一种改进 RRT* 结合四次样条的协调路径规划方法

针对空间机器人抓捕空间非合作目标的在轨服务任务,同时考虑机器人运动学约束和动力学约束,提出一种分层式的自由漂浮双臂空间机器人协调路径规划方法. 首先,在路径规划层面上基于 RRT* 算法分别规划双臂末端执行器在笛卡尔空间下的初始可行路径,为双臂设置独立的采样空间,保证路径规划过程中双臂系统不发生自身碰撞. 然后,在轨迹规划层面上利用四次样条曲线平滑 RRT* 算法生成的初始路径,设计满足样条曲线的一阶、二阶及三阶微分连续约束,同时考虑机械臂末端执行器的初末速度约束条件、初始加速度约束条件,得到适合于空间机器人执行的动力学可行的平滑 轨迹.最后,计算所规划路径的最大速度、最大加速度与机械臂末端执行器物理极限值的比值,取最小上限,即为最少路径规划时间. 所提路径规划方法能够设计出满足特定路径点约束的协调路径,且所设计的路径考虑了机械臂的物理限制条件,通过对自由漂浮双臂空间机器人进行仿真试验,验证了所提路径规划算法的有效性.      

COORDINATED PATH PLANNING BY INTEGRATING IMPROVED RRT$^{\small*}$ AND QUARTIC SPLINE$^{\bf 1)}$

针对空间机器人抓捕空间非合作目标的在轨服务任务,同时考虑机器人运动学约束和动力学约束,提出一种分层式的自由漂浮双臂空间机器人协调路径规划方法. 首先,在路径规划层面上基于 RRT* 算法分别规划双臂末端执行器在笛卡尔空间下的初始可行路径,为双臂设置独立的采样空间,保证路径规划过程中双臂系统不发生自身碰撞. 然后,在轨迹规划层面上利用四次样条曲线平滑 RRT* 算法生成的初始路径,设计满足样条曲线的一阶、二阶及三阶微分连续约束,同时考虑机械臂末端执行器的初末速度约束条件、初始加速度约束条件,得到适合于空间机器人执行的动力学可行的平滑 轨迹.最后,计算所规划路径的最大速度、最大加速度与机械臂末端执行器物理极限值的比值,取最小上限,即为最少路径规划时间. 所提路径规划方法能够设计出满足特定路径点约束的协调路径,且所设计的路径考虑了机械臂的物理限制条件,通过对自由漂浮双臂空间机器人进行仿真试验,验证了所提路径规划算法的有效性.     

Robust control of flexible-joint robots using voltage control strategy

So far, control of robot manipulators has frequently been developed based on the torque-control strategy. However, two drawbacks may occur. First, torque-control laws are inherently involved in complexity of the manipulator dynamics characterized by nonlinearity, largeness of model, coupling, uncertainty and joint flexibility. Second, actuator dynamics may be excluded from the controller design. The novelty of this paper is the use of voltage control strategy to develop robust tracking control of electrically driven flexible-joint robot manipulators. In addition, a novel method of uncertainty estimation is introduced to obtain the control law. The proposed control approach has important advantages over the torque-control approaches due to being free of manipulator dynamics. It is computationally simple, decoupled, well-behaved and has a fast response. The control design includes two interior loops; the inner loop controls the motor position and the outer loop controls the joint position. Stability analysis is presented and performance of the control system is evaluated. Effectiveness of the proposed control approach is demonstrated by simulations using a three-joint articulated flexible-joint robot driven by permanent magnet dc motors.     

Artemia swarm dynamics and path tracking

Artemia larvae may show swarming organization under the presence of a light spot, while being insensitive to several other external stimuli. In this paper, the dynamics of the Artemia population in response to this kind of stimuli has been exploited to design a robot moving inside the water and able to lead the direction of the group. The robot therefore implements external leadership, by driving the Artemia population along a set of desired trajectories. Experimental results and simulations based on a model of Artemia motion confirmed the suitability of the approach.     

