Process planning for 8-axis robotized laser-based direct metal deposition system: A case on building revolved part

Laser-based direct metal deposition (LBDMD) is a promising additive manufacturing technology that is well suited for production of complex metal structures, low-volume manufacturing, and high-value component repair or modification. It finds broad application in the automotive, biomedical, and aerospace industries. The Research Center for Advanced Manufacturing (RCAM) at Southern Methodist University is developing a robot controlled LBDMD system that couples a 6-axis robot arm with an additional 2-axis tilt and rotatory positioning system. The system simplifies the process planning of multiple-directional deposition for complex parts and reduces production time. This paper describes the printing process specific to complex revolved parts. Taking advantage of the coupled 2-axis tilt and rotatory system, a hybrid slicing method is developed to map the overhanging structures of a revolved part to be at a planar base. Consequently, the traditional path planning strategies are applicable to generate the tool-path for the mapped structures. The method is successfully applied to build a propeller.     

Eco-programming of industrial robots for sustainable manufacturing via dynamic time scaling of trajectories

Nowadays, Industrial Robots (IRs) have become widespread in many manufacturing industries. Medium and high payload IRs cover a significant percentage of the overall factory Energy Consumption (EC). This article focuses on the IRs eco-programming to minimize the EC of a robot, being energy efficiency one of the fundamental aims of sustainable manufacturing. By leveraging well-known trajectory scaling methods, this research develops a novel, versatile, fast, and efficient process to define the IR optimal velocity/acceleration profile in time, keeping the geometry of the trajectory fixed. A complete IR system model that founds application in various types of 6 degrees of freedom articulated manipulators has been developed by considering electrical motors, actuator drive systems, and controller cabinet losses. A new optimization technique based on Dynamic Time Scaling of trajectories is presented, and the obtained results are compared with other methods used in the scientific literature. When performing critical path analysis, the EC of the robot system is estimated to be cut down, being the robot motion time fixed, by about 13% through this novel approach. The model has been validated through commercial software, and the proposed optimization algorithm has been implemented in a user-friendly interface tool.     

基于GA优化RBF神经网络的机器人轨迹规划

针对机器人在不确定环境下末端执行器运动轨迹的准确性及平稳性问题,采用基于遗传算法(GA)优化径向基函数(RBF)神经网络的轨迹规划方法对Kinova Mico2机器人进行轨迹规划研究。介绍了机器人的相关参数及坐标系、建立了D-H矩阵和运动学模型。提取机器人实际抓取物品的直线轨迹并等分插补,用GA优化并实时在线更新RBF神经网络的权值,以更优的权值参数建立新的RBF网络。研究结果表明:相比优化前,基于GA优化RBF的规划轨迹逼近误差小且平滑稳定,仿真结果较为稳定,轨迹规划的可行性满足机器人实际抓取工作的需要。     

Coordinated control method of space-tethered robot system for tracking optimal trajectory

Space-tethered robot system is a new kind of space robot, which consists of a robot platform, space tether, and operation robot. This paper presents the coordinated control method in order to save thruster fuel of operation robot in the process of tracking the optimal approach trajectory. First, the optimal approach trajectory of an operation robot is designed using the Gauss pseudospectral method, which resulted in continuous optimal control force using the Lagrange interpolation scheme. The optimal control force is optimized and distributed to space tether and thrusters through simulated annealing algorithm in discrete points, which minimized fuel consumption of thrusters. The distributive continuous force is obtained via cubic polynomial fitting of optimal distributive force in 0.1s discrete time point. To tracking the optimal trajectory, Fuzzy Proportional-Derivative controller is designed with the help of optimal distribution force which come from optimization model. Simultaneously, the relative attitude of the operation robot is stabilized using attitude time-delay algorithm through the reaction wheels. Numerical results are presented, demonstrating the validity of saving thruster fuel and well performance in tracking the optimal trajectory.

