基于ARM9的嵌入式仿人机器人控制系统设计

依据DF-1仿人机器人需要实现的功能,提出了基于ARM9的嵌入式仿人机器人控制系统方案。设计了控制系统的硬件电路,整个系统软件采用模块化设计思想,简化了设计程序,提高了系统的可靠性。     

基于虚拟位姿迟钝搜索的仿人机器人手臂抓取控制系统的设计

为了使仿人机器人手臂抓取控制系统更加智能化,提高运行效率,设计并实现了一种基于虚拟位姿迟钝搜索的仿人机器人手臂抓取控制系统。系统采用PMAC运动控制器完成机器人运行数据的传递、处理以及对机器人手臂抓取工作台的控制,采用Accelus系列数字伺服驱动器,调控仿人机器人运动位置和速度,通过关节控制器对机器人抓取过程中手臂关节的位置、速度以及角度信息进行控制,通过以S3C2440为核心芯片的上位机,实现仿人机器人手臂控制的远程通信以及抓取任务的调度,完成仿人机器人手臂抓取的智能控制,软件设计过程中,对基于虚拟位姿迟钝搜索的仿人机器人手臂抓取控制算法进行了详细分析,并给出了机器人手臂抓取控制程序代码实例,通过仿真实例验证了本系统的可用性和实用性。     

基于一级倒立摆模型仿人机器人控制算法研究

针对仿人机器人步态行走不稳定的问题,以倒立摆为控制对象,建立仿人机器人步态行走数学模型。以仿人机器人姿态角和位移建立双闭环控制系统,采用PID控制算法对仿人机器人姿态角和位移进行调节。以19自由度仿人机器人进行实验验证,表明了所采用仿人机器人步态行走系统PID控制算法的正确性及高精确度。系统响应稳定,超调<0.3%,调节时间<0.2 s,关节输出相对误差最大值为2.25%,可实现仿人机器人稳定的步态行走。     

基于CAN总线和DSP的仿人机器人运动控制系统研究

从全新的角度对仿人型机器人运动控制系统进行了尝试和探索，提出了一种以DSP为核心、CAN总线为通信标准的新型控制结构，并分情况给出了三种不同的设计方案。整个控制系统集成在机器人本体上，结构灵活，工作稳定可靠，经实践证明，十分适合仿人机器人的控制。     

CAN总线在仿人机器人运动控制系统中的应用

文章先对CAN总线进行了介绍，然后把CAN总线应用到仿人机器人中，设计出一种适合仿人机器人的分布式运动控制系统，并给出了详细的设计过程。整个控制系统层次清晰，结构灵活，对仿人机器人的进一步发展具有积极的作用，同时为现场总线在仿人机器人中的应用提供了重要的参考。     

小型仿人机器人控制系统设计

本文提出了一种以ARM9为主控制器的新型的仿人机器人分布式控制系统。单片机和外部计数器组成关节控制器。主控制器和关节控制器之间采用USB通信。从而实现了控制系统的小型化和低功耗。通过该系统控制小型仿人机器人完成了行走实验。     

STM32的小型仿人机器人控制系统设计

仿人机器人是一种集机械、电子、控制、通信、计算机等多种技术于一体的智能系统,而控制技术是它的核心.本文设计了一款基于STM32F103芯片的小型仿人机器人控制系统.该控制系统通过输出10路PWM波实现机器人的关节运动控制,通过红外测距传感器实现机器人避障,通过姿态传感器MPU6050实现机器人的姿态测量.经过试验验证,在该系统的控制下,10自由度小型仿人机器人能够稳定行走并完成各种预期动作,且能够实现自主避障功能.     

仿人型机器人动态步行控制方法

本文介绍了仿人型机器人动态步行的一些基本问题和相关概念．从信息和控制的 角度对近年来仿人型机器人动态步行研究中出现的步态规划和姿态控制方法进行了分析,并 指出了它们的特点．提出了先进仿人型机器人实现过程中值得进一步研究的问题．     

仿人机器人的分布式控制系统设计

针对仿人机器人系统自由度多,实时性与可靠性要求高的特点,设计了基于CAN总线的具有Windows与RT-Linux系统的双主机的主控层结构的分布式控制系统,整个控制系统采用集中管理分散控制的方式,按照控制系统的结构和功能划分为主控层、通信层、协调执行层3层。CAN总线与一般通信总线相比,它的数据通信具有较强的实时性,并且CAN总线连线简单,降低了系统连线的复杂程度,增强了系统的可靠性。其中基于Windows的控制系统负责仿人机器人关节电机的调试以及传感数据的显示;基于RT-Linux的系统实现机器人的实时运动控制。实验表明提出的分布式控制系统操作简便、安全可靠、实时性强,能充分满足仿人机器人系统调试与运动控制的要求。     

从两足机器人到仿人型机器人的研究历史及其问题

本文介绍了从两足机器人发展到仿人型机器人的历 史,分析了在自由度、能量最优和碰撞研究的一些研究现状和前景,并对仿人型机器人与两 足机器人在运动特性上有所不同提出了一些问题．     

