A Real-Time Kinematics on the Translational Crawl Motion of a Quadruped Robot

It is known that the kinematics of a quadruped robot is complex due to its topology and the redundant actuation in the robot. However, it is fundamental to compute the inverse and direct kinematics for the sophisticated control of the robot in real-time. In this paper, the translational crawl gait of a quadruped robot is introduced and the approach to find the solution of the kinematics for such a crawl motion is proposed. Since the resulting kinematics is simplified, the formulation can be used for the real-time control of the robot. The results of simulation and experiment shows that the present method is feasible and efficient.     

四足步行机器人爬行步态的计算机仿真

由于机器人数学描述的复杂性,使得在机器人运动学、动力学分析方面显得较为困难,计算机虚拟仿真技术在该领域的应用为机器人的运动特性分析提供了依据.文中建立了一个连续转动式腿机构的四足步行机器人模型,并规划了该机器人的一种直线爬行步态,利用ADAMS虚拟样机软件对机器人的爬行步态进行了动力学仿真,得到了机器人各个关节相关物理量的变化曲线,分析了四个髋关节的驱动力矩在步行过程中的变化情况.通过仿真,验证了步态规划的合理性,同时为进一步选择电机、分析机器人系统的动态特性提供了依据.     

Steady Crawl Gait Generation Algorithm for Quadruped Robots

The capability of stable walking on irregular terrain is the primary advantage of legged robots over wheeled mobile robots. However, the traditional foothold selection-based gait generation algorithms are not suitable at some points for blind robots which cannot obtain the exact terrain information. A velocity-based gait generation algorithm with real-time adaptation rules which are necessary for steady walking is suggested. Particularly, we have developed a steady crawl gait with duty factor β = 0.75. The main feature of the suggested algorithm is that it is not based on foothold selection and it can be used for the walking of blind robots on more realistic irregular terrain. The adaptation rules are the translational velocity modification to satisfy the steady gait requirement and the swing period modification to avoid the kinematic limitation. The suggested gait generation algorithm has been implemented in a simple quadruped robot that has a total of eight actuated joints on the legs. Using PD controllers for each actuated joint for the trajectory following and the adaptation algorithm of gait parameters, the steady periodic crawl gait on irregular terrain has been demonstrated.     

Gait Adaptation in a Quadruped Robot

A newborn foal can learn to walk soon after birth through a process of rapid adaptation acting on its locomotor controller. It is proposed here that this kind of adaptation can be modeled as a distributed system of adaptive modules (AMs) acting on a distributed system of adaptive oscillators called Adaptive Ring Rules (ARRs), augmented with appropriate and simple reflexes. It is shown that such a system can self-program through interaction with the environment. The adaptation emerges spontaneously as several discrete stages: Body twisting, short quick steps, and finally longer, coordinated stepping.This approach is demonstrated on a quadrupedal robot. The result is that the system can learn to walk several minutes after inception.     

"现代木牛流马"的智能控制

机器人是科学技术发展到一定历史阶段的产物。作为机器人的核心部分,机器人控制技术经历了经典控制技术、现代控制技术和智能控制技术的发展过程。本文通过对具有15个自由度的＂现代木牛流马＂四足步行机器人的研究,开发了一个由上位机和PLC组建的两级控制系统对其进行智能控制,完成了在复杂道路情况下的自适应行走,并结合实例做了具体介绍,经展品试验证明了其可行性,并获得了很好的效果。     

Iterative Path Tracking of an Omni-Directional Mobile Robot

We propose a path-tracking algorithm that is developed using an iterative learning control (ILC) technique and use the algorithm to control an omni-directional mobile robot. The proposed algorithm can be categorized as an open–closed PD-type ILC; it generates robot velocity commands by a PD-type ILC update rule using both previous and current information. When applied to the omni-directional mobile robot, it can decrease position errors and track the desired trajectory. Under the general problem setting that includes a mobile robot, we show that the proposed algorithm guarantees that the system states, outputs and control inputs converge to within small error bounds around the desired ones even under state disturbances, measurement noises and initial state errors. By using simulation and experimental tests, we demonstrate that the proposed algorithm converges fast to the desired path, and results in small root-mean-square (r.m.s.) position error under various surface conditions. The proposed algorithm shows better path-tracking performance than the conventional PID algorithm and achieves faster convergence and lower r.m.s. error than the existing two ILC algorithms.     

A Fuzzy-Logic-Based Approach for Mobile Robot Path Tracking

One important problem in autonomous robot navigation is the effective following of an unknown path traced in the environment in compliance with the kinematic limits of the vehicle, i.e., bounded linear and angular velocities and accelerations. In this case, the motion planning must be implemented in real-time and must be robust with respect to the geometric characteristics of the unknown path, namely curvature and sharpness. To achieve good tracking capability, this paper proposes a path following approach based on a fuzzy-logic set of rules which emulates the human driving behavior. The input to the fuzzy system is represented by approximate information concerning the next bend ahead the vehicle; the corresponding output is the cruise velocity that the vehicle needs to attain in order to safely drive on the path. To validate the proposed algorithm two completely different experiments have been run: in the first experiment, the vehicle has to perform a lane-following task acquiring lane information in real-time using an onboard camera; in the second, the motion of the vehicle is obtained assigning in real-time a given time law. The obtained results show the effectiveness of the proposed method     

