An analytical C3 continuous tool path corner smoothing algorithm for 6R robot manipulator

Tool path smoothness is important to guarantee good dynamic and tracking performance of robot manipulators. An analytical C³ continuous tool path corner smoothing algorithm is proposed for robot manipulators with 6 rotational (6R) joints. The tool tip position is smoothed directly in the workpiece coordinate system (WCS). The tool orientation is smoothed after transferring the tool orientation matrix as three rotary angles. Micro-splines of the tool tip position and tool orientation are constructed under the constraints of the maximum deviation error tolerances in the WCS. Then the tool orientation and tool tip position are synchronized to the tool tip displacement with C³ continuity by replacing the remaining linear segments using specially constructed B-splines. Control points of the locally inserted micro-splines are all evaluated analytically without any iterative calculations. Simulation and experimental results show that the proposed algorithm satisfies constraints of the preset tool tip position and the tool orientation tolerances. The proposed corner smoothing algorithm achieves smoother and lower jerks than C² continuous corner smoothing algorithm. Experimental results show that the tracking errors associated to the execution of the C³ continuous tool path are up to 10% smaller than C² continuous path errors.     

Improved Telemanipulator Navigation During Display-Control Misalignments Using Augmented Reality Cues

An augmented reality (AR) cueing method designed to improve teleoperator performance under conditions of display-control misalignment is investigated. The teleoperation task was designed to mimic the operation of space robot arms, which are manipulated using hand controllers (HCs) to orient and translate the body-fixed coordinates at the end effector (EE). Cameras provide visual feedback. However, the pose of the EE seen through the camera hinders operator performance due to misalignments between the displayed EE axes and the HC axes. In this paper, the coordinate system of the EE is graphically overlaid in three dimensions on the video views with uniquely colored axes using AR. The same color scheme is used to label the corresponding axes on the HCs. Operators use these color cues to map each axis on the HCs to the corresponding colored axis of the augmented coordinates at the EE to obtain EE movement in the desired direction. Between-groups and within-participant experiments comparing EE trajectory distance, deviation from path, navigation errors, and HC axis usage were used to determine the effectiveness of the augmented coordinates over conventional teleoperation without augmented coordinates. Significant reductions in EE trajectory distance, deviation from path, navigation errors, and single-axis HC usage were observed when participants manipulated the remote robot with augmented coordinates. The results demonstrate that the use of simple AR cues in remote robot arm teleoperation is beneficial to the operator.     

A path following algorithm for mobile robots

This paper considers path following control for a robotic platform. The vehicle used for the experiments is a specially designed robotic platform for performing autonomous weed control. The platform is four-wheel steered and four-wheel driven. A diesel engine powers the wheels via a hydraulic transmission. The robot uses a Real Time Kinematic Differential Global Positioning System to determine both position and orientation relative to the path. The deviation of the robot to the desired path is supplied to two high level controllers minimizing the orthogonal distance and orientation to the path. Wheel angle setpoints are determined from inversion of the kinematic model. At low level each wheel angle is controlled by a proportional controller combined with a Smith predictor. Results show the controller performance following different paths shapes including a step, a ramp, and a typical headland path. A refined tuning method calculates controller settings that let the robot drive as much as possible along the same path to its setpoint, but also limit the gains at higher speeds to prevent the closed loop system to become unstable due to the time delay in the system. Mean, minimum and maximum orthogonal distance errors while following a straight path on a paving at a speed of 0.5 m/s are 0.0, −2.4 and 3.0 cm respectively and the standard deviation is 1.2 cm. The control method for four wheel steered vehicles presented in this paper has the unique feature that it enables control of a user definable position relative to the robot frame and can deal with limitations on the wheel angles. The method is very well practical applicable for a manufacturer: all parameters needed are known by the manufacturer or can be determined easily, user settings have an easy interpretation and the only complex part can be supplied as a generic software module.     

Indoor Mobile Robot Local Path Planner with Trajectory Tracking

This paper deals with the design and implementation of an indoor mobile robot local path planner. This latter is based essentially on an ultrasonic perception system, where the covered region of sight is widened and the apparent distance between any two adjacent sensors can be adjusted. So, good resolution can be obtained and laterally positioned obstacles with respect to the robot line of sight are well identified. Furthermore, we propose a technique to improve the odometric method, to reduce the systematic errors and to detect floor irregularities. Following a predefined trajectory is provided by the control of the trailing wheel deviation angle.     

