机械臂最优运动规划问题的混合粒子群算法

多关节机械臂路径规划是一个高度受限的非线性优化问题,很难找到单一的优化解.提出一种基于单纯形算法和粒子群算法的混合算法,以解决机械臂的路径规划问题.仿真试验表明,相较于常规的A*算法,该混合算法具有更高的求解精度.     

基于模糊力控制算法的移动机器人避障控制

根据机器人的末端执行器和外界环境表面接触与移动机器人避障控制的相似点,将力/位置控制成功应用到移动机器人的避障控制领域内.对新颖的移动机器人避障控制算法是通过在移动机器人和障碍物之间形成虚拟力场,且对其进行整定以使两者之间能保持期望的距离.因为机器人动力学模型和障碍物的不确定性会对避障控制性能造成影响,为避免碰撞,采用模糊PD的智能混合力/位置控制来整定机器人和障碍物精确距离的力场.通过仿真研究证明了算法的有效性,可为机器人设计提出可靠依据.     

基于简单模糊逻辑的冗余度机器人动力学路径规划新方法

论文提出了基于模糊逻辑的冗余度机器人避障算法,算法中利用模糊规则自动调整避障控制参数,使机器人在最短的时间内做出快速回避反应,提高了系统的智能性;另一方面,算法中利用动力学控制代替了位置控制,减少了避障过程中,由于速度突变引起的关节冲击力,提高了系统使用寿命。最后通过一平面三连杆三自由度机器人进行仿真研究,结果证实了该算法的有效性。     

Determination of optimum robot base location considering discrete end-effector positions by means of hybrid genetic algorithm

The performance of a robot manipulator during a process depends on its position relative to the corresponding path. An ill-placed manipulator risks inefficient operation as well as blocks due to singularities. The paper deals with an optimization algorithm to determine the base position and the joint angles of a spatial robot, when the end-effector poses are prescribed, avoiding the singular configurations. The optimization problem is solved through a hybrid heuristic method that combines the advantages of a genetic algorithm, a quasi-Newton algorithm and a constraints handling method. Six cases of a 6-DOF manipulator are studied to verify the feasibility of the proposed algorithm.     

System centroid position based tipover stability enhancement method for a tracked search and rescue robot

Tipover may cause fatal damages to the mobile robot system during obstacle crossing or stair climbing, and the system centroid position (SCP) is very important for the tipover stability. By monitoring the SCP, it is possible to estimate the risk of tipover and take appropriate actions to prevent the incident from happening. This paper proposes a new tipover avoidance method for enhancing the tipover stability of a tracked mobile manipulator by online adjusting the SCP. The tipover stability criteria for the robot are discussed based on the orientation data from a three-axial gyroscope and the SCP calculation. The velocity kinematic model of the manipulator for SCP adjustment is also presented in this paper. In addition, a redundancy resolution method is employed in order to improve the performance of the robot. The proposed method is applied to a search and rescue robot consists of a four degree of freedom manipulator and a tracked mobile base, and the effectiveness of this method is demonstrated by experimental results.     

Prediction of geometric errors of robot manipulators with Particle Swarm Optimisation method

This paper reports on the prediction of the expected positioning errors of robot manipulators due to the errors in their geometric parameters. A Swarm Intelligence (SI) based algorithm, which is known as Particle Swarm Optimization (PSO), has been used to generate error estimation functions. The experimental system used is a Motoman SK120 manipulator. The error estimation functions are based on the robot position data provided by a high precision laser measurement system. The functions have been verified for three test trajectories, which contain various configurations of the manipulator. The experimental results demonstrate that the positioning errors of robot manipulators can be effectively predicted using some constant coefficient polynomials whose coefficients are determined by employing the PSO algorithm. It must be emphasized that once the estimation functions are obtained, there may be no need of any further experimental data in order to determine the expected positioning errors for a subsequent use in the error correction process.     

Simulation of a SCARA robot with PD and learning controllers

In this study, a SCARA robot manipulator is simulated under PD and learning based controllers. The trajectory following performance of the robot is studied against these controllers. The adaptive/learning hybrid controller scheme and learning controller method are utilized as learning based controllers. The results of simulations show that, learning algorithm based controllers reduce the position tracking error effectively. The hybrid adaptive/learning controller has similar performance as the learning controller although it uses partial state information and compensates both mechanical and electrical dynamics, whereas the learning controller needs both position and velocity measurements neglecting electrical dynamics.     

