具有壁面自适应能力的磁吸附爬壁机器人设计

为解决爬壁机器人在船舶货舱清洗过程中多壁面过渡的问题,该文设计了一种具有壁面自适应能力的磁吸附爬壁机器人,其包括磁吸附机构、自适应清洗机构和行走机构。该文首先通过建立机器人壁面过渡时的力学模型,得到机器人磁吸附力的分布特点,并据此设计出一种弧形磁吸附机构。然后利用 ANSYS Maxwell 3D 软件对该机构磁吸附力的分布进行优化,以满足壁面过渡的需要;此外,还在机器人前端设计了一种自适应清洗机构,通过对该机构的结构原理进行分析和实验,验证了清洗机构也具有壁面过渡能力。最后通过模拟船舶货舱壁面的实际特点,对机器人样机进行壁面过渡综合实验,完成了机器人舱底过渡行走实验和舱顶过渡行走实验,验证了该机器人的壁面自适应和舱内行走的能力。     

基于PIC单片机的六足机器人制作

基于仿生原理，以PIC单片机为控制器的核心，制作出了动作灵活、价格低廉以及模块化结构的六足机器人。该机器人能够严格按三角步态进行行走，实现诸如直线、转弯、躲避障碍物和追踪物体等行走功能。文中介绍了该机器人三角步态的行走原理、结构组成、控制系统和控制算法。     

正弦驱动与传感反馈结合的双足机器人仿生行走控制

提出了一种正弦驱动与传感反馈结合的双足机器人仿生行走控制方法．所有关节由正弦振荡器驱动, 较之相互耦合的神经元振荡器更加简单;控制参数具有明晰的物理意义,便于对运动模式进行调节．传感反馈表征 了机器人的运动状态,对于保证机器人的稳定行走起着至关重要的作用．将机器人碰地、碰膝等关键运动状态作为 相位反馈,对控制力矩进行相位重置,协调各关节动作,进而实现控制器、机器人、环境的耦合．同时,从节省能量 和仿生的角度,考虑了关节运动的被动特性,确定了各关节力矩的作用区间．仿真结果表明,该控制方法能实现机 器人稳定行走,并具有良好的能效性和自稳定性.     

基于六维力/力矩传感器和关节力矩的仿人机器人步态补偿算法

为实现仿人机器人的稳定行走,提出一种根据其足底六维力/力矩传感器信息、针对关节力矩的步态补偿算法．利用直流伺服电机的过载能力,来改善仿人机器人关节在大负载扰动下的动态性能．行走实验证明了该算法在离线实施过程中的有效性．     

水上行走机器人

水上行走机器人仿生水黾,利用液体的表面张力在水面上站立和行走,是近年来机器人研究领域新出 现的研究方向．本文综合分析了水上行走机器人相关理论与技术及系统研制等方面的国内外研究现状,并对该领域 未来的研究重点、关键技术和发展方向进行了展望．     

一种轮足复合式爬壁机器人机构建模与分析

基于行星轮系运动及双足真空吸附原理,提出了一种新型爬壁机器人机构,介绍了机构的构型及结构特点,推导了运动学方程,分析了沿直线行走、平面旋转和跨越交叉壁面三种运动模式．仿真结果表明该机构具有移动速度快、运动灵活、跨越交叉壁面能力强等特点．     

无动力双足步行机器人控制策略与算法

本文研究无动力双足步行机器人的建模、分析与控制问题. 基于能量的控制增加了机器人行走极限环的稳定性、鲁棒性, 扩大了极限环的收敛域; 角度不变控制使机器人的稳定行走步态摆脱了地面倾斜角度的限制; 把基于能量的控制与角度不变控制结合起来, 可以实现在不同倾斜角度地面上行走模式的切换. 基于能量的行走平均速度控制方法在平均速度与目标能量之间建立了联系, 能使机器人的行走产生新的稳定步态. 最后, 对无动力双足步行机器人的研究前景做了展望.     

三轮机器人直线行走问题分析

分析能力风暴UII机器人直线行走的常用控制方法,并提出利用指南针和数字PID混合控制的方法完成机器人直线行走,实践表明,该策略要优于其它控制方法,能够解决三轮机器人直线行走问题.     

使用零力矩点轨迹规划的四足机器人步态进化方法

通过对AIBO 机器人行走时身体摇摆现象的研究,提出一种使用零力矩点轨迹规划的步态控制方法． 与此同时,使用基于遗传算法的进化学习方法对步态控制参数进行优化．实验使用AIBO 机器人进行测试,机器人 使用该进化学习方法可自主地得到最优步态,其最优步态在保证稳定性的基础上最大速度达到了455 mm/s．实验结 果表明,应用该方法进行步态控制,机器人获取的最优步态不仅满足稳定性要求,而且对不平地形也具有较好的适 应能力．     

基于耦合驱动蛇形机器人机构设计与抬起的方法

文中设计了模块化的新型蛇形机器人关节单元．该单元具有三个自由度，其中摆动和俯仰自由度由耦合机构驱动来获得较大的力矩和活动空间．由该单元组成的蛇形机器人具有很强的驱动能力，能够抬起较多的单元．针对蛇形机器人的特点，给出了耦合机构的设计原则．对蛇形机器人抬起方法作了分析，得出采用适当规划方法能够抬起的最大单元数量是直接抬起的最大单元数量的平方关系的结论，并在此基础上分析了最大关节角对机器人抬起的影响，最后结合实例验证了上面分析结果．     

基于单神经元控制器的独轮自平衡机器人双闭环自适应控制

针对竖直飞轮的独轮自平衡机器人系统,提出了一种基于自适应单神经元控制的双闭环(DLSN)控制方法.根据对独轮自平衡机器人动力学模型的分析,将独轮自平衡机器人分成两个子系统,提出了一种具有俯仰倾角和横滚倾角内环、前向位移外环的双闭环自适应控制结构,其中每个控制环均由单神经元自适应控制器构成.仿真实验结果表明:所设计的基于双闭环单神经元自适应独轮自控制方法是有效的.     

采用神经元补偿器的机械手计算转矩控制算法

在本文中,我们提出了一种神经网络控制方法,以增 强在机械手控制中普遍使用的计算转矩控制结构．本算法将计算转矩控制结构,和神经网络 补偿结构有效地结合起来,使得在不增加控制结构复杂性的基础上,大大增强了控制的鲁棒 性．由于神经元补偿器具有很强的自适应性,因此在整个控制算法中无需事先精确了解机器 人的动力学参数和结构,而且在操作中变化的参数也能得到很好的补偿．这种算法还有一个 突出的优点就是,神经元补偿器作为前馈控制回路中的一个独立部分,使得整个控制系统能 够实现多速率采样控制结构．     

Dual closed‐loop tracking control for wheeled mobile robots via active disturbance rejection control and model predictive control

A dual closed‐loop tracking control is proposed for a wheeled mobile robot based on active disturbance rejection control (ADRC) and model predictive control (MPC). In the inner loop system, the ADRC scheme with an extended state observer (ESO) is proposed to estimate and compensate external disturbances. In the outer loop system, the MPC strategy is developed to generate a desired velocity for the inner loop dynamic system subject to a diamond‐shaped input constraint. Both effectiveness and stability analysis are given for the ESO and the dual closed‐loop system, respectively. Simulation results demonstrate the performances of the proposed control scheme.     

双闭环策略下非完整轮式机器人鲁棒自适应运动/力协调控制

非完整轮式移动机器人的路径跟踪,需要在保证机器人姿态跟踪精度的同时,增强其地面适应性能.为实现这种运动/力的协调控制目标,本文提出双闭环的控制系统结构:外环能够增加运动精度,内环则可以增强机器人对地面动态摩阻的适应性.同时,考虑到地面摩阻的慢时变性,本文通过构造观测器对其进行估计.在具体算法实现方面,采用反步法在外环构建运动控制器:而在内环,则是应用积分型的滑模技术设计力控制器与观测器.最后,对控制系统进行仿真,仿真结果证明所提出控制方法的有效性.     

Adaptive synchronization control of networked robot systems without velocity measurements

This paper addresses the adaptive synchronization control problem of networked robot systems characterized by the Lagrangian function, where exact dynamic models are unknown and velocity measurements are unavailable. A class of distributed observers, comprised of multiple dynamic variables and static variables, are established based on no a priori restriction on the boundness of the observer states. The observer is compatible for different control schemes with or without structure uncertainties. Using the estimated states given by the observer, adaptive distributed control input is developed, and then, closed‐loop dynamic models for filtered vectors are established. It is proven that our proposed control scheme permits global exact state estimation and global asymptotic synchronization while compensating for structure uncertainties. Simulations are provided to demonstrate the effectiveness of the results.     

基于滑模位置控制的机器人灵巧手模糊自适应阻抗控制

提出一种基于滑模位置控制的模糊自适应阻抗控制策略。该控制方案通过模糊控制器实时地调整阻抗参数,不但可使系统稳定,而且具有良好的动态品质;同时内环的滑模位置控制器可增强系统的鲁棒性,最后以机器人灵巧手单关节为对象进行仿真研究,证明了该控制策略的有效性和可行性。     

Dynamics and Noncollocated Model‐Free Position Control for a Space Robot with Multi‐Link Flexible Manipulators

In this paper, both the dynamics and noncollocated model‐free position control (NMPC) for a space robot with multi‐link flexible manipulators are developed. Using assumed modes approach to describe the flexible deformation, the dynamic model of the flexible space robotic system is derived with Lagrangian method to represent the system dynamic behaviors. Based on Lyapunov's direct method, the robust model‐free position control with noncollocated feedback is designed for position regulation of the space robot and vibration suppression of the flexible manipulators. The closed‐loop stability of the space robotic system can be guaranteed and the guideline of choosing noncollocated feedback is analyzed. The proposed control is easily implementable for flexible space robot with both uncertain complicated dynamic model and unknown system parameters, and all the control signals can be measured by sensors directly or obtained by a backward difference algorithm. Numerical simulations on a two‐link flexible space robot are provided to demonstrate the effectiveness of the proposed control.     

Contribution to the indirect decentralized adaptive control of manipulation robots

In this paper, efficient approaches to the synthesis of indirect decentralized adaptive control for manipulation robots are presented. The first part of control synthesis consists of the estimation of unknown dynamic robot parameters using the methods of recursive identification and fast dynamic as well as identification models in a symbolic form. The second part of synthesis includes the self-tuning control strategy which is a basis for adaptive control synthesis according to the estimates of the unknown dynamic parameters. Using the theory of decentralized systems, a new robust algorithm for adaptive control with the ability of adaptation in the feedforward or feedback loop are proposed. A complete stability and convergence analysis is presented. A special part of the paper represents an analysis of practical implementation of the proposed control algorithms on modern microprocessor-based robot controllers. Based on this analysis, an efficient application of indirect adaptive algorithms in real time with high-quality system performance is shown. Adaptive algorithms are verified through simulation of trajectory tracking for an industrial robot with unknown dynamic parameters of payload.     

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.     

Adaptive variable structure controller of redundant robots with mobile/fixed obstacles avoidance

In this paper, a variable structure adaptive controller is proposed for redundant robot manipulators constrained by moving obstacles. The main objective of the controller is to force the model states of the robot to track those of a chosen reference model. In addition, the controller is designed directly in Cartesian space and no knowledge on the dynamic model is needed, except its structure. The parameters of the controller are adapted using adaptive laws obtained via Lyapunov stability analysis of the closed loop. The performances of the proposed controller are evaluated using a 3 DOF robot manipulator evolving in a vertical plane constrained by a mobile obstacle. The obtained results show its effectiveness compared to other tested variable structure controllers.