A novel cartesian trajectory planning method by using triple NURBS curves for industrial robots

This article presents a novel method of robot pose trajectory synchronization planning. First of all, based on triple NURBS curves, a method of describing the position and orientation synchronization of the robot is proposed. Then, through considering geometric and kinematic constraints, especially angular velocity constraint, and employing bidirectional interpolation algorithm, a robot pose trajectory planning approach is developed, which has limited linear jerk, continuous bounded angular velocity and approximate optimal time, and does not need an optimization program. Ultimately, two robot pose paths, blade-shaped curve and fan-shaped curve, are utilized for simulations, and the results indicate that the proposed trajectory planning method can satisfy the given constraint conditions, i.e. the linear jerk is limited and the angular velocity is continuous bounded. The trajectory tracking experiments are further carried out on a 6-DOF industrial robot, and the results show that the proposed planning method can generate smooth trajectories to ensure the stability of the robot motion without impact in practical situations.     

Robotic path compensation training method for optimizing face milling operations based on non-contact CMM techniques

Currently, the use of industrial robots in the machining of large components in metallic materials of significant hardness is proliferating. The low rigidity of industrial robots is still the main conditioning for their use in machining applications, where the forces developed in the process cause significant deviations on the cutting tool path. Although there are already methodologies that facilitate the pose study of the robot mechanical behaviour, predicting deviation values of the cutting tool path and facilitating the selection of process variables, robotic cell users still request new methods able to allow them to optimize the use of these production systems. On the other hand, non-contact measurement technologies have burst into many fields of knowledge, their use is becoming consolidated, and they allow the digitization of complex surfaces. This research presents the development of a new method of robotic machining trajectory compensation that allows optimizing the manufacture of flat surfaces using an industrial anthropomorphic robot. The new training method determines the actual deviations of the cutting tool after the machining process, and checks if these are within the admissible range of flatness error. This method is a novel iterative technique that incorporates the algorithm that uses the measured deviations and a reduction factor fr to calculate the offset that modifies the coordinate value of the programmed path points outside the admissible range and generates a new machining path to be tested. The method has been tested on a pre-industrial scale for aluminium machining, and the algorithm has carried out two iterations to generate a compensated robotic milling path within a flatness tolerance range of 300 µm, improving the error deviation by 37% comparing to the initial path.     

弧焊机器人焊缝跟踪神经网络控制器

介绍了一种能提高高弧焊机器人焊缝跟踪精度的神经网络控制器,通过神经网络的补偿作用,弥补了由于无法知道机器人精确模型所造成的控制上的误差,不同于机器人控制中传统的网络控制器,本文提出并应用了基于笛卡尔空间轨迹控制的机器人焊缝跟踪神经网络,大大简化了控制算法,计算机模拟及实验表明,该控制器非常适用于只的实际焊接,对于现有机器人,无须改变其控制器内部结构,即可应用该技术,与常用的机器人关节力矩控制法相比     

A Novel Approach for Mobile Robot Navigation with Dynamic Obstacles Avoidance

This paper proposes a new approach for trajectory optimization of a mobile robot in a general dynamic environment. The new method combines the static and dynamic modes of trajectory planning to provide an algorithm that gives fast and optimal solutions for static environments, and generates a new path when an unexpected situation occurs. The particularity of the method is in the representation of the static environment in a judicious way facilitating the path planning and reducing the processing time. Moreover, when an unexpected obstacle blocks the robot trajectory, the method uses the robot sensors to detect the obstacle, finds a best way to circumvent it and then resumes its path toward the desired destination. Experimental results showed the effectiveness of the proposed approach.     

