多杆空间柔性机器人递推Lagrange动力学建模和仿真

研究了多杆空间柔性机器人的动力学问题.运用Lagrange方法,结合齐次变换矩阵,推导得到了多杆空间柔性机器人动力学方程,在推导过程中采用了运动学递推策略以提高计算效率.建模时除考虑柔性构件的横向弯曲变形外,还计及了构件的扭转变形.基于上述理论研制了多杆空间柔性机器人动力学仿真软件,并对一空间柔性机器人进行了动力学仿真计算,验证了理论和软件的先进性能.     

空间机器人组装超大型结构的动力学分析北大核心CSCD

超大型航天结构具有超大柔性、超低固有频率的特点,空间机器人在轨组装时应尽可能避免激起超大型结构的柔性振动.空间机器人组装超大型结构模块的过程分成抓捕阶段、位姿调整与稳定阶段、安装阶段和爬行阶段.通过对安装阶段的动力学与控制研究,提出共线安装的轨迹规划方法,有效避免了柔性结构振动.首先,采用自然坐标法和绝对节点坐标法建立主结构-空间机器人-待组装结构的在轨组装系统动力学模型.然后,将共线安装的要求转化为空间机器人的轨迹规划约束,要求空间机器人质心到主结构/待组装结构的距离保持不变,实现共线安装的轨迹规划.数值仿真表明:提出的组装方法在组装过程中可有效避免超大型结构的横向运动,降低夹持力矩.最后,分析了系统参数对组装过程动力学响应的影响,为超大型航天器的在轨组装提供了参考.     

技术柔性、柔性生产与柔性技术的价值

在产品市场和要素市场存在不确定性的条件下,将企业的生产行为和技术柔性水平的选择纳入一个统一框架进行分析,给出了柔性技术的价值函数及其特征.结果表明,给定技术柔性水平,柔性生产行为价值不会低于非柔性生产行为的价值;给定生产行为,柔性技术的价值不会随着其柔性增加而降低.进一步,在一定条件下,柔性生产行为比非柔性生产行为更具价值,柔性技术的价值随着其柔性水平的增加而增加.     

一类柔性梁系统的谱分析和半群生成

讨论了一类双臂三关节柔性梁系统的分析问题．首先,建立了一个与柔性梁的偏微分方程组及初值边值条件相应的希尔伯特空间中的一阶发展系统．接着讨论系统算子的谱性质和半群性质．最后借助系统算子的谱性质和半群性质提出并证明了柔性梁系统的指数稳定性．     

具有确定运动姿势的柔性体的动力学分析研究

讨论了具有确定运动姿态的柔性多体系统的非线性动力学控制方程． 将飞行器在空间的运动看作是已知的,分析了飞行器上的挠性构件对飞行器运动和姿态的影响,利用假设模态,将挠性构件的变形,看作是空间直角坐标轴方向的线元振动所构成的,根据动力学中的Kane方法,建立了动力学方程,方程中包含表示弹性变形的结构刚度矩阵及表示变形体非线性变形几何刚度矩阵,方程推导从应力-应变关系入手,使用了有限元法．经简化,得到了带帆板结构的平面挠性体对飞行器运动影响的动力学方程,这种方程可通过计算机实现其数值解．     

一类柔性臂机器人的稳定性

本文研究了一类柔性臂机器人的控制问题,且柔性臂的弯曲振动与扭转振动的耦合作用表现在边界方程中。本文运用算子谱理论、算子半群理论等,得到系统的主算子生成的C0-半群的具体表示式,并证明了半群的解析性、非紧性及非一致指数稳定性。     

一个刚柔耦合的火箭发射架动力学模型

对刚柔耦合火箭发射架进行了动力学建模．将火箭发射架分成两个子系统,一个是多刚体系统,另一个是空间大位移运动的柔性发射管．先对这两个子系统的动力学分别建模,然后再考虑这两个系统之间的动力学耦合,从而获得整个系统的动力学模型．这种方法把复杂系统离散成简单系统,再由现存的简单系统的动力学模型组合成整个系统的动力学模型,使得整个建模过程高效、方便．     

双臂空间机器人姿态、关节协调运动基于RBF神经网络的自适应控制算法

讨论了载体位置无控、姿态受控情况下,双臂空间机器人姿态、关节协调运动的控制问题．由Lagrange第二类方法及系统动量守恒关系,建立了漂浮基双臂空间机器人的系统动力学方程．以此为基础,借助于RBF神经网络技术、GL矩阵及其乘积算子定义,对双臂空间机器人系统进行了神经网络系统建模;之后针对双臂空间机器人所有惯性参数均未知的情况,设计了双臂空间机器人载体姿态与机械臂各关节协调运动基于RBF神经网络的自适应控制算法．提出的控制算法不要求系统动力学方程具有惯常的关于惯性参数的线性性质,且无需预知系统惯性参数的任何信息,也无需对神经网络进行离线训练、学习,因此更适于实时应用．一个平面漂浮基双臂空间机器人系统的数值仿真,证实了该控制算法的有效性．     

基于时间有限元方法的旋转柔性叶片动力学响应分析

将时间有限元方法引入到柔性多体系统的数值计算中,研究了旋转柔性叶片系统的刚-柔耦合响应问题.首先,基于非线性梁理论,建立了旋转柔性叶片系统的中心刚体-柔性梁模型,构造柔性叶片系统考虑一次近似耦合的Lagrange函数;其次,采用假设模态方法对空间坐标进行离散,建立系统的时间有限元格式;最后,通过数值实验,分析了柔性叶片的动力学响应.该方法直接构造了系统的离散积分格式,并自动保证了该格式是保辛的,因而具有较高的数值精度和稳定性.数值结果表明:时间有限元可以有效地求解旋转柔性叶片系统内低频大范围运动与高频弹性振动之间的刚-柔耦合问题.     