A genetic approach to motion planning of redundant mobile manipulator systems considering safety and configuration

This article presents a genetic algorithm approach to multi-criteria motion planning of mobile manipulator systems. For mobile robot path planning, traveling distance and path safety are considered. The workspace of a mobile robot is represented as a grid by cell decomposition, and a wave front expansion algorithm is used to build the numerical potential fields for both the goal and the obstacles. For multi-criteria position and configuration optimization of a mobile manipulator, least torque norm, manipulability, torque distribution and obstacle avoidance are considered. The emphasis of the study is placed on using genetic algorithms to search for global optimal solutions and solve the minimax problem for manipulator torque distribution. Various simulation results from two examples show that the proposed genetic algorithm approach performs better than the conventional methods.     

Adaptive neuro fuzzy based hybrid force/position control for an industrial robot manipulator

In this paper an ANFIS-PD+I (AFSPD+I) based hybrid force/position controller has been proposed which works effectively with unspecified robot dynamics in the presence of external disturbances. A constraint is put to limit the movement of manipulator in XY Cartesian coordinates. The validity of the proposed controller has been tested using a 6-degree of freedom PUMA robot manipulator. The performance comparison have been done with the fuzzy proportional derivative plus integral, fuzzy proportional integral derivative and conventional proportional integral derivative controllers subjected to the same data set with proposed controller. The projected AFSPD+I controller adhered to the desired path closer and smoother than the other mentioned controllers.     

Verification of throwing operation by a manipulator with variable viscoelastic joints with straight-fiber-type artificial muscles and magnetorheological brakes

The performance of a robot can be enhanced by increasing its output. However, increasing the output of rigid actuators such as motors and hydraulic actuators will likely increase the weight of the robot. Conversely, organisms such as human beings achieve high output within a short time by accumulating and releasing the elastic energy stored in their muscles; thus, providing an instantaneous force. Moreover, the viscoelastic properties of muscle enable organisms to control their instantaneous force outputs and overall movements. Therefore, in this study, we developed a manipulator with two-degree-of-freedom (DOF) variable viscoelastic joints. The manipulator comprised straight-fiber-type artificial muscles and a magnetorheological (MR) brakes. The ability of a manipulator to generate controlled movement from an instantaneous force was tested in a throwing operation. This simple two-DOF variable viscoelastic manipulator with apparent viscosity control by the MR brakes achieved successful throwing motions. However, it was not possible to calculate the experimental parameters from the target operation in previous study. Therefore, we focused on particle swarm optimization (PSO) as a parameter search method. In this paper, we try to optimize parameters of the throwing movement by combining the spring model of a two-DOF variable viscoelastic manipulator with the PSO method.     

On the decoupling of position and force controllers in constrained robotic tasks

In hybrid control of robot manipulators separate controllers are designed for force and position errors control. Controllers are designed either in task or joint space and their outputs combine to provide input torque to the manipulator. Position and force controllers performance in a constrained robotic task is affected by their interaction to a degree dependent on the controller's ability to reject disturbances. Ideally, decoupling of the two control loops is desired to achieve the best performance in position and force directions. In this article, analysis of control loop interactions is performed for contact and noncontact phases, and controller design requirements are developed to achieve maximum decoupling. Design requirements involve output subspace of each controller leading to control discontinuities for contact and noncontact phases. In the noncontact phase, satisfaction of design requirements leads to a fully linearized and decoupled system. When in contact with the constraining surface, design requirements eliminate disturbances in the force loop, but minimize disturbances in the position loop to an extent dependent on force loop performance. Known hybrid control schemes analysis is performed to reveal existence of control loop interactions in these schemes. Confirmation of theoretical analysis is done through simulation of a three revolute planar manipulator. © 1998 John Wiley & Sons, Inc.     

A force–impedance controlled industrial robot using an active robotic auxiliary device

A strategy to improve the performance of current commercial industrial robots is presented in this paper. This strategy involves cooperation of two robotic manipulators: the robotic controlled impedance device (RCID) and a commercial industrial robot. The RCID is a small six degrees-of-freedom (DOF) high bandwidth force–impedance controlled parallel manipulator, developed at the School of Engineering of the University of Porto (Portugal). The RCID works attached in series with a position controlled commercial industrial robot. Combination of the two manipulators behaves as a single manipulator having the impedance and force control dynamic performance of the RCID, as well as the workspace and trajectory tracking bandwidth of the industrial robot. Force–impedance control of the RCID, and experimental results on typical tasks that involve end-effector contact with uncertain environments of unknown stiffness are presented.     

Task decoupling in robot manipulators

Task decoupling in robotic manipulators implies that there is a subset of joints primarily responsible for the completion of a subset of the manipulator task. In this paper, we take a novel and general view of task decoupling in which we identify link subsystems primarily responsible for completion of a subset of the manipulator task components, which is not necessarily position or orientation. Our analysis leads to the discovery of other decoupled manipulator geometries never identified before, wherein the decoupled system is responsible for a subset of degress-of-freedom involving a hybrid combination of both position and orientation. Closed-form inverse kinematic solutions for these manipulator geometries are therefore guaranteed. Task decoupling also implied singularity decoupling wherein singularities of decoupled subsystems are equivalent to the manipulator singularities. The analysis leads to a novel and efficient method for identifying the singularities and solving the inverse kinematics problem of six-axes manipulators with decoupled geometries. The practicality of the concepts introduced is demonstrated through an industrial robot example involving a hybrid position and orientation decoupling.     

基于ROS的六自由度机械臂运动规划

针对传统机器人在复杂环境下的安全问题以及运动规划问题,采用开源机器人操作系统ROS搭建了机器人仿真平台,并进行运动规划。在ROS平台下,利用URDF文件完成机械臂3D建模;利用Movelt配置助手(setup assistant)配置机械臂模型并且生成启动文件。在Rviz中显示三维模型;利用Movelt完成对六自由度机械臂的运动规划,以及避障轨迹规划。结果表明,通过Rqt_plot导出机械臂运动过程中六个关节的位置关系信息,可为进一步改善和研究机械臂轨迹规划提供更加直观的方法。     

Collision free path-planning for cable-driven parallel robots

In this study, a path-planning method that has been developed for serial manipulators is adapted to cable-driven robots. The proposed method has two modes. The first one is active when the robot is far from an obstacle. In this mode, the robot moves toward the goal on a straight line. The second mode is active when the robot is near an obstacle. During this mode, the robot finds the best way to avoid the obstacle. Moreover, an algorithm is presented to detect the collision between the robot and the obstacle. A similar algorithm is also presented to avoid the collision of the cables with an obstacle. Some simulation results are shown, which are then validated experimentally using a built 4-cable-driven parallel manipulator. Although the path obtained between the initial and final poses may not be the shortest possible one, it guarantees finding a path, when it exists, no matter how cluttered the environment is.     

动态环境中基于改进粒子群的机器人路径规划

提出一种模糊隶属度函数对动态环境中机器人的运动状况进行建模,该建模方法不会无谓地牺牲机器人的可运动空间,可尽量减少机器人路径规划的约束强度;同时提出通过调整位置加权趋向无约束最优解的算子改进粒子群算法,提高算法的寻优速度。仿真结果表明,通过两者结合,可快速获得动态环境中的优化路径。     

Pose Planning for a Mobile Manipulator Based on Joint Motions for Posture Adjustment to End-Effector Error

This paper proposes a motion planning method for a mobile manipulator. In general, humans can grasp an object by various ways which depend on object posture, position and so on. The objective of this paper is to present how to detect the pose of a mobile manipulator under the condition that several ways of grasping are given to the robot. Motion errors and object position errors are considered to detect robot pose in our method because these affect the grasp motion of the robot hand. Coping with these errors, we will propose an effective pose searching method for a mobile manipulator from numerous pose candidates. The performance of the proposed method is illustrated by simulation and experiment.     

Intelligent tracking control for robot manipulator including actuator dynamics via TSK-type fuzzy neural network

In this paper, a Takagi-Sugeno-Kang-type fuzzy-neural-network control (T-FNNC) scheme is constructed for an n-link robot manipulator to achieve high-precision position tracking. According to the concepts of mechanical geometry and motion dynamics, the dynamic model of an n-link robot manipulator including actuator dynamics is introduced initially. However, it is difficult to design a suitable model-based control scheme due to the uncertainties in practical applications, such as friction forces, external disturbances and parameter variations. In order to cope with this problem, a T-FNNC system without the requirement of prior system information and auxiliary control design is investigated to the joint position control of an n-link robot manipulator for periodic motion. In this model-free control scheme, a five-layer fuzzy-neural-network is utilized for the major control role, and the adaptive tuning laws of network parameters are established in the sense of projection algorithm and Lyapunov stability theorem to ensure the network convergence as well as stable control performance. In addition, experimental results of a two-link robot manipulator actuated by dc servomotors are provided to verify the effectiveness and robustness of the proposed T-FNNC methodology.     

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.     

Stability of hybrid position and force control for robotic manipulator with kinematics and dynamics uncertainties

Most research so far on hybrid position and force control laws of robotic manipulator has assumed that knowledge of kinematics is known exactly. In the presence of modeling errors, it is unknown whether the stability of the constrained robot system can still be ensured. In this paper, stability and setpoint control problems of constrained robot with kinematics and dynamics uncertainties are formulated and solved. We shall show that the manipulator end-effector's motion is asymptotically stable even in the presence of such uncertainties.