水冷壁爬壁机器人路径跟踪研究

摘要：准确的直线运动是水冷壁爬壁机器人完成磨损检测工作的前提,为了保证其做直线运动,设计了一种水冷壁爬壁机器人路径跟踪控制律。本文通过建立爬壁机器人的运动学模型,用摄像机采集水冷壁图像,对图像处理并提取直线路径,实现对其位姿的反馈,再根据Backstepping跟踪算法设计路径跟踪控制律对机器人位姿进行控制,同时采用Lyapunov稳定理论对控制律的收敛性进行验证,最后通过MATLAB软件进行仿真实验,仿真结果验证了控制律的有效性。     

室内机器人及其路径跟踪网络设计

近年来,室内移动机器人的研究和设计成为关注的焦点。我们采用单片机作为机器人的核心控制器,利用超声波传感器、碰撞传感器、步进电机及其控制芯片Ta8435联合制作开发了机器人实验平台。最后介绍了模糊控制、模糊神经网络,并利用模糊控制和模糊神经网络技术对室内机器人导航中的模糊控制避障和模糊神经网络路径跟踪作了MATLAB仿真研究,达到了预期的目的。     

基于移动机器人的路径跟踪方法研究

研究光电传感器工作原理、控制电路及信号接口连接,合理设计并制作传感电路板,使移动机器人能够顺延在场地中布置的白色轨迹纸带行走,并保证其行走时避免脱轨的现象。     

飞机牵引机器人路径跟踪模糊控制

为了提高飞机地面自动导航路径跟踪的控制精度,提出了基于模糊自适应控制的智能飞机牵引机器人纯追踪路径跟踪方法。首先建立了牵引机器人-飞机两轮简化模型,进行了路径跟踪运动分析;基于此分析,以牵引机器人-飞机系统运动速度和轨迹误差为输入,以预测距离为输出,通过模糊自适应控制实时调整纯追踪算法预测距离,设计了基于自适应模糊控制的路径跟踪控制器;通过几何仿真和虚拟样机仿真两种方法分别对所提出的方法进行了验证。结果表明,牵引机器人-飞机系统在变速运动时,路径跟踪的轨迹误差能控制在0.5 m左右,完全满足飞机地面自动牵引滑行的精度要求,验证了所提方法的有效性和适应性。     

Development of an Autonomous Quadruped Robot for Robot Entertainment

In this paper, we present Robot Entertainment as a new field of the entertainment industry using autonomous robots. For feasibility studies of Robot Entertainment, we have developed an autonomous quadruped robot, named MUTANT, as a pet-type robot. It has four legs, each of which has three degree-of-freedom, and a head which also has three degree-of-freedom. Micro camera, stereo microphone, touch sensors, and other sensor systems are coupled with newly developed behavior generation system, which has emotion module as its major components, and generates high complex and interactive behaviors. Agent architecture, real-world recognition technologies, software component technology, and some dedicated devices such as Micro Camera Unit, were developed and tested for this purpose. From the lessons learned from the development of MUTANT, we refined the design concept of MUTANT to derive requirements for a general architecture and a set of interfaces of robot systems for entertainment applications. Through these feasibility studies, we consider entertainment applications a significant target at this moment from both scientific and engineering points of view.     

四腿机器人步态控制与仿真研究

本文分析了四腿机器人行走步态,依据现有机器人部件设计了行走控制程序,其中采用腿部摆转,起落分时控制方法,实现了机器人前进、后退、转向等典型动作,机器人最后经ADAMS进行机构运动仿真,仿真结果准确,可用于指导该机器人的结构优化与程序开发.     

On the Design and Development of a Quadruped Robot Platform

In this paper, we describe the development of a quadruped robot named HuboDog. The objective of this project is to develop a reliable and robust quadruped robot platform that enables the implementation of stable and fast static/dynamic walking on even or uneven terrain, and walking while carrying a payload. A lightweight but highly rigid platform is achieved via a frame-type structure and double-supported beam-type joint design. A small, light but high output power joint actuator is designed with a harmonic reduction gear and electric motor that has high speed and a high output power. A distributed control system is used since it can reduce the computational burden of the main computer and easily extend the electrical components. Microprocessor-based subcontrollers are developed for motor control and sensor signal feedback. The main computer, which is mounted on the trunk, communicates with the subcontroller via the CAN (Controller Area Network) protocol. We used Windows XP as the operating system and have established a real-time control system in Windows XP by using RTX (Real Time eXtension) software. This paper includes design concepts, mechanical system design, system integration and electrical system design. In order to demonstrate the performance of the robot platform, simple experiments were performed.     

Indoor Mobile Robot Local Path Planner with Trajectory Tracking

This paper deals with the design and implementation of an indoor mobile robot local path planner. This latter is based essentially on an ultrasonic perception system, where the covered region of sight is widened and the apparent distance between any two adjacent sensors can be adjusted. So, good resolution can be obtained and laterally positioned obstacles with respect to the robot line of sight are well identified. Furthermore, we propose a technique to improve the odometric method, to reduce the systematic errors and to detect floor irregularities. Following a predefined trajectory is provided by the control of the trailing wheel deviation angle.     

动态环境下移动机器人路径跟踪与避障

采用模糊神经网络并结合模糊逻辑控制的方法,研究在动态环境下移动机器人的在线路径跟踪与实时避障问题:针对移动机器人的运动学模型,依据点与直线间的距离关系设计了移动机器人的路径跟踪算法,提出了一种基于模糊神经网络的移动机器人在线路径跟踪方案,采用改进的BP算法对网络进行学习与训练,利用梯度下降法调整网络的权值与阈值,使其实际输出与期望输出的误差总均方差最小.同时,运用模糊逻辑控制,实现了移动机器人的实时避障.仿真实例证实了控制方案的有效性,表明了所提出的跟踪算法与控制方案具有良好的动态路径跟踪与实时避障能力.