     

Comparison of four different heuristic optimization algorithms for the inverse kinematics solution of a real 4-DOF serial robot manipulator

In this study, a 4-degree-of-freedom (DOF) serial robot manipulator was designed and developed for the pick-and-place operation of a flexible manufacturing system. The solution of the inverse kinematics equation, one of the most important parts of the control process of the manipulator, was obtained by using four different optimization algorithms: the genetic algorithm (GA), the particle swarm optimization (PSO) algorithm, the quantum particle swarm optimization (QPSO) algorithm and the gravitational search algorithm (GSA). These algorithms were tested with two different scenarios for the motion of the manipulator’s end-effector. One hundred randomly selected workspace points were defined for the first scenario, while a spline trajectory, also composed of one hundred workspace points, was used for the second. The optimization algorithms were used for solving of the inverse kinematics of the manipulator in order to successfully move the end-effector to these workspace points. The four algorithms were compared according to the execution time, the end-effector position error and the required number of generations. The results showed that the QPSO could be effectively used for the inverse kinematics solution of the developed manipulator.     

一种协作型机器人运动性能分析与仿真

随着制造模式的变革,协作型机器人在工业领域的应用日益广泛。本文介绍了协作型机器人的特性,并且以KUKA LBR iiwa机器人为例,进行运动性能分析,旨在为研发此类机器人提供设计理论依据。利用Denavit-Hartenberg法建立了该机器人运动学模型。基于蒙特卡洛法在MATLAB环境下对机器人灵活性和可操作性进行分析,并对其在狭小空间内作业进行轨迹规划,仿真结果表明LBR iiwa机器人具有良好的灵活性、可操作性及避障能力。     

基于PLC技术的焊接机器人主从协调运动控制系统研究

焊接机器人运动控制系统的控制功能直接决定了焊接工作质量,利用PLC技术优化设计焊接机器人主从协调运动控制系统。在系统硬件设计方面,装设位置、速度、旋转电弧等传感器设备,利用传感数据检测焊接机器人实时位姿。在考虑焊接机器人组成结构、工作原理以及动力驱动方式的情况下,构建焊接机器人的数学模型。结合当前位姿和控制目标之间的位置关系,规划焊接机器人主从协调运动轨迹,在约束条件的作用下,利用PLC控制器生成控制指令,作用在改装的焊接机器人驱动器上,实现系统的焊接机器人主从协调运动控制功能。通过系统测试实验得出结论：与传统控制系统相比,优化设计系统的速度控制误差、姿态角控制误差分别降低了0.075mm/s和0.38°,在优化系统控制下,主从焊接机器人的运动轨迹与规划轨迹之间无明显差异。     

Optimal Protraction of a Biologically Inspired Robot Leg

In this paper, protraction movement, namely forward stepping, of a biologically inspired three-joint robot leg is optimized for minimum energy consumption. Trajectory optimization is performed for various initial-final tip point positions of protraction. A modified version of gradient descent based optimal control algorithm is used. The objective function is modified in steps to jump over many unfeasible and inefficient local optima. The optimized trajectories are used to construct a radial basis function neural network (RBFNN) to interpolate for the untrained regions. The results of optimization are compared with the observations of protraction of stick insects. It is concluded that a direct biological imitation of protraction is not energy efficient. A sample protraction of a leg of the Robot-EA308 is demonstrated in guidance of the optimized trajectory. Energy optimal protraction of a robot leg necessitates flexion of the leg, rather than extension as observed in the stick insects.     

A novel methodology for optimal single mobile robot scheduling using whale optimization algorithm

One of the fundamental requirements for creating an intelligent manufacturing environment is to develop a reliable, efficient and optimally scheduled material transport system. Besides traditional material transport solutions based on conveyor belts, industrial trucks, or automated guided vehicles, nowadays intelligent mobile robots are becoming widely used to satisfy this requirement. In this paper, the authors analyze a single mobile robot scheduling problem in order to find an optimal way to transport raw materials, goods, and parts within an intelligent manufacturing system. The proposed methodology is based on biologically inspired Whale Optimization Algorithm (WOA) and is aimed to find the optimal solution of the nondeterministic polynomial-hard (NP-hard) scheduling problem. The authors propose a novel mathematical model for the problem and give a mathematical formulation for minimization of seven fitness functions (makespan, robot finishing time, transport time, balanced level of robot utilization, robot waiting time, job waiting time, as well as total robot and job waiting time). This newly developed methodology is extensively experimentally tested on 26 benchmark problems through three experimental studies and compared to five meta-heuristic algorithms including genetic algorithm (GA), simulated annealing (SA), generic and chaotic Particle Swarm Optimization algorithm (PSO and cPSO), and hybrid GA–SA algorithm. Furthermore, the data are analyzed by using the Friedman statistical test to prove that results are statistically significant. Finally, generated scheduling plans are tested by Khepera II mobile robot within a laboratory model of the manufacturing environment. The experimental results show that the proposed methodology provides very competitive results compared to the state-of-art optimization algorithms.     

