Laser interferometry-based guidance methodology for high precision positioning of mechanisms and robots

Laser interferometry-based sensing and measurement (LISM) technique was originally investigated to perform dynamic measurements of the end effector of a robot manipulator in motion. This technique can provide dynamic position measurements in real time and has high accuracy, large working space, high sampling rate and automatic target tracking. In this paper, a methodology using LISM technique is proposed to perform laser interferometry-based guidance (LIG) for accurate positioning of a robot manipulator in high precision manufacturing operations. The methodology utilizes the LISM apparatus to guide the robot's end effector to a desired location or along a desired path by directing the robot to follow the trajectory mapped by the laser beam. This is accomplished through the establishment of techniques for path generation, sensing and data acquisition and guidance error determination and compensation in the control algorithm. The algorithms for this methodology, together with the measurement and analysis techniques are described. A number of experiments are carried out to examine and validate the proposed LIG technique. Experimental results show that the established technique can effectively improve the positioning accuracy of the robot manipulator.     

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.     

To push or not to push: on the rearrangement of movable objects bya mobile robot

We formulate and address the problem of planning a pushing manipulation by a mobile robot which tries to rearrange several movable objects in its work space. We present an algorithm which, when given a set of goal configurations, plans a pushing path to the "cheapest" goal or announces that no such path exists. Our method provides detailed manipulation plans, including any intermediate motion of the pusher while changing contact configuration with the pushed movables. Given a pushing problem, a pushing path is found using a two-phase procedure: a context sensitive back propagation of a cost function which maps the configuration space, and a gradient descent phase which builds the pushing path. Both phases are based on a dynamic neighborhood filter which constrains each step to consider only admissible neighboring configurations. This admissibility mechanism provides a primary tool for expressing the special characteristics of the pushing manipulation. It also allows for a full integration of any geometrical constraints imposed by the pushing robot, the pushed movables and the environment. We prove optimality and completeness of our algorithm and give some experimental results in different scenarios.     

Collision-avoidance trajectory planning using tube concept: Analysis and simulation

The concept of a tube is introduced and is applied to the solving of the collision-avoidance, minimum-time trajectory planning problem. A collision-free space is represented by an articulated tube with parameters of reference points and path tolerances. For obstacle avoidance, the end effector is constrained to move inside of the tube. An algorithm which will find suboptimal solutions for optimizing both path and velocity history of the trajectory by the use of piecewise joint-space polynomials is presented. This algorithm exploits the robot arm dynamics in realistic environments where obstacles are present and the minimization of task time is desired with smooth motion. Experimental results show that as the path tolerance increases the new algorithm takes advantage of the spatial freedom to provide solutions superior to conventional approaches and to methods based on predefined paths.     

An Automated Method to Calibrate Industrial Robots Using a Virtual Closed Kinematic Chain

This paper describes an industrial robot calibration algorithm called the virtual closed kinematic chain method. Current robot kinematic calibration methods use measurements of position and orientation of the end effector. The accuracy of these measurements is limited by the resolution of the measuring equipment. In the proposed method, a laser pointer tool, attached to the robot's end effector, aims at a constant but unknown location on a fixed object, effectively creating a virtual 7 DOFs closed kinematic chain. As a result, small variations in position and orientation of the end effector are magnified on the distant object. Hence, the resolution of observations is improved, increasing the accuracy of joint angle measurements that are required to calibrate the robot. The method is verified using both simulation and real experiments. It is also shown in simulation that the method can be automated by a feedback system that can be implemented in real time. The accuracy of the robot after using the proposed calibration procedure is measured by aiming at an arbitrary fixed point and measuring the mean and standard deviation of the radius of spread of the projected points. The mean and standard deviation of the radius of spread were improved from 5.64 and 1.89 mm to 1.05 and 0.587 mm, respectively.     

Planning of collision-free paths for a reconfigurable dual manipulator equipped mobile robot

In this paper, we study the problem of finding a collision-free path for a mobile robot which possesses manipulators. The task of the robot is to carry a polygonal object from a starting point to a destination point in a possibly culttered environment. In most of the existing research on robot path planning, a mobile robot is approximated by a fixed shape, i.e., a circle or a polygon. In our task planner, the robot is allowed to change configurations for avoiding collision. This path planner operates using two algorithms: the collision-free feasible configuration finding algorithm and the collision-free path finding algorithm. The collision-free feasible configuration finding algorithm finds all collision-free feasible configurations for the robot when the position of the carried object is given. The collision-free path finding algorithm generates some candidate paths first and then uses a graph search method to find a collision-free path from all the collision-free feasible configurations along the candidate paths. The proposed algorithms can deal with a cluttered environment and is guaranteed to find a solution if one exists.     

Multi-objective approach for robot motion planning in search tasks

This work addresses the problem of single robot coverage and exploration in an environment with the goal of finding a specific object previously known to the robot. As limited time is a constraint of interest we cannot search from an infinite number of points. Thus, we propose a multi-objective approach for such search tasks in which we first search for a good set of positions to place the robot sensors in order to acquire information from the environment and to locate the desired object. Given the interesting properties of the Generalized Voronoi Diagram, we restrict the candidate search points along this roadmap. We redefine the problem of finding these search points as a multi-objective optimization one. NSGA-II is used as the search engine and ELECTRE I is applied as a decision making tool to decide among the trade-off alternatives. We also solve a Chinese Postman Problem to optimize the path followed by the robot in order to visit the computed search points. Simulation results show a comparison between the solution found by our method and solutions defined by other known approaches. Finally, a real robot experiment indicates the applicability of our method in practical scenarios.     

An adaptive-learning algorithm to solve the inverse kinematics problem of a 6 D.O.F serial robot manipulator

An adoptive learning strategy using an artificial neural network ANN has been proposed here to control the motion of a 6 D.O.F manipulator robot and to overcome the inverse kinematics problem, which are mainly singularities and uncertainties in arm configurations. In this approach a network have been trained to learn a desired set of joint angles positions from a given set of end effector positions, experimental results has shown an excellent mapping over the working area of the robot, to validate the ability of the designed network to make prediction and well generalization for any set of data, a new training using different data set has been performed using the same network, experimental results has shown a good generalization for the new data sets.The proposed control technique does not require any prior knowledge of the kinematics model of the system being controlled, the basic idea of this concept is the use of the ANN to learn the characteristics of the robot system rather than to specify explicit robot system model. Any modification in the physical set-up of the robot such as the addition of a new tool would only require training for a new path without the need for any major system software modification, which is a significant advantage of using neural network technology.     

基于虚拟子目标点的移动机器入路径规划

传统的反应式路径规划算法有时会出现＂死锁现象＂,为此设计了一种基于虚拟子目标点的移动机器人路径规划算法。首先根据已知的环境信息生成一条连接初始点和目标点的全局路径,移动机器人在沿全局路径行走时通过传感器探测周围的实时环境信息并寻找障碍物的转弯处,然后在该障碍物的转弯处设置虚拟子目标点,根据虚拟子目标点构建局部路径,机器人沿着局部路径走到该子目标点并进入下一个路径规划循环。仿真结果验证了该算法的有效性。     

An improved trajectory planner for redundant manipulators in constrained workspace

This article studies the trajectory planning of redundant robots performing tasks within an enclosed workspace. Configuration control of kinematically redundant manipulators using the pseudo‐inverse with null‐space projection method is a well‐known scheme. One advantage of this method is that the gradient of an objective function can be included in the homogeneous term to optimize the objective function without affecting the position of the end‐effector. Using different objective functions, this method can achieve redundancy resolution such as obstacle or joint limits avoidance. Along this line of redundancy resolution, a switching objective function is proposed. We modify Liegeois' joint angle availability objective function so that the midpoints of each joint are switched at a series of prespecified key path points for the end‐effector to achieve. These key path points are planned beforehand according to the geometry of the constrained workspace. The trajectory planning problem can then be viewed as a series of proper postures (i.e., midpoints) determination problems at the key path points. The proper postures are determined using a combination of the potential field method and the elastic model method that takes into account joint operating ranges and the motion tendency of the end‐effector. A variable weighting technique to achieve the proper postures effectively is also presented. Simulations of a planar eight‐link robot in a constrained workspace illustrate the effectiveness of the switching objective function with the variable weighting approach in trajectory planning problems. ©1999 John Wiley & Sons, Inc.     

基于非均匀环境建模与三阶Bezier曲线的平滑路径规划

针对工作于复杂环境下的大型工装,本文提出了一种基于非均匀环境建模与三阶Bezier曲线的平滑路径规划算法,以指导工装的运动.在环境建模方面,利用四叉树建立环境的非均匀模型,能够有效压缩环境信息,提高搜索效率;在路径搜索方面,以非均匀环境模型为基础,提出一种距离启发搜索和信息素混合更新的蚁群算法,能够得到工装的安全可行路径点;在路径平滑方面,基于三阶Bezier曲线,提出能够连接任意位置和任意方向两点的转弯单元的设计方法,利用转弯单元连接路径搜索算法得到的路径点,能够获得满足工装非完整性约束的平滑路径.最后,以大型激光驱动器的靶场环境为对象,对本文算法的有效性和可靠性进行验证,并利用DELMIA平台进一步验证了规划路径的运动平滑性和安全性.     

Coating thickness optimization for a robotized thermal spray system

Thermal spraying techniques are used to protect or improve the surface performance of a workpiece by adding melted (or heated) powders onto the surface. Thickness and uniformity control are critical for obtaining an excellent thermal spraying coating. In the contemporary manufacturing industry, with the increasing demand for efficient and accurate processes, robot manipulators and handling systems have been developed to control the movement of the spray gun relative to the workpiece surface, where the robot manipulators and handling systems lead the spray gun to reciprocate along a predefined path. However, the research on optimizing the path for generating the desired coating thickness is very limited. In this paper, a parametric coating thickness prediction model is adapted from our previous research. Then, the Nelder-Mead method drives the model to find out the optimal kinematic parameters of a zigzag (meander) path for a uniform coating with the desired thickness. Based on the obtained kinematic parameters, the trajectory and program of a robot end effector (spray gun) are yielded. Finally, a prototype system with an intuitive user interface is developed to integrate these functions. From the input of a Gaussian coating growth model and a substrate, it can provide an optimal path directly. At the end of this work, one case was implemented by a homemade spray system and a robot system for verifying the effectiveness of the system.     

改进RRT-人工势场法的机械臂堆垛运动方法

快速拓展随机树算法(RRT)在机械臂路径规划中存在随机性强、搜索效率低、规划路径长等问题,不能在货柜堆垛场景中取得相对最优的光滑路径.对此,该文提出了一种改进RRT-人工势场法混合算法进行货柜堆垛机械臂运动规划.首先,对传统快速拓展随机树算法进行改进,在传统快速拓展随机树算法的全局搜索的基础上引入目标搜索,增强了随机树...     

A search algorithm for motion planning with six degrees of freedom

The motion planning problem is of central importance to the fields of robotics, spatial planning, and automated design. In robotics we are interested in the automatic synthesis of robot motions, given high-level specifications of tasks and geometric models of the robot and obstacles. The “Movers'” problem is to find a continuous, collision-free path for a moving object through an environment containing obstacles. We present an implemented algorithm for the classical formulation of the three-dimensional Movers' problem: Given an arbitrary rigid polyhedral moving object P with three translational and three rotational degrees of freedom, find a continuous, collision-free path taking P from some initial configuration to a desired goal configuration.This paper describes an implementation of a complete algorithm (at a given resolution) for the full six degree of freedom Movers' problem. The algorithm transforms the six degree of freedom planning problem into a point navigation problem in a six-dimensional configuration space (called C-space). The C-space obstacles, which characterize the physically unachievable configurations, are directly represented by six-dimensional manifolds whose boundaries are five-dimensional C-surfaces. By characterizing these surfaces and their intersections, collision-free paths may be found by the closure of three operators which (i) slide along five-dimensional level C-surfaces parallel to C-space obstacles; (ii) slide along one- to four-dimensional intersections of level C-surfaces; and (iii) jump between six-dimensional obstacles. These operators are employed by a best-first search algorithm in C-space. We will discuss theoretical properties of the algorithm, including completeness (at a resolution). This paper describes the heuristic search, with particular emphasis on the heuristic strategies that evaluate local geometric information. At the heart of this paper lie the design and implementation of these strategies for planning paths along level C-surfaces and their intersection manifolds, and for reasoning about motions with three degrees of rotational freedom. The problems of controlling the interaction of these strategies, and of integrating diverse local experts for geometric reasoning provide an interesting application of search to a difficult domain with significant practical implications. The representations and algorithms we develop impact many geometric planning problems, and extend to Cartesian manipulators with six degrees of freedom.     

A 3-level autonomous mobile robot navigation system designed by using reasoning/search approaches

This paper describes how soft computing methodologies such as fuzzy logic, genetic algorithms and the Dempster–Shafer theory of evidence can be applied in a mobile robot navigation system. The navigation system that is considered has three navigation subsystems. The lower-level subsystem deals with the control of linear and angular volocities using a multivariable PI controller described with a full matrix. The position control of the mobile robot is at a medium level and is nonlinear. The nonlinear control design is implemented by a backstepping algorithm whose parameters are adjusted by a genetic algorithm. We propose a new extension of the controller mentioned, in order to rapidly decrease the control torques needed to achieve the desired position and orientation of the mobile robot. The high-level subsystem uses fuzzy logic and the Dempster–Shafer evidence theory to design a fusion of sensor data, map building, and path planning tasks. The fuzzy/evidence navigation based on the building of a local map, represented as an occupancy grid, with the time update is proven to be suitable for real-time applications. The path planning algorithm is based on a modified potential field method. In this algorithm, the fuzzy rules for selecting the relevant obstacles for robot motion are introduced. Also, suitable steps are taken to pull the robot out of the local minima. Particular attention is paid to detection of the robot’s trapped state and its avoidance. One of the main issues in this paper is to reduce the complexity of planning algorithms and minimize the cost of the search. The performance of the proposed system is investigated using a dynamic model of a mobile robot. Simulation results show a good quality of position tracking capabilities and obstacle avoidance behavior of the mobile robot.     

基于虚拟子目标的移动机器人主动寻径导航

纯粹的反应式导航算法有时会出现“没有远见现象”,为此设计了一种基于行为和虚拟路径子目标的 移动机器人主动寻径导航策略．该策略首先在机器人的局部探测域内运用改进的可视点寻径法寻找最优虚拟子目 标,接着使用行为决策树实现快速的行为决策．机器人将如人类寻路一样,主动地灵巧绕过障碍物,基于圆弧轨迹 的运动方式使之能以平滑的路径到达目标．仿真结果验证了本策略的可行性和有效性．     

改进的势场蚁群算法的移动机器人路径规划

针对蚁群算法路径规划初期信息素浓度差异较小,正反馈作用不明显,路径搜索存在着盲目性、收敛速度相对较慢、易陷入局部最优等情况,人工势场算法的势场力可引导机器人快速朝目标位置前进,提出势场蚁群算法,通过栅格法对机器人的工作环境进行建模,利用人工势场中的势场力、势场力启发信息影响系数及蚁群算法中机器人与目标位置的距离构造综合启发信息,并利用蚁群算法的搜索机制在未知环境中寻找一条最优路径。大量的仿真实验表明势场蚁群算法路径规划能找到更优路径和收敛速度更快。     

基于变步长蚁群算法的移动机器人路径规划

针对传统蚁群算法以及双层蚁群算法在路径规划中存在搜索效率低、收敛性较慢以及成本较高的问题,本文提出了变步长蚁群算法。该算法扩大蚁群可移动位置的集合,通过对跳点的选择以达到变步长策略,有效缩短移动机器人路径长度;初始化信息素采用不均匀分布,加强起点至终点直线所涉及到栅格的信息素浓度平行地向外衰减;改进启发式信息矩阵,调整移动机器人当前位置到终点位置的启发函数计算方法。试验结果表明:变步长蚁群算法在路径长度及收敛速度两方面均优于双层蚁群算法及传统蚁群算法,验证了变步长蚁群算法的有效性和优越性,是解决移动机器人路径规划问题的有效算法。     

Pose Optimization of Serial Manipulators Using Knowledge of Their Velocity‐Degenerate (Singular) Configurations

This work investigates the exploitation of velocity‐degenerate configurations to optimize the pose of either nonredundant or redundant serial manipulators to sustain desired wrenches. An algorithm is developed that determines a desirable start point for the optimization of a serial manipulator's pose. The start‐point algorithm (SPA) uses analytical expressions of the velocity‐degenerate (singular) configurations of a serial manipulator to determine a pose that would be best suitable to sustain a desired wrench. Results for an example redundant serial manipulator are presented. The example results show that by using the SPA with the optimization routine, the resulting poses obtained require less effort from the actuators when compared to the poses obtained without using the SPA. It is shown that when no constraint is imposed on the position of the end‐effector, the SPA excels at providing a better solution with less iterations than running the optimization without the SPA. © 2003 Wiley Periodicals, Inc.     

Fuzzy Motion Planning of Mobile Robots in Unknown Environments

A fuzzy algorithm is proposed to navigate a mobile robot from a given initial configuration to a desired final configuration in an unknown environment filled with obstacles. The mobile robot is equipped with an electronic compass and two optical encoders for dead-reckoning, and two ultrasonic modules for self-localization and environment recognition. From the readings of sensors at every sampling instant, the proposed fuzzy algorithm will determine the priorities of thirteen possible heading directions. Then the robot is driven to an intermediate configuration along the heading direction that has the highest priority. The navigation procedure will be iterated until a collision-free path between the initial and the final configurations is found. To show the feasibility of the proposed method, in addition to computer simulation, experimental results will be also given.