基于模糊人工势场法的智能全向车路径规划

针对于移动机器人在传统人工势场法路径规划中易于陷入局部最小点而无法抵达目标点的问题,同时考虑到实际环境中人工势场法相关参数的不确定性,提出了一种基于模糊人工势场法的动态路径规划方法。借助于专家经验进行模糊决策,调整移动机器人在各个时刻的合力大小和方向,进而解决斥力常数、引力方向偏角以及机器人行驶速度的不确定性问题。为了验证该方法的有效性,在智能全向车平台进行了应用,结果表明,智能全向车运动轨迹平滑,避免了实际应用中的震荡问题。     

Feedrate planning for machining with industrial six-axis robots

Nowadays, the adaptation of industrial robots to carry out high-speed machining operations is strongly required by the manufacturing industry. This new technology machining process demands the improvement of the overall performances of robots to achieve an accuracy level close to that realized by machine-tools. This paper presents a method of trajectory planning adapted for continuous machining by robot. The methodology used is based on a parametric interpolation of the geometry in the operational space. FIR filters properties are exploited to generate the tool feedrate with limited jerk. This planning method is validated experimentally on an industrial robot.     

Trajectory generation and control of a five-bar-link parallel direct-drive robot

This paper describes a dyanamic learning control method for a five-bar-link parallel direct-drive robot. A new method to generate a complex continuous trajectory in Cartesian coordinates is presented. The trajectory is expressed as a composition of a segment of a parametric free-form space curve. Hosaka's form of the Bezier curve of degree 3, is used in this study. The availability of robot control based on this trajectory is proven through computer simulation.     

State Space Constrained Iterative Learning Control for Robotic Manipulators

Real‐life work operations of industrial robotic manipulators are performed within a constrained state space. Such operations most often require accurate planning and tracking a desired trajectory, where all the characteristics of the dynamic model are taken into consideration. This paper presents a general method and an efficient computational procedure for path planning with respect to state space constraints. Given a dynamic model of a robotic manipulator, the proposed solution takes into consideration the influence of all imprecisely measured model parameters, making use of iterative learning control (ILC). A major advantage of this solution is that it resolves the well‐known problem of interrupting the learning procedure due to a high transient tracking error or when the desired trajectory is planned closely to the state space boundaries. The numerical procedure elaborated here computes the robot arm motion to accurately track a desired trajectory in a constrained state space taking into consideration all the dynamic characteristics that influence the motion. Simulation results with a typical industrial robot arm demonstrate the robustness of the numerical procedure. In particular, the results extend the applicability of ILC in robot motion control and provide a means for improving the overall trajectory tracking performance of most robotic systems.     

基于混合遗传算法的工业机器人最优轨迹规划

为兼顾工业机器人工作效率与轨迹的平稳性,提出一种基于混合遗传算法的二次轨迹规划方案.通过最优时间轨迹规划得到最小执行时间,在最小执行时间内进行最优冲击轨迹规划,进而规划出一条既高效又平滑的运动轨迹.采用五次均匀B样条在关节空间进行快速插值,不仅保证了各关节速度和加速度连续性还保证了各关节冲击的连续性.连续平滑的冲击可以减少机械振动,延长机器人的工作寿命.选用PUMA560为对象进行仿真与实验,结果表明,该方案可以获得比较理想的机器人运动轨迹,所提出的混合遗传算法能有效提高全局寻优的性能和算法运行的稳定性.     

昆虫视觉启发的光流复合导航方法

昆虫能够使用视觉感受的光流(Optical flow, OF)信息执行导航任务. 启发于昆虫的视觉导航, 本文提出了一种生物视觉启发的光流复合导航方法, 它由光流导航和光流辅助导航两部分组成, 以实现高效精确的视觉导航定位. 该方法中, 光流导航的作用是使用昆虫视觉启发的光流法, 测量系统每一时刻的运动位移, 然后使用路径积分累加位移得到位置信息; 光流辅助导航的作用是针对路径积分会产生累积误差的缺点, 使用光流匹配的方法来估计和修正导航中的位置误差. 该光流辅助导航也参考了昆虫启发的光流法, 通过基于光流的卡尔曼滤波器来执行实际和预测光流的迭代匹配. 由于光流导航和光流辅助导航中的光流计算来源于同一昆虫启发光流法, 使得光流复合导航的两部分可共享输入信号和部分执行过程. 文中使用移动机器人进行导航实验,证明了该复合导航方法的效率.     