Trajectory tracking optimization of mobile robot using artificial immune system

In this paper, an optimization method that provides quick response using artificial immune system, is proposed and applied to a mobile robot for trajectory tracking. The study focuses on the immune theory to derive a quick optimization method that puts emphasis on immunity feedback using memory cells by the expansion and suppression of the test group rather than to derive a specific mathematical model of the artificial immune system. Various trajectories were selected in mobile environment to evaluate the performance of the proposed artificial immune system. The global inputs to the mobile robot are reference position and reference velocity, which are time variables. The global output of mobile robot is a current position. The tracking controller makes position error to be converged to zero. In order to reduce position error, compensation velocities on the track of trajectory are necessary. Input variables of fuzzy are position errors in every sampling time. The output values of fuzzy are compensation velocities. Immune algorithm is implemented to adjust the scaling factor of fuzzy automatically. The results of the computer simulation proved the system to be efficient and effective for tracing the trajectory to the final destination by the mobile robot.

     

Dynamic visual servo control of a 4-axis joint tool to track image trajectories during machining complex shapes

A large part of the new generation of computer numerical control systems has adopted an architecture based on robotic systems. This architecture improves the implementation of many manufacturing processes in terms of flexibility, efficiency, accuracy and velocity. This paper presents a 4-axis robot tool based on a joint structure whose primary use is to perform complex machining shapes in some non-contact processes. A new dynamic visual controller is proposed in order to control the 4-axis joint structure, where image information is used in the control loop to guide the robot tool in the machining task. In addition, this controller eliminates the chaotic joint behavior which appears during tracking of the quasi-repetitive trajectories required in machining processes. Moreover, this robot tool can be coupled to a manipulator robot in order to form a multi-robot platform for complex manufacturing tasks. Therefore, the robot tool could perform a machining task using a piece grasped from the workspace by a manipulator robot. This manipulator robot could be guided by using visual information given by the robot tool, thereby obtaining an intelligent multi-robot platform controlled by only one camera.     

并联3-URS踝关节康复机器人的机构与运动学研究

为了帮助患者进行踝关节康复训练,减轻治疗师工作强度,在分类分析现有的各类型踝关节康复机器人的基础上,设计了一种六自由度并联3-URS踝关节康复机器人。从人体生理结构及康复训练需求出发,设计、优化了康复机器人结构,加工制造了实物样机模型;采用闭环矢量的方法建立了并联机器人运动学模型,结合Rosenbrock-Banana优化函数,将正逆运动学数值求解问题转换为优化问题。以背屈训练轨迹作为数值算例,求解精度可达10-10~10-7mm;结合虚拟样机技术,验证了该并联机器人运动学优化求解方法的可靠性,适用于3-URS并联踝关节康复机器人。     

运行时间周期化工业机器人模型迭代寻优NURBS轨迹插补

为满足工业机器人高精度复杂曲线运动的需求,本文提出运行时间周期化工业机器人模型迭代寻优NURBS轨迹插补算法.首先,根据轨迹最大轮廓误差和机器人动力学特性对曲线分段.随后,提出优化回溯算法,使各子曲线段均可用S曲线加减速规划.之后,为保证机器人在进给速度极小值处不超速,将各加减速阶段运行时间调整为插补周期的整数倍,并对子曲线段衔接处速度平滑处理.最后,提出模型迭代寻优曲线插补,大大降低了速度波动率.仿真试验表明,该方法插补轨迹的各项指标均满足要求且最大速度波动率仅为0.000099%.真机试验也验证了该方法可有效减小轨迹误差.     

