四足步行机器人模糊神经网络控制

本文以模糊控制与神经网络应用于四足步行机器人的力与位置混合控制系统为目的，针对ＪＴＵＷＭ－ＩＩ四足步行机器人，进行了有关神经网络、模糊控制的理论研究和实验     

二足步行机器人的新型脚力传感器的研究

本文论述了二足步行机器人使用的新型脚力传感器。该脚力传感器能够较精确地测出二足步行机器人脚上所受的垂直负荷。利用该脚力传感器的输出能够较准确地计算出二足步行机器人的重心位置，对于步行的控制具有重要意义。     

四足机器人动态步行仿真及步行稳定性分析

为了研究影响四足机器人动态稳定步行的因素,使用ADAMS虚拟样机软件对四足步行机器人动态步行进行运动仿真。文中详细叙述了从机器人的运动轨迹规划、将MATLAB计算数据输入ADAMS,到由ADAMS施加力和约束、建立步行机器人虚拟样机的具体方法和步骤。从理沦及仿真结果两方面对影响机器人稳定步行的因素进行了较全面的分析和验证,如步长、步行周期、起步等。通过虚拟样机实验弥补了由于客观条件限制无法在物理样机上进行的部分实验内容,发现了机器人起步方式对步行稳定性具有明显影响并进行了分析。研究结果及所用的MATLAB-ADAMS联合仿真方法对四足步行机器人的设计研究以及仿真实验工作都具有指导意义。     

仿人步行二足机器人的研制

本文介绍一种关节采用滑块－摆杆机构的仿人步行二足机器人。该机器人具有１２个自由度，动力源为１２个伺服电机，每个伺服电机都配有相应的轴角编码器。机器人的脚上装有力传感器，身体上装有电子陀螺。机器人的步行由计算机控制。     

四足机器人斜面静态步行的稳定性分析

本研究对四足机器人在斜面静态步行的稳定性问题进行分析.针对机器人在斜面步行中存在绕支撑脚连线翻转的现象,采用Sne工具分析稳定性,并提出了通过降低机器人重心高度来提高四足机器人在斜面静态步行时的稳定性的方法.通过仿真实验验证了该方法的可行性.     

步行机器人的递阶分布式计算机控制系统研究

本文描述了一种四足步行机器人的递阶、分布式实时计算机控制系统,介绍了该系统的结构及实现方案,讨论了关节位置的开关控制问题及步行机器人的总体控制问题.最后论述了步行实验结果.     

二足步行机器人三维动步行的双脚支撑期的理论解析及仿真

本文以１０自由度二足步行机器人三维动步行的实现为目的，根据动力矩和静力矩的概念，运用Ｓ和Ｆ非分离的三维力学分析方法，对于双脚支持期的二足步行运动，进行了理论解析和步行仿真，证明了该方法的有效性。     

基于形状记忆合金的四足步行机器人

利用形状记忆合金（Shape Memory Alloys,简称SMA）作为驱动元件，设计制作四足步行机器人，其动作靠电流的通，断来控制，本文介绍了这种机器人的具体的设计和制作方案，包括该机器人的运动原理，设计要点，结构组成和控制方式，并且对样机的相关参数作了评价。     

四足机器人静步态直线行走规划研究

为使四足机器人以静态步行方式实现稳定直线行走.基于仿生学,利用SolidWorks环境下所构建的虚拟模趔,使用三角函数法对机器人的步行参数进行了规划和设计,并在ADAMS中对所规划的步行方式进行了仿真和检验.进而针对仿真中机器人出现横向偏移的现象,对影响机器人稳定直线行走的原因进行了分析,提出了支撑足零差速规划方法,并在进一步的仿真中证明了方法能有效减小横向偏移量,实现机器人的稳定直线行走.研究结果以及所用的仿真方法对四足机器人的步态设计具有一定的借鉴意义.     

四足机器人对角小跑起步姿态对稳定步行的影响

对四足机器人对角小跑步态下绕支撑对角线的翻转力矩建立了力学模型，分析了该力矩对机器人运动姿态及稳定步行的不利影响，并提出了利用起步姿态来削弱翻转力矩不利影响的方法——三分法．     

Demonstration and Analysis of Quadrupedal Passive Dynamic Walking

Animals, including human beings, can travel in a variety of environments adaptively. Legged locomotion makes this possible. However, legged locomotion is temporarily unstable and finding out the principle of walking is an important matter for optimum locomotion strategy or engineering applications. As one of the challenges, passive dynamic walking has been studied on this. Passive dynamic walking is a walking phenomenon in which a biped walking robot with no actuator walks down a gentle slope. The gait is very smooth (like a human) and much research has been conducted on this. Passive dynamic walking is mainly about bipedalism. Considering that there are more quadruped animals than bipeds and a four-legged robot is easier to control than a two-legged robot, quadrupedal passive dynamic walking must exist. Based on the above, we studied saggital plane quadrupedal passive dynamic walking simulation. However, it was not enough to attribute the result to the existence of quadrupedal passive dynamic walking. In this research, quadrupedal passive dynamic walking is experimentally demonstrated by the four-legged walking robot 'Quartet 4'. Furthermore, changing the type of body joint, slope angle, leg length and variety of gaits (characteristics in four-legged animals) was observed passively. Experimental data could not have enough walking time and could not change parameters continuously. Then, each gait was analyzed quantitatively by the experiment and three-dimensional simulation.     