A constant plunge depth control strategy for robotic FSW based on online trajectory generation

Robotic friction stir welding (RFSW) usually comes with a huge upsetting force, and the stiffness of the welding system distributes unevenly over the position, which leads to a large deviation of the plunge depth of the tool at the end of the robot. The conventional constant distance tracking control suffers from the problem of unsmooth compensation leading to the vibration of the robot and thus degrading the weld quality. For this problem, a constant plunge depth control based on online trajectory generation for RFSW is studied, which can generate an accurate welding trajectory according to the rough initial reference path and smoothly compensate for the plunge deviation. Initially, three laser-ranging sensors are utilized to measure the pose deviation of the tool in real-time and generate the ideal welding trajectory according to the projection vector method. Then, a deformation compensation model is established to realize the real-time prediction of the correct value. To ensure the smoothness and rapidity of the dynamic tracking process of displacement deviation, we adopt an online trajectory generator as the core of optimization control to meet the process constraints such as speed, acceleration, and jerk during the compensation process. Finally, simulation and experiment are carried out. The results show that the proposed method can effectively reduce the vibration caused by compensation during the welding process and reduce flash, which can improve the welding quality.     

Path Planning for a Statically Stable Biped Robot Using PRM and Reinforcement Learning

In this paper path planning and obstacle avoidance for a statically stable biped robot using PRM and reinforcement learning is discussed. The main objective of the paper is to compare these two methods of path planning for applications involving a biped robot. The statically stable biped robot under consideration is a 4-degree of freedom walking robot that can follow any given trajectory on flat ground and has a fixed step length of 200 mm. It is proved that the path generated by the first method produces the shortest smooth path but it also increases the computational burden on the controller, as the robot has to turn at almost all steps. However the second method produces paths that are composed of straight-line segments and hence requires less computation for trajectory following. Experiments were also conducted to prove the effectiveness of the reinforcement learning based path planning method.     

基于QPSO 算法移动机器人轨迹规划与实验

针对移动机器人路径规划问题,提出一种基于QPSO算法的路径规划方法,并用概率论的方法分析了移动机器人路径规划的收敛性,阐明了该方法随均匀分布和正态分布的参数关系和收敛区间;然后根据移动机器人的运动特征提出一种改进的轨迹规划方法。移动机器人平台的实验结果表明了该方法在移动机器人路径规划中的有效性和可行性。     

Dual-edge robotic gear chamfering with registration error compensation

This paper describes a novel method for robotic gear chamfering called dual-edge chamfering which can facilitate simultaneous chamfering of the two edges of adjacent gear teeth and overcome typical registration errors arising due to the placement of the workpiece in the robot workspace. Deviations of the robot end-effector trajectory when compared to the nominal trajectory due to registration errors are discussed first; such trajectory deviations caused by typical registration errors due to gear center translation and rotation are quantified. Dual-edge chamfering process is described and an efficient trajectory design strategy is developed by considering the kinematic constraints imposed by the profiles of the gear edge and the abrasive tool. The dual-edge chamfering robot trajectory is facilitated by a simple procedure for identifying the gear and gear root centers by employing the robot. To execute the dual-edge chamfering trajectory, an efficient motion/force control strategy that includes active compliance from the tool mounted on the robot is proposed. A number of real-time experiments are conducted to evaluate the proposed method by employing a commercial six degree-of-freedom robot. Two types of large cylindrical metal gears are utilized for testing, an external gear with teeth on the outside and an internal gear with teeth on the inside. In addition to these, two different robotic compliant tools with axial and radial compliance are tested. A representative sample of the experimental results are presented and discussed.     

Task-oriented optimal dimensional synthesis of robotic manipulators with limited mobility

In this article, an optimization method is proposed for the dimensional synthesis of robotic manipulators with limited mobility, i.e. with less than 6 degrees-of-freedom (“DoF”), with a prescribed set of tasks in a constrained environment. Since these manipulators cannot achieve full 6-DoF mobility, they are able to follow only certain paths with prescribed position and orientation in space. While the most common approach to this problem employs pure path-planning algorithms, operations in narrow and complex environments might require changes to the robot design too. For this reason, this paper presents an improved approach which aims to minimize position and orientation error with a dimensional synthesis. First, a novel methodology that combines a path planning algorithm and dimensional synthesis has been proposed in order to optimize both robot geometry and pose for a given set of points. Then, the method is validated with a 4-DoF robot for high-precision laser operations in aeroengines as a case study. The example shows that the proposed procedure provides a stable algorithm with a high convergence rate and a short time to solution for robots with limited mobility in highly constrained scenarios.