An online robot trajectory planning and programming support system for industrial use

The manufacturing industry today is still looking for enhancement of their production. Programming of articulated production robots is a major area for improvement. Today, offline simulation modified by manual programming is widely used to reduce production downtimes but requires financial investments in terms of additional personnel and equipment costs. The requirements have been evaluated considering modern manufacturing aspects and a new online robot trajectory planning and programming support system is presented for industrial use. The proposed methodology is executed solely online, rendering offline simulation obsolete and thereby reduces costs. To enable this system, a new cell-based Voronoi generation algorithm, together with a trajectory planner, is introduced. The robot trajectories so achieved are comparable to manually programmed robot programs. The results for a Mitsubishi RV-2AJ five axis industrial robot are presented.     

Simulation-based methodology for machine cell design

This paper presents a simulation-based methodology which uses both design and manufacturing attributes to form manufacturing cells. The methodology is implemented in three phases. In phase I, parts are grouped into part families based on their design and manufacturing dissimilarities. In phase II, machines are grouped into manufacturing cells based on relevant operational costs and various cells are assigned part families using an optimization technique. Phases I and II are based on integer and mixed-integer mathematical models. Finally, in phase III, a simulation model of the proposed system is built and verified, and the model is run so that data on the proposed system may be gathered and evaluated. The mathematical and simulation models are used to solve a sample production problem. The results from these models are compared, and can be used to justify the final design. By the use of these modeling tools, cellular manufacturing systems can be designed, analyzed, optimized, and finally justified.     

An energy-efficient approach for 3D printing with a Linear Delta Robot equipped with optimal springs

In this paper a novel approach for sustainable 3D printing with a Linear Delta Robot equipped with elastic elements is presented and experimentally validated. Energy saving is achieved thanks to the introduction and optimization of linear springs that are mounted on the robot with different configurations: in parallel to the prismatic joints, or directly connecting the end-effector to the fixed frame. The elastic elements allow for a conversion between potential and kinetic energy during a cyclic motion, as for instance the printing of a material layer in additive manufacturing, resulting in actuators energy saving. To reduce the energy consumption, the spring parameters are optimized for the different scenarios by considering the kinematic, dynamic and electro-mechanical models of the parallel robot performing a 3D printing trajectory. The proposed approach is experimentally validated, showing an energy reduction up to almost 50% with respect to the nominal case without springs. The method is general and can be applied for energy efficiency and sustainability in several fields of robotics and computer-integrated manufacturing.     

Optimal trajectory generation algorithm for serial and parallel manipulators

In this paper, an Optimal Trajectory Generation Algorithm (OTGA) is developed for generating minimum-time smooth motion trajectories for serial and parallel manipulators. OTGA is divided into two phases. The first phase encompasses derivation of minimum-time optimal trajectory using cubic spline due to its less vibration and overshoot characteristics. Although cubic splines are widely used in robotics, velocity and acceleration ripples in the first & last knots can worsen manipulator trajectory. The second phase includes changing cubic spline interpolation in the first and last knots of optimized trajectory with 7th order polynomial for having zero jerk at the beginning and end points of trajectory. Performing this modification eliminate undesired worsening in the trajectory and provide smoother start and stop of joint motions. Particle Swarm Optimization (PSO) is chosen as optimization algorithm because of its easy implementation and successful optimization performance. OTGA has been tested in simulation for PUMA robot and results are compared with algorithms proposed by earlier authors. In addition, a discrete-time PID control scheme for PUMA robot is designed for comparing energy consumption of OTGA with algorithms developed by previous authors. Comparison results illustrated that OTGA is the better trajectory generation algorithm than the others.     

Memory-saving memetic computing for path-following mobile robots

In this paper, a recently proposed single-solution memetic computing optimization method, namely three stage optimization memetic exploration (3SOME), is used to implement a self-tuning PID controller on board of a mobile robot. More specifically, the optimal PID parameters minimizing a measure of the following error on a path-following operation are found, in real-time, during the execution of the control loop. The proposed approach separates the control and the optimization tasks, and uses simple operating system primitives to share data. The system is able to react to modifications of the trajectory, thus endowing the robot with intelligent learning and self-configuration capabilities. A popular commercial robotic tool, i.e. the Lego Mindstorms robot, has been used for testing and implementing this system. Tests have been performed both in simulations and in a real Lego robot. Experimental results show that, compared to other online optimization techniques and to empiric PID tuning procedures, 3SOME guarantees a robust and efficient control behaviour, thus representing a valid alternative for self-tuning control systems.