in the subspace of configurations where the object is grasped by the n fingers. This property helps reduce the problem by structuring the search space. The developed planner captures in a probabilistic roadmap the connectivity of submanifolds of the composite configuration space. The answer to the manipulation planning query is then given by searching a path in the computed graph. Simulation experiments are reported for different multi-fingered manipulation task examples showing the efficiency of the proposed method.     

固定翼无人机在线航迹规划方法

在不确定环境下,针对固定翼无人机（UAV）航迹规划问题,提出了一种基于滚动时域控制的模糊粒子群优化算法与改进人工势场法相结合的在线航迹规划方法。首先,对凸多边形障碍物进行最小外接圆拟合;然后,根据静态威胁,将规划问题转化为一系列时域窗口内的在线子问题,利用模糊粒子群算法实时优化求解以实现静态避障;当环境中存在动态威胁时,使用改进人工势场法对航迹进行调整完成动态避障。为了满足固定翼无人机的动态约束,同时提出固定翼UAV的碰撞检测法,可提前判断障碍物是否为真正威胁源,以此减少转弯频率和幅度,降低飞行代价。仿真实验结果表明,所提方法在固定翼UAV航迹规划中能有效提升规划速度、稳定性与实时避障能力,且克服了传统人工势场容易陷入局部最优的缺点。     

Collision avoidance for Robot manipulators: Application to Catia/IBM 7565 interface

A collision avoidance algorithm has been developed to augment the capability of an automatic (off-line) robot path planning (programming) tool. The use of off-line programming tools for robot task programming is becoming increasingly important, but the advantages to be gained by off-line programming may be lost if collision-free path planning capabilities are not included. This article addressed the problem of collision-free path planning in the context of a gantry type robot. The collision avoidance algorithm described here uses the <heuristic approach> to collision-free path planning. The manipulator and obstacles are modeled as spheres to simplify tests for collision. An important feature of this algorithm is that it permits the manipulation of objects in the robot's environment. When compared against an algorithm from the literature, given a lightly cluttered environment modelled by spheres, the new algorithm finds a collision-free path much faster. This new algorithm has been implemented as part of the CATIA/IBM 7565 interface which forms an automatic off-line programming system for the IBM 7565 robot. It has also been implemented as a supervisory collision filter to allow collision-free control of the robot from the operator's console. In both cases the algorithm has been demonstrated to provide efficient and effective collision avoidance for the IBM 7565 robot.     

六轴工业机器人先验引导RRT*避障轨迹算法研究

针对六轴工业机器人装配避障路径运动问题,研究了机器人整体避障运动路径规划方法,提出一种RRT*改进算法;算法以RRT*算法为基础,在障碍物建模中引入包围盒算法,加入对机器人各轴与障碍物的碰撞检测;在路径规划中加入对随机点生成方向与树枝生长方向的先验引导机制,优化了算法路径长度与路径搜寻效率;通过Matlab进行了试验验证,结果表明与标准RRT*算法相比,先验引导RRT*算法缩短路径长度14%左右,且满足机器人末端路径与手臂各轴的避障需求。