A unified solution to swing-up control for n-link planar robot with single passive joint based on virtual composite links and passivity

This paper concerns the swing-up control of an n-link revolute planar robot with any one of the joints being passive. The goal is to design and analyze a swing-up controller that can bring the robot into any arbitrarily small neighborhood of the upright equilibrium point, at which all the links are in the upright position. We present a unified solution based on the notion of virtual composite link (VCL), which is a virtual link made up of one or more active links. By using the angles of two series of VCLs separated by the passive joint and using the total mechanical energy of the robot, we design a swing-up controller and analyze the global motion of the robot under the controller. The main new results of this paper are: (1) we obtain a lower bound for each control gain related to the angle of each VCL such that the closed-loop system has only one undesired equilibrium point in addition to the upright equilibrium point, and we present an original proof of the conditions on the control gains for a class of n-link underactuation-degree-one planar robots with an active first joint; (2) we provide a bigger control gain region for achieving the control objective than those of previous results on three- and n-link robots with a passive first joint; (3) we validate the theoretical results via numerical simulations on a 4-link robot with the passive joint in each of the four positions. This paper gains an insight into the passivity-based control of underactuated multiple-DOF systems.     

Prototype design of a translating parallel robot

The paper describes the mechanical design of a parallel manipulator for motions of pure translation, whose kinematic analysis has shown very good performances such as a large workspace and small overall dimensions of the mobile platform; in particular, the “Cartesian” structure of the machine allowed to obtain constant accuracy and kinematic properties throughout the workspace. The structural design has minimized the mass of the moving links and, by the combined use of FEM and multibody codes, allowed to take into consideration the high stresses coming from inertial forces and to evaluate a-priori the resulting dynamic properties. A physical prototype has just been built in order to validate the developed models and assess the actual robot performances in real operating conditions. The present research has been partially co-funded by the Italian Ministry of Research and University and by the Polytechnic University of Marche under PRIN03 project “Design and prototyping of application-oriented mini-PKM”.     

柔性关节-柔性臂空间机器人的神经网络自适应反演控制及双重柔性振动抑制

空间机器人系统的柔性主要体现在空间机器人的臂杆和连接各臂杆之间的铰关节。由于空间机器人系统结构的复杂性,以往研究人员对同时具有柔性关节和柔性臂的系统关注不够。为此探讨了参数未知柔性关节-柔性臂空间机器人系统的动力学模拟、轨迹跟踪控制算法设计和关节、臂杆双重柔性振动的主动抑制问题。首先,采用多体动力学建模方法并结合漂浮基空间机器人固有的线动量和角动量守恒动力学特性,推导了系统的动力学方程。以此为基础,考虑到空间机器人实际应用中各关节铰具有较强柔性的情况,引入一种关节柔性补偿控制器解决了传统奇异摄动法应用受关节柔性限制问题,导出了适用于控制系统算法设计的数学模型。然后,利用该模型,基于反演思想在慢时标子系统中设计神经网络自适应控制算法来补偿系统参数未知和柔性关节引起的转动误差,实现系统运动轨迹跟踪性能;针对快时标子系统,设计了鲁棒最优控制算法抑制因柔性关节及柔性臂引起的系统双重弹性振动,保证系统的稳定性。最后,通过仿真对比实验验证了所设计控制算法的有效性。     

State-Space Generalized Predictive Control for Redundant Parallel Robots

Abstract

The article deals with the design and properties of generalized predictive control (GPC) for path control of redundant parallel robots. Redundant parallel classification means redundant number of actuators, i.e., more actuators than degrees of freedom of the robot. Control of such structures suffers from several new control problems like potential inconsistency of steady state positions or nonuniqueness of control actions. The article explains classical direct derivation of GPC and its modification based on square root two-step design of control actions for solving the control problems. As an example for verification of algorithms, a prototype of a planar redundant parallel robot is used. Both design approaches are compared and several possibilities of extensions are presented for taking into consideration additional requirements, like smooth course of actuators or fulfillment of the anti-backlash condition.     

Mathematical Modeling, Control, Computer Simulation and Laboratory Experiments of a Spatial Servopneumatic Parallel Robot

In this paper, the special construction of a parallel robot, called spatial servopneumatic multi-axis test facility, will be discussed. The investigations include the following aspects: (i) the laboratory set-up of the robot, (ii) various results obtained in laboratory experiments, taking into account quite different control algorithms and command-input signals, (iii) a comparison of the laboratory experiments with the computer simulations of Part I of this paper, and ({vi}) a quality check of the results compared with the cost of the different controller realizations. The results of both the computer simulations and the laboratory experiments show: (i) The dynamic behavior of the parallel structure can be tremendously improved by using sophisticated nonlinear control algorithms. (ii) This improvement has to be paid by a drastically increased amount of work for deriving the model equations and control algorithms, and by augmented hardware cost of the sensing elements and controller electronics. (iii) Carefully developed model equations and identified model parameters provide theoretical models of the complex parallel structure that are very close to reality. This enables the design engineer to systematically investigate constructive alternatives of the design parameters, sensor and actuator concepts, and control strategies of the MAP prior to their hardware realization.This work has been supported by the German Science Foundation (DFG) under Contract No. Ha 1666/6-3.     

一类新型仿生起竖结构设计及其动力学分析

由于生物能够通过丰富的运动形式完成特定的任务, 仿生设计方法受到了学者们的广泛关注. 蚯蚓在各种环境中具有出色的移动能力和适应性, 受此启发, 仿蠕虫机器人被提出并应用在搜救、医疗等领域. 然而现有的仿蠕虫机器人一般通过体节的轴向变形实现直线运动, 无法实现类似蛇类生物的起竖功能. 为了解决现有的仿蠕虫机器人无法起竖的问题, 本文提出了一种具有非线性多稳态性质的仿生柔性关节, 并在此基础上构建了多节仿生起竖结构以实现类似尺蠖、蛇等生物的起竖功能. 首先, 本文提出了一种仿生起竖关节模型, 推导了多节仿生起竖结构的总势能表达式, 从而建立了多节仿生起竖结构的动力学模型; 随后, 基于多节仿生起竖结构总势能的表达式和多元函数极值原理, 提出了实现需求起竖构型的结构参数设计准则, 利用动力学模型验证了结构参数设计准则的有效性, 并研究了需求构型的触发条件; 最后, 针对不同起竖节数的设计需求, 设计了相应节数的仿生起竖结构. 研究结果表明, 结构参数设计准则能够使得多节仿生起竖结构达到需求的仿生起竖构型, 并在需求构型处保持稳定平衡; 此外, 定义了初始激励与起竖构型的比例系数单调性变量, 并基于仿生起竖结构不同稳态的吸引盆揭示了上述变量构成的构型触发准则, 这为仿生起竖结构的构型切换提供了理论依据. 本文提出的仿生起竖结构对仿蠕虫机器人的功能拓展具有参考价值和指导意义, 也是对仿生设计理论的进一步完善.      

Dynamic analysis of microrobots with Coulomb friction using harmonic balance method

In this paper, we investigate the dynamic analysis of a strongly nonlinear microrobot using a three-term harmonic balance method. The employed locomotion concept, namely “friction drive principle,” is based on the superposition of a horizontal vibration at the interface between the robot and work floor and an active variation of friction force, obtained by the vertical vibration of the base at the same interface. The equation of motion for the system reveals a parametrically excited oscillator with discontinuity for which the elastic force term is proportional to a signum function. The obtained periodic solution not only is of high accuracy, but also can predict the contribution of the friction coefficient in the average velocity of the slider. Results show that the velocity and the step efficiency of motion depend almost sinusoidally on the phase shift between the horizontal and the vertical vibration. Unlike traditional analytical techniques and in agreement with both numerical simulations and experimental results reported in the literature, the utilized method demonstrates that the maximum average velocity occurs at a phase shift that varies with respect to system’s configuration parameters. Besides, the effect of variation of different configuration parameters on the behavior of this type of microrobots has been studied and the maximum achievable performance in terms of velocity and the step efficiency has been evaluated.     

A particle swarm optimization approach for fuzzy sliding mode control for tracking the robot manipulator

In this paper, an optimal fuzzy sliding mode controller is used for tracking the position of robot manipulator, is presented. In the proposed control, initially by using inverse dynamic method, the known sections of a robot manipulator’s dynamic are eliminated. This elimination is done due to reduction over structured and unstructured uncertainties boundaries. In order to overcome against existing uncertainties for the tracking position of a robot manipulator, a classic sliding mode control is designed. The mathematical proof shows the closed-loop system in the presence of this controller has the global asymptotic stability. Then, by applying the rules that are obtained from the design of classic sliding mode control and TS fuzzy model, a fuzzy sliding mode control is designed that is free of undesirable phenomena of chattering. Eventually, by applying the PSO optimization algorithm, the existing membership functions are adjusted in the way that the error tracking robot manipulator position is converged toward zero. In order to illustrate the performance of the proposed controller, a two degree-of-freedom robot manipulator is used as the case study. The simulation results confirm desirable performance of optimal fuzzy sliding mode control.     

Utilization of nonlinear vibrations of soft pipe conveying fluid for driving underwater bio-inspired robot

Creatures with longer bodies in nature like snakes and eels moving in water commonly generate a large swaying of their bodies or tails, with the purpose of producing significant frictions and collisions between body and fluid to provide the power of consecutive forward force. This swaying can be idealized by considering oscillations of a soft beam immersed in water when waves of vibration travel down at a constant speed. The present study employs a kind of large deformations induced by nonlinear vibrations of a soft pipe conveying fluid to design an underwater bio-inspired snake robot that consists of a rigid head and a soft tail. When the head is fixed, experiments show that a second mode vibration of the tail in water occurs as the internal flow velocity is beyond a critical value. Then the corresponding theoretical model based on the absolute nodal coordinate formulation (ANCF) is established to describe nonlinear vibrations of the tail. As the head is free, the theoretical modeling is combined with the computational fluid dynamics (CFD) analysis to construct a fluid-structure interaction (FSI) simulation model. The swimming speed and swaying shape of the snake robot are obtained through the FSI simulation model. They are in good agreement with experimental results. Most importantly, it is demonstrated that the propulsion speed can be improved by 21% for the robot with vibrations of the tail compared with that without oscillations in the pure jet mode. This research provides a new thought to design driving devices by using nonlinear flow-induced vibrations.

     

变长度弹性伸缩腿双足机器人动力学与控制

研究了半被动双足机器人的平面稳定行走的控制问题．基于弹簧质点模型，采用拉格朗日方法分别得到双足机器人单支撑阶段与双支撑阶段的动力学方程，对机器人系统的动力学方程求得周期解．应用非线性系统状态反馈线性化理论，在双足机器人的单支撑阶段和双支撑阶段中，通过控制双足机器人的腿长度，实现稳定的周期行走．在理论分析的基础上，对控制算法进行了仿真与研究．结果表明：在周期行走过程中，文中采用的变长度控制算法可以使双足机器人克服外界的干扰，并具有较强的抗干扰性．     

Trajectory planning and tracking control for autonomous bicycle robot

Control of the autonomous bicycle robot offers considerable challenges to the field of robotics due to its nonholonomic, underactuated, and nonminimum-phase properties. Furthermore, instability and complex dynamic coupling make the trajectory planning of the bicycle robot even more challenging. In this paper, we consider both trajectory planning and tracking control of the autonomous bicycle robot. The desired motion trajectory of the contact point of the bicycle’s rear wheel is constructed using the parameterized polynomial curve that can connect two given endpoints with associated tangent angles. The parameters of the polynomial curve are determined by minimizing the maximum of the desired roll angle’s equilibrium of the bicycle, and this optimization problem is solved by the particle swarm optimization algorithm. Then, a control scheme that can achieve full-state trajectory tracking while maintaining the bicycle’s balance is proposed by combining a planar trajectory tracking controller with a roll angle balance controller. Simulation results are presented to demonstrate the effectiveness of the proposed method.     

L'espace articulaire de la Robotique Industrielle est un espace vectorielIndustrial Robotics joint space is a vector space

The mathematical modelling of industrial robots is based on the vectorial nature of the n-dimensional joint space of the robot, defined as a kinematic chain with n degrees of freedom. However, in our opinion, the vectorial nature of the joint space has been insufficiently discussed in the literature. We establish the vectorial nature of the joint space of an industrial robot from the fundamental studies of B. Roth on screws. To cite this article: B. Tondu, C. R. Mecanique 331 (2003).     

Requirements and system design for a robot performing selective cleaning in young forest stands

Cleaning is a silvicultural tending operation, primarily aimed at improving the growing conditions of the remaining trees in young stands (ca. 3 m of height). The cost of cleaning has increased in comparison to other forest operations, and the annually cleaned area has decreased in Sweden. Therefore, cleaning with robots might be the key to improve profitability. This paper aims at assessing some design requirements, and suggesting an architecture for a robot cleaning in young forest stands, based on reviewed literature and our own research. The results of cleaning performed by robots have to reach acceptable results and be done at a competitive cost. The robot has to find, select, and handle trees in the whole assigned area according to given instructions. Furthermore, it must be safe for humans, capable of moving safely within the forest environment, and be able to handle snow and other prevalent boreal weather conditions. The vehicle’s size and mass are of importance, and bear on its ability to manoeuvre among remaining stems. Generally, the robot must be capable of operating independently and unattended for several hours in a dynamic and non-deterministic environment. Obstacle avoidance and target identification are identified as the most difficult problems. Machine vision, radar, and laser scanners are promising techniques for both obstacle avoidance, tree identification, and tool control. The proposed architecture is based on a hybrid between the reactive and the hierarchical robot paradigms.     

ZMP based neural network inspired humanoid robot control

This paper concerns ZMP-based control that is inspired by artificial neural networks for humanoid robot walking on varying sloped surfaces. Humanoid robots are currently one of the most exciting research topics in the field of robotics, and maintaining stability while they are standing, walking or moving is a key concern. To ensure a steady and smooth walking gait of such robots, a feedforward type of neural network architecture, trained by the back-propagation algorithm, is employed. The inputs and outputs of the neural network architecture are the ZMPx and ZMPy errors of the robot, and the x, y positions of the robot, respectively. The neural network developed allows the controller to generate the desired balance of the robot positions, resulting in a steady gait for the robot as it moves around on a flat floor, and when it is descending or ascending slopes. In this paper, experiments of humanoid robot walking are carried out, in which the actual position data from a prototype robot are measured in real-time situations, and fed into a neural network inspired controller designed for stable bipedal walking. In addition, natural walking motions on the different surfaces with varying slopes are obtained and the performance of the resulting controller is shown to be satisfactory.     

基于虚拟力概念的柔性臂空间机器人模糊退步自适应控制算法设计

讨论了漂浮基柔性臂空间机器人系统的动力学模拟、运动轨迹跟踪控制算法设计及柔性振动主动抑制。采用多体动力学建模方法并结合假设模态法,建立了漂浮基柔性臂空间机器人的系统动力学模型。基于该模型,针对系统惯性参数未知情况,提出了刚性运动基于模糊基函数网络自适应调节的退步控制算法,以完成柔性臂空间机器人载体姿态及机械臂各关节铰的协调运动。然后,为了主动抑制系统柔性振动,运用虚拟力的概念,构造了同时反映柔性模态和刚性运动轨迹的混合期望轨迹,通过改造原有的控制算法,提出了基于虚拟力概念的模糊退步自适应控制算法;这样不但保证了之前刚性运动控制方案对模型不确定的鲁棒性,而且能主动抑制柔性振动,从而提高了轨迹跟踪性能。理论分析及数值仿真算例均表明了控制方法的可行性。     

机器人无标定视觉伺服控制研究进展

视觉伺服控制是机器人系统重要的控制手段. 相比传统的在标定条件下使用的视觉伺服系统,无标定视觉伺服系统具有更高的灵活性与适应性,是机器人伺服控制系统未来重要的发展方向和研究热点. 本文从目标函数选择、控制器设计、运动轨迹规划三方面综述了无标定视觉伺服控制系统近年来的主要研究进展. 首先根据目标函数的形式,分析了基于位置的视觉伺服、基于图像的视觉伺服以及混合视觉伺服各自的特点与应用;在控制器设计方面,根据是否在设计过程中考虑机器人的非线性动力学特性,分别介绍了考虑机器人运动学与考虑机器人动力学的无标定视觉伺服控制器的设计,重点突出了雅克比矩阵的构造与估计方法;针对无标定视觉伺服系统运动轨迹可能存在的问题,从空间轨迹优化与障碍规避的角度,阐述了已有的可行解决方案. 最后,基于当前的研究进展展望了无标定视觉伺服的未来研究方向.