柔性臂中的一类本征值问题

本文研究单杆件柔性机器人操作手中出现的如下本征值问题(?)得到了本征值所满足的特征方程,据此研究了相应本征值的分布.此外还给出了本征函数之间的直交关系.最后给出了本征值计算结果,验证了上述理论分析的正确性.     

Fast reinforcement learning for simple physical robots

In the past few years, the field of autonomous robot has been rigorously studied and non-industrial applications of robotics are rapidly emerging. One of the most interesting aspects of this field is the development of the learning ability which enables robots to autonomously adapt to given environments without human guidance. As opposed to the conventional methods of robots’ control, where human logically design the behavior of a robot, the ability to acquire action strategies through some learning processes will not only significantly reduce the production costs of robots but also improves the applicability of robots in wider tasks and environments. However, learning algorithms usually require large calculation cost, which make them unsuitable for robots with limited resources. In this study, we propose a simple two-layered neural network that implements a novel and fast Reinforcement Learning. The proposed learning method requires significantly less calculation resources, hence is applicable to small physical robots running in the real world environments. For this study, we built several simple robots and implemented the proposed learning mechanism to them. In the experiments, to evaluate the efficacy of the proposed learning mechanism, several robots were simultaneously trained to acquire obstacle avoidance strategies in the same environment, thus, forming a dynamic environment where the learning task is substantially harder than in the case of learning in a static environment and promising result was obtained.     

Distributed adaptive formation tracking using quantized feedback communication for networked mobile robots with unknown wheel slippage

In this study, we consider a quantized-feedback-communication-based control design problem for the distributed adaptive formation tracking of multiple nonholonomic mobile robots with unknown slippage constraints under capacity-limited network control environments. Uniform-hysteretic quantizers are employed to quantize all the inputs and states of robots and the quantized position information of each robot is only transmitted to neighboring robots through directed networks. Compared with existing literature related to the robot formation, the primary contribution of this paper lies in establishing a novel local adaptive control design methodology to deal with the discontinuity problem caused by using the quantized states of each follower and the quantized position communication of neighboring robots. In the proposed strategy, the communication of the orientations and velocities of neighboring robots is not required for the local control design of follower robots. Moreover, quantized-states-based adaptive compensation schemes are constructed for the effects of signal quantization and wheel slippage. Based on the analysis of quantization errors, the practical stability strategy of the overall closed-loop formation system is derived with the convergence of local tracking errors. Simulation results clarify the proposed formation strategy.     

Motion Planning for Multiple Robots

We study the motion-planning problem for pairs and triples of robots operating in a shared workspace containing n obstacles. A standard way to solve such problems is to view the collection of robots as one composite robot, whose number of degrees of freedom is d , the sum of the numbers of degrees of freedom of the individual robots. We show that it is sufficient to consider a constant number of robot systems whose number of degrees of freedom is at most d-1 for pairs of robots, and d-2 for triples. (The result for a pair assumes that the sum of the number of degrees of freedom of the robots constituting the pair reduces by at least one if the robots are required to stay in contact; for triples a similar assumption is made. Moreover, for triples we need to assume that a solution with positive clearance exists.) We use this to obtain an O(n ^d ) time algorithm to solve the motion-planning problem for a pair of robots; this is one order of magnitude faster than what the standard method would give. For a triple of robots the running time becomes O(n ^d-1 ) , which is two orders of magnitude faster than the standard method. We also apply our method to the case of a collection of bounded-reach robots moving in a low-density environment. Here the running time of our algorithm becomes O(n log n) both for pairs and triples. Received August 10, 1998, and in revised form February 17, 1999.     

Accurate and robust body position trajectory tracking of six-legged walking robots with nonsingular terminal sliding mode control method

Many tasks, such as walking in narrow environments, detecting land mines, coordinating with manipulators, and avoiding obstacles, demand multi-legged walking robots to accurately and robustly track predefined body trajectories. Tracking body position trajectory must be accurate and robust in these situations, but research on this topic is rarely carried out. In this study, we propose a nonsingular terminal sliding mode (NTSM) control algorithm to implement accurate and robust body position trajectory tracking of six-legged walking robots. The NTSM control algorithm is constructed on the basis of the body position trajectory tracking model with a new NTSM reaching law. The performance of the NTSM control method is evaluated through several verifications. Results demonstrate that the proposed algorithm is effective for accurate and robust body position trajectory tracking. The findings of this study can provide insights into improving multi-legged walking robots’ walking and operation abilities in special environments and expanding the application fields of these robots.     