Statistical Learning for Humanoid Robots

The complexity of the kinematic and dynamic structure of humanoid robots make conventional analytical approaches to control increasingly unsuitable for such systems. Learning techniques offer a possible way to aid controller design if insufficient analytical knowledge is available, and learning approaches seem mandatory when humanoid systems are supposed to become completely autonomous. While recent research in neural networks and statistical learning has focused mostly on learning from finite data sets without stringent constraints on computational efficiency, learning for humanoid robots requires a different setting, characterized by the need for real-time learning performance from an essentially infinite stream of incrementally arriving data. This paper demonstrates how even high-dimensional learning problems of this kind can successfully be dealt with by techniques from nonparametric regression and locally weighted learning. As an example, we describe the application of one of the most advanced of such algorithms, Locally Weighted Projection Regression (LWPR), to the on-line learning of three problems in humanoid motor control: the learning of inverse dynamics models for model-based control, the learning of inverse kinematics of redundant manipulators, and the learning of oculomotor reflexes. All these examples demonstrate fast, i.e., within seconds or minutes, learning convergence with highly accurate final peformance. We conclude that real-time learning for complex motor system like humanoid robots is possible with appropriately tailored algorithms, such that increasingly autonomous robots with massive learning abilities should be achievable in the near future.     

不同个性的情感机器人表情研究

在情感机器人研究中,不同个性的面部表情是情感机器人增强真实感的重要基础。为实现情感机器人更加丰富细腻的表情,将人类的个性特征引入情感机器人,分析个性理论和情感模型理论,得知不同个性机器人的情感强度。结合面部动作编码系统中面部表情与机器人控制点之间的映射关系,得到情感机器人不同个性的基本表情实现方法。利用Solidworks建立情感机器人脸部模型,在ANSYS工程软件中将SHFR-Ⅲ情感机器人脸部模型设置为弹性体,通过有限元仿真计算方法,对表情的有限元仿真方法进行了探究,得到实现SHFR-Ⅲ不同个性基本表情的控制区域载荷大小和仿真结果。最后,根据仿真结果,进行SHFR-Ⅲ情感机器人不同个性的表情动作实验。实验结果表明,有限元表情仿真可以指导SHFR-Ⅲ情感机器人实现近似人类的不同个性的基本面部表情。     

面向仿人机器人自然步态规划的人体步行实验分析

自然步态规划方法是实现仿人机器人步态柔顺和能量优化的可行方法,该方法要求对人体步行及其平衡策略进行定量研究．本文分析自然步态规划方法的原理,建立了一套快捷有效的人体步态测试系统,并通过实验建立了人体步行的参数化数据库．实验结果揭示了人体步行的参数化特征及其平衡策略,对于仿人机器人的自然步态规划及控制提供了理论指导．结论特别指出,仅仅通过规划的方式实现仿人机器人的自然步态是不完备的,自然步态的实现必须同仿生控制策略相结合．同时实验结论对于仿人机器人的本体优化设计也提供了参考．     

仿人跑步机器人稳定性与控制策略研究进展

针对仿人跑步机器人稳定性和控制策略的研究现状与发展趋势进行了探讨.首先.分析了仿人跑步模型的固有特性,包括单边约束特性、系统混杂特性和变拓扑结构特性,介绍了基于ZMP(Zero Moment Point)和零化角动量的稳定性判据以及基于庞加莱映射和极限环的稳定性判据,总结了基于轨迹规划的时变控制策略和基于虚拟约束的定常...     

Whole-Body Motion Generation Integrating Operator's Intention and Robot's Autonomy in Controlling Humanoid Robots

This paper introduces a framework for whole-body motion generation integrating operator's control and robot's autonomous functions during online control of humanoid robots. Humanoid robots are biped machines that usually possess multiple degrees of freedom (DOF). The complexity of their structure and the difficulty in maintaining postural stability make the whole-body control of humanoid robots fundamentally different from fixed-base manipulators. Getting hints from human conscious and subconscious motion generations, the authors propose a method of generating whole-body motions that integrates the operator's command input and the robot's autonomous functions. Instead of giving commands to all the joints all the time, the operator selects only the necessary points of the humanoid robot's body for manipulation. This paper first explains the concept of the system and the framework for integrating operator's command and autonomous functions in whole-body motion generation. Using the framework, autonomous functions were constructed for maintaining postural stability constraint while satisfying the desired trajectory of operation points, including the feet, while interacting with the environment. Finally, this paper reports on the implementation of the proposed method to teleoperate two 30-DOF humanoid robots, HRP-1S and HRP-2, by using only two 3-DOF joysticks. Experiments teleoperating the two robots are reported to verify the effectiveness of the proposed method.     

Survey of Intelligent Control Techniques for Humanoid Robots

This paper focusses on the application of intelligent control techniques (neural networks, fuzzy logic and genetic algorithms) and their hybrid forms (neuro-fuzzy networks, neuro-genetic and fuzzy-genetic algorithms) in the area of humanoid robotic systems. It represents an attempt to cover the basic principles and concepts of intelligent control in humanoid robotics, with an outline of a number of recent algorithms used in advanced control of humanoid robots. Overall, this survey covers a broad selection of examples that will serve to demonstrate the advantages and disadvantages of the application of intelligent control techniques.     

仿人跑步机器人机构与步态规划综述

阐述了仿人跑步机器人研究的必要性,介绍了几款国外典型的仿人机器人机构设计和驱动系统设计,对仿人跑步机器人的步态规划问题进行了综述,并指出仿人跑步机器人领域的研究难点和未来研究方向。     

A closed-loop approach for tracking a humanoid robot using particle filtering and depth data

Humanoid robots introduce instabilities during biped march that complicate the process of estimating their position and orientation along time. Tracking humanoid robots may be useful not only in typical applