Error Detection and Prediction Algorithms: Application in Robotics

This article presents research on error detection and prediction algorithms in robotics. Errors, defined as either agent error or Co-net error, are analyzed and compared. Three new error detection and prediction algorithms (EDPAs) are then developed, and validated by detecting and predicting errors in typical pick and place motions of an Adept Cobra 800 robot. A laser Doppler displacement meter (LDDM™) MCV-500 is used to measure the position of robot gripper in 105 experiment runs. Results show that combined EDPAs are preferred to detect and predict displacement errors in sequential robot motions.     

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.     

Evolutionary multi criteria design optimization of robot grippers

This paper explores the use of intelligent techniques to obtain optimum geometrical dimensions of a robot gripper. The optimization problem considered is a non-linear, complex, multi-constraint and multicriterion one. Three robot gripper configurations are optimized. The aim is to find Pareto optimal front for a problem that has five objective functions, nine constraints and seven variables. The problem is divided into three cases. Case 1 has first two objective functions, the case 2 considers last three objective functions and case 3 deals all the five objective functions. Intelligent optimization algorithms namely Multi-objective Genetic Algorithm (MOGA), Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-objective Differential Evolution (MODE) are proposed to solve the problem. Normalized weighting objective functions method is used to select the best optimal solution from Pareto optimal front. Two multi-objective performance measures (solution spread measure (SSM) and ratio of non-dominated individuals (RNIs)) are used to evaluate the strength of the Pareto optimal fronts. Two more multi-objective performance measures namely optimizer overhead (OO) and algorithm effort are used to find the computational effort of MOGA, NSGA-II and MODE algorithms. The Pareto optimal fronts and results obtained from various techniques are compared and analyzed.     

双臂搬运机器人结构设计与动态仿真分析

针对棒料搬运和无人机翼下弹药挂装,设计了一种基于双六自由度结构的双臂搬运机器人.对机器人总体构型和各驱动回转及末端执行器等重要部分结构加以阐述.双臂机器人由10个驱动转动环节组成,其中腰部和肩部回转为2个共用关节,双臂各有4个回转关节,组成双六自由度机械臂.机器人通过两臂间的协作可以准确地调整搬运对象的位姿,完成复杂的...     

基于3D目标跟踪算法的机器人手眼协调研究

为了适应环境的复杂性和多样性,增强机器人抓取任务的鲁棒性,本文从3D目标跟踪算法出发,提出了一种实现机器人手眼协调的新方法。该方法采用改进的基于区域的位姿追踪算法同时跟踪机械臂夹持器和目标物体的位姿,根据二者的相对位置关系引导机械臂运动。对基于区域的位姿跟踪算法,本文提出根据局部区域分割线构建分割模型并改进模型颜色似然的线性更新方式,使得算法能够准确跟踪机械臂夹持器与目标物体。基于ROS平台搭建了一套仿真实验环境,并分别在仿真环境和真实环境下验证了此手眼协调系统的有效性和鲁棒性。这种方式不仅不需要手眼标定,更接近于人类“Sensor-Actor”带反馈的闭环控制方式,同时赋予了机器人足够的灵活性来应对弹性的任务和多变的环境。     

Calibration of a measuring robot: Experimental results on a 5 DOF structure

An original method for the static calibration of robots using the pose matching approach is presented. Three algorithms for the identification of the structural parameters are investigated. The procedure includes a methodology to automatically remove the unnecessary parameters for the robot under analysis. After a theoretical introduction, the methodology is practically applied to an actual 5 DOF measuring robot used in a shoe manufactory industry. The accuracy of the robot is increased up to its repeatability. © 2001 John Wiley & Sons, Inc.     

手眼系统中刀具刀头位姿标定与视觉引导

在服务机器人的日常任务中要求机械手抓取不同的目标,且根据目标的放置位姿的不同需要从相应角度进行抓取,但机械手与手持目标的位姿关系往往难以精确和直接地测量。以刀具作为手持目标,利用eye-in-hand手眼系统抓取该目标后,在线标定手眼与手持刀具刀头的位姿关系,首先给出了摄像机调焦前后焦距标定的计算方法,再将调整焦距视为摄像机沿光轴的平移运动,通过调焦前后摄像机获取的两幅图像,标定出刀具在摄像机和机械手坐标系下的位姿,同时给出了刀具刀头到期望加工点的导向矢量计算方法。     

Pose estimation-based path planning for a tracked mobile robot traversing uneven terrains

A novel path-planning algorithm is proposed for a tracked mobile robot to traverse uneven terrains, which can efficiently search for stability sub-optimal paths. This algorithm consists of combining two RRT-like algorithms (the Transition-based RRT (T-RRT) and the Dynamic-Domain RRT (DD-RRT) algorithms) bidirectionally and of representing the robot–terrain interaction with the robot’s quasi-static tip-over stability measure (assuming that the robot traverses uneven terrains at low speed for safety). The robot’s stability is computed by first estimating the robot’s pose, which in turn is interpreted as a contact problem, formulated as a linear complementarity problem (LCP), and solved using the Lemke’s method (which guarantees a fast convergence). The present work compares the performance of the proposed algorithm to other RRT-like algorithms (in terms of planning time, rate of success in finding solutions and the associated cost values) over various uneven terrains and shows that the proposed algorithm can be advantageous over its counterparts in various aspects of the planning performance.     

基于三坐标测量机的机器人位姿精度检测方法

针对医疗场合导航引导下的手术机器人定位精度检测问题,提出了基于三坐标测量机的机器人位姿距离精度测量方法。该方法通过放置在一个平面上的三个标准球来实现三坐标测量机对姿态精度的测量,并参照机器人辅助外科手术系统的定位原理构建基于三坐标测量机的机器人位姿检测平台。在此基础上,依据国家标准规定的机器人性能检测方法和过程,完成机器人位姿距离精度的测量。通过该方法对研发的骨科手术定位机器人进行测量的结果表明,所设计机器人位置距离准确度和重复性分别在[10-1]mm和[10-2]mm级别,姿态距离准确度和重复性分别在[10-1]度和[10-2]度级别。最后将该机器人应用于前交叉韧带重建手术实验,结果表明通过这种方法检测的机器人能够满足手术场合要求。     

打磨机器人误差建模与参数辨识

简要介绍了一种实用的机器人位姿误差建模方法一摄动法,并利用此方法建立了打磨机器人位姿误差模型,对利用三坐标测量机测量的误差数据进行了建模补偿。误差参数辨识中,在传统的九线法的基础上,提出了单点法测量机器人的误差参数,克服了九线法中三测量点位置误差对测量结果的影响,提高了测量结果的可信度。实验结果表明,建模补偿后机器人位姿误差平均值降低到初始值的1／5左右,最大值降低到初始值的1／6左右,验证了所建模型的正确性和参数辨识方法的有效性。     

Closed form solution for the sensor registration problem using only position information

Sensors, mounted on the dexterous end of a robot, can be used for feedback control or calibration. When you mount a sensor on a robot it becomes necessary to find the pose (orientation and position) of the sensor relative to the robot. This is the sensor registration problem. Many researchers have provided closed-form solutions to the sensor registration problem; however, the published solutions apply only to sensors that can measure a complete pose (three positions and three orientations). Many sensors, however, can provide only position information; they cannot measure the orientation of an object. This article provides a closed-form solution to the sensor registration problem applicable when: (1) the sensor can provide only position information and (2) the robot can move along and rotate about straight lines. © 1994 John Wiley & Sons, Inc.     

Modeling, analysis, and performance evaluation of a robotic grippersystem for limp material handling

This paper presents an analytical model of a flat surfaced robotic gripper designed to automate the process of reliable, rapid and distortion-free limp material handling. The designed gripper prototype is integrated with an industrial robot manipulator. The gripper geometry and its grasp stability are justified. Performance of the overall system is experimentally tested, based on a set of industry dictated operational constraints. It is found that the gripper system has high reliability, grasp stability, and that it is capable of rapid rates of manipulation.     

基于亚像素的乒乓球机器人本体位姿视觉测量

提出一种基于亚像素精度的特征点提取算法,结合PnP方法和正交迭代(OI)算法计算乒乓球机器人本体的位姿.根据摄像机成像时弥散斑的近似高斯分布,以亚像素精度精确求取色标块的边缘,利用边缘直线交点得到高精度的角点作为特征点.基于PnP算法利用上述特征点求取机器人位姿的初值,再通过OI算法进行优化,以保证其姿态矩阵的正交性.实验结果表明,该方法能快速准确地实现机器人本体的位姿测量.     

Consistent triangulation for mobile robot localization using discontinuous angular measurements

Localization is a fundamental operation for the navigation of mobile robots. The standard localization algorithms fuse external measurements of the environment with the odometric evolution of the robot pose to obtain its optimal estimation. In this work, we present a different approach to determine the pose using angular measurements discontinuously obtained in time. The presented method is based on an Extended Kalman Filter (EKF) with a state-vector composed of the external angular measurements. This algorithm keeps track of the angles between actual measurements from robot odometric information. This continuous angular estimation allows the consistent use of the triangulation methods to determine the robot pose at any time during its motion. The article reports experimental results that show the localization accuracy obtained by means of the presented approach. These results are compared to the ones obtained applying the EKF algorithm with the standard pose state-vector. For the experiments, an omnidirectional robotic platform with omnidirectional wheels is used.     

Robust optimization with applications to design of context specific robot solutions

This paper presents an investigation of five optimization algorithms for simulation-based optimization for robotic tasks, where robust solutions are required. We evaluate the optimization methods on three use cases. The use cases involve using a robot for handling meat, optimizing gripper design for aligning objects and optimizing gripper design for table picking in cluttered scenes. We use dynamic simulations to model the use cases, where the most important physical aspects are captured. We have a focus on the robustness with respect to crucial system uncertainties, which is important in an industrial setting. The choice of parameterization and objective scores is also discussed since this choice has some impact on the performance of the optimization algorithms. For all problems, we find feasible solutions ready for real world testing, and overall the optimization method RBFopt has the best performance in terms of finding robust solutions within the fewest amount of simulations.     

Neural Network-Based Vision for Precise Control of a Walking Robot

This article describes a connectionist vision system for the precise control of a robot designed to walk on the exterior of the space station. The network learns to use video camera input to determine the displacement of the robot's gripper relative to a hole in which the gripper must be inserted. Once trained, the network's output is used to control the robot, with a resulting factor of five fewer missed gripper insertions than occur when the robot walks without sensor feedback. The neural network visual feedback techniques described could also be applied in domains such as manufacturing, where precise robot positioning is required in an uncertain environment.     

Mobile robot localization based on PSO estimator

Localization is fundamental to autonomous operation of the mobile robot. A particle filter (PF) is widely used in mobile robot localization. However, the robot localization based PF has several limitations, such as sample impoverishment and a degeneracy problem, which reduce significantly its performance. Evolutionary algorithms, and more specifically their optimization capabilities, can be used in order to overcome PF based on localization weaknesses. In this paper, mobile robot localization based on a particle swarm optimization (PSO) estimator is proposed. In the proposed method, the robot localization converts dynamic optimization to find the best robot pose estimate, recursively. Unlike the localization based on PF, the resampling step is not required in the proposed method. Moreover, it does not require noise distribution. It searches stochastically along the state space for the best robot pose estimate. The results show that the proposed method is effective in terms of accuracy, consistency, and computational cost compared with localization based on PF and EKF.     

视觉伺服机械臂手机抓取最佳位姿检测

针对下水道、勾缝等狭窄位置的手机拾取的问题, 本文提出一种基于机器视觉的伺服机械臂抓取方法. 首先对机械臂eye-in-hand上的相机进行标定, 图像预处理及目标检测等, 在位姿检测中提出一种基于二维坐标系下手机位姿解算算法, 得出解算的最佳位姿角只与夹持点的像素坐标的差值有关, 其位姿角的大小决定了手抓旋转的角度. 实验用Matlab软件对位姿检测进行仿真分析, 其包括SURF不变特征点的目标检测实验和位姿解算实验, 最后用Rethink双臂机器人的右臂对手机进行抓取验证. 实验表明, 在误差允许范围内, 提出的算法具有一定的有效性, 其结果为伺服机械臂抓取手机提供良好的准确性.     

Support vector regression methodology for prediction of input displacement of adaptive compliant robotic gripper

The prerequisite for new versatile grippers is the capability to locate and perceive protests in their surroundings. It is realized that automated controllers are profoundly nonlinear frameworks, and a faultless numerical model is hard to get, in this way making it troublesome to control utilizing tried and true procedure. Here, a design of an adaptive compliant gripper is presented. This design of the gripper has embedded sensors as part of its structure. The use of embedded sensors in a robot gripper gives the control system the ability to control input displacement of the gripper and to recognize specific shapes of the grasping objects. Since the conventional control strategy is a very challenging task, soft computing based controllers are considered as potential candidates for such an application. In this study, the polynomial and radial basis function (RBF) are applied as the kernel function of Support Vector Regression (SVR) to estimate and predict optimal inputs displacement of the gripper according to experimental tests and shapes of grasping objects. Instead of minimizing the observed training error, SVR _poly and SVR _rbf attempt to minimize the generalization error bound so as to achieve generalized performance. The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the SVR approach compared to other soft computing methodology.     

机器人在全口义齿制作中的应用研究

全口义齿机器人制作系统的研制是将机器人应用于口腔修复医学的一次大胆尝试 ．它将口腔医生的丰富经验和牙科技师的熟练技术融合于专家系统软件中,并由机器人完成 复杂的义齿种植的工作．该系统可以根据患者的颌弓形状自动为患者设计和制作出一套适合 的全口义齿,提高了全口义齿制作的质量和效率．本文介绍了全口义齿机器人制作系统的硬 件部分的基本结构,及专家预排、三维显示和人机交互式调整、轨迹规划和控制等软件模块 ．完成了系统的初步试验,实现了系统的基本要求．