Neuro-fuzzy technique for navigation of multiple mobile robots

In this paper, navigation techniques for several mobile robots are investigated in a totally unknown environment. In the beginning, Fuzzy logic controllers (FLC) using different membership functions are developed and used to navigate mobile robots. First a fuzzy controller has been used with four types of input members, two types of output members and three parameters each. Next two types of fuzzy controllers have been developed having same input members and output members with five parameters each. Each robot has an array of sensors for measuring the distances of obstacles around it and an image sensor for detecting the bearing of the target. It is found that the FLC having Gaussian membership function is best suitable for navigation of multiple mobile robots. Then a hybrid neuro-fuzzy technique has been designed for the same problem. The neuro-fuzzy technique being used here comprises a neural network, which is acting as a pre processor for a fuzzy controller. The neural network considered for neuro-fuzzy technique is a multi-layer perceptron, with two hidden layers. These techniques have been demonstrated in simulation mode, which depicts that the robots are able to avoid obstacles and reach the targets efficiently. Amongst the techniques developed neuro-fuzzy technique is found to be most efficient for mobile robots navigation. Experimental verifications have been done with the simulation results to prove the authenticity of the developed neuro-fuzzy technique.     

Model-based and model-free control of flexible-link robots: A comparison between representative methods

The paper presents a comparative study on representative methods for model-based and model-free control of flexible-link robots. Model-based techniques for the control of flexible-link robots can come up against limitations when an accurate model is unavailable, due to parameters uncertainty or truncation of high order vibration modes. On the other hand, several research papers argue that suitable model-free control methods result in satisfactory performance of flexible-link robots. In this paper two model-free approaches of flexible-link robot control are examined: (i) energy-based control, and (ii) neural adaptive control. The performance of the aforementioned methods is compared to the inverse dynamics model-based control, in a simulation case study for planar 2-DOF manipulators.     

A social approach for target localization: simulation and implementation in the marXbot robot

Foraging is a common benchmark problem in collective robotics in which a robot (the forager) explores a given environment while collecting items for further deposition at specific locations. A typical real-world application of foraging is garbage collection where robots collect garbage for further disposal in pre-defined locations. This work proposes a method to cooperatively perform the task of finding such locations: instead of using local or global localization strategies relying on pre-installed infrastructure, the proposed approach takes advantage of the knowledge gathered by a population about the localization of the targets. In our approach, robots communicate in an intrinsic way the estimation about how near they are from a target; these estimations are used by neighbour robots for estimating their proximity, and for guiding the navigation of the whole population when looking for these specific areas. We performed several tests in a simulator, and we validated our approach on a population of real robots. For the validation tests we used a mobile robot called marXbot. In both cases (i.e., simulation and implementation on real robots), we found that the proposed approach efficiently guides the robots towards the pre-specified targets while allowing the modulation of their speed.     

Automatic synthesis of kinematic structures of mechanisms and robots especially for those with complex structures

Structural synthesis of kinematic structures of mechanisms and robots is the first step in conceptual design. This paper proposes an automatic method for the structural synthesis of closed mechanisms and robots, even for those very complex structures seldom addressed till now. Loop theory based method is proposed to solve the problem of rigid sub-chain detection. The unique representation of graphs is obtained and used to detect isomorphism between kinematic chains. A human–machine interactive synthesis program is also developed, and the required kinematic structures of mechanisms and robots can be synthesized automatically. Some synthesis examples are given to show the efficiency and effectiveness of the method. The method is also helpful for automatic synthesizing other kinds of structures which can be represented by closed loop graphs, such as truss structures and molecular structures of organic substances.     

How to collect balls moving in the Euclidean plane

In this paper, we study how to collect n balls moving with a fixed constant velocity in the Euclidean plane by k robots moving on straight track-lines through the origin. Since all the balls might not be caught by robots, differently from Moving-target TSP, we consider the following 3 problems in various situations: (i) deciding if k robots can collect all n balls; (ii) maximizing the number of the balls collected by k robots; (iii) minimizing the number of the robots to collect all n balls. The situations considered in this paper contain the cases in which track-lines are given (or not), and track-lines are identical (or not). For all problems and situations, we provide polynomial time algorithms or proofs of intractability, which clarify the tractability-intractability frontier in the ball collecting problems in the Euclidean plane.     

Control Strategy of Hardware-in-the-Loop Simulator EPOS 2.0 for Autonomous Docking Verification

This paper briefly describes the hybrid simulator system called European Proximity Operation Simulator (EPOS 2.0) and the development of the hardware-in-the-loop (HIL) docking simulation concept. A critical requirement for the docking simulation of this HIL simulator is that the 6-DOF robots in the loop have to exactly mimic the dynamic response of the two satellites during a contact operation. The main challenges to meet this requirement are in the stiffness of the robots, which is unlike that of the satellites, as well as the time delay in the HIL simulator. The paper mainly presents the impedance parameter identification concept for matching the impedance between the satellites impact model and the EPOS robots. Finally it presents the preliminary results and future work. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)