Design of a proposed neural network control system for trajectory controlling of walking robots

The use of a proposed recurrent hybrid neural network to control of walking robot with four legs is investigated in this paper. A neural networks based control system is utilized to the control of four-legged walking robot. The control system consists of four proposed neural controllers, four standard PD controllers and four-legged planar walking robot. The proposed neural network (NN) is employed as an inverse controller of the robot. The NN has three layers, which are input, hybrid hidden and output layers. In addition to feedforward connections from the input layer to the hidden layer and from the hidden layer to the output layer, there is also feedback connection from the output layer to the hidden layer and from the hidden layer to itself. The reason to use hybrid layer is that robot’s dynamics consists of linear and non-linear parts. The results show that the proposed neural control system has superior performance to control trajectory of walking robot with payload.     

仿蟹机器人步态分析与仿真

在仿蟹机器人的行走控制中,步态的选择对机器人的稳定快速行走具有至关重要的作用。本文对仿蟹八足机器人的基本步态进行了分类,并进一步对八足波形步态进行分析,得出八足步行机器人在采用双四足步态的行走方式时,既可以满足速度的要求,又可以保证机器人的稳定性。通过计算机软件ADAMS对所选步态进行全局仿真,结果验证了步态规划的合理性,同时得到了机器人相关物理量的变化曲线,为进一步选择电机,分析机器人系统的动态特性提供了依据。     

Neuromorphic walking gait control

We present a neuromorphic pattern generator for controlling the walking gaits of four-legged robots which is inspired by central pattern generators found in the nervous system and which is implemented as a very large scale integrated (VLSI) chip. The chip contains oscillator circuits that mimic the output of motor neurons in a strongly simplified way. We show that four coupled oscillators can produce rhythmic patterns with phase relationships that are appropriate to generate all four-legged animal walking gaits. These phase relationships together with frequency and duty cycle of the oscillators determine the walking behavior of a robot driven by the chip, and they depend on a small set of stationary bias voltages. We give analytic expressions for these dependencies. This chip reduces the complex, dynamic inter-leg control problem associated with walking gait generation to the problem of setting a few stationary parameters. It provides a compact and low power solution for walking gait control in robots.     

Four-legged intelligent mobile autonomous robot

This paper presents the design and development of a four-legged mobile robot with intelligent sensing and decision-making capabilities. Multiple sensors with embedded knowledge bases and learning capabilities are used in a novel approach towards environmental perception and reaction. These sensors continuously monitor the environment as well as their own operating parameters. Priority is given to any one or a group of sensors based on prevailing environmental conditions. Intelligent sensing is shown to be the key towards a high degree of autonomy for a mobile robot. Nicknamed Flimar, this robot has the ability to function at varying degrees of intelligence made possible by an object-oriented architecture with embedded intelligence at various levels. This architecture is shown to be conducive towards incremental learning. Each of the four legs has three degrees of freedom, i.e. Flimar has a total of 12 motors on its four legs. Flimar can walk and turn without dragging or skidding, and also turns about its center of gravity with a zero radius. Flimar responds to light, sound and touch in different ways, based on prevailing environmental conditions. The overall goal of the paper is to present a novel walking principle and control architecture for a walking robot.     

适用多种环境的救灾勘探四足仿生机器狗

随着自然灾害的频发,救援人员的伤亡人数也在增加,机器人代替人完成救援工作成为研究热点。根据对国际相关领域研究成果的分析,设计了一款稳定性高,环境适应能力强的仿生四足机器狗。全身支架采用铝合金打造,腿部采用碳纤维打造,搭配大扭矩电机,结合六自由度机械臂,实现不同地形环境下的前进方式转换。基于前肘后膝式的腿型设计并结合ADAMS仿真,实现稳定行走。结合气体检测和图像识别模块,实现救灾现场的环境勘探和搜救任务。基于稳定裕度最优化的原则,采用对角步态的行走步态控制方式。公布了8自由度前肘后膝X腿型式四足机器狗机械设计及其步态控制方案。     

4足步行机器人斜坡运动的研究

在4足步行机的运动环境中,上下坡是一种基本的典型环境.本文研究了缩放式4足步行机在上下坡环境中运动的一些基本规律,得出了上下坡时4足步行机在不同坡度下的最大步长,最佳机体高度.对4足步行机上下坡时能保持稳定运动的边界环境条件也进行了研究.     

基于中枢模式发生器的仿生机器狗步态控制的应用研究

由于人工规划产生的步态是比较僵硬的、缓慢的,缺乏灵活的自组织能力,与真正的动物步态存在很大差别;文章提出了机器狗生物步态的概念;以生物的中枢模式发生器CPG模型为核心建立仿生四足机器狗运动控制系统;根据哺乳动物的肢体运动关系,建立机器狗膝髋关节运动关系方程,并设计系统软硬件;设计的控制器能够有效地克服机器狗关节轨迹跟踪控制中耦合、力矩非线性等因素的影响,且具有自适应能力;通过仿真验证了应用于机器狗的生物CPG控制机理的控制方法是有效的。     

欠驱动两足步行机器人研究现状

针对欠驱动两足步行机器人的研究现状与发展趋势进行了探讨。首先,总结了被动行走和踝关节欠驱动两足机器人的研究现状,介绍了欠驱动两足步行机器人的基本研究方法,包括问题描述、步态规划、运动控制和稳定性判定等,并对欠驱动两足机器人需要进一步研究的问题和发展方向进行深入研究,最终目标是将欠驱动控制策略应用于两足步行机器人的行走过程控制,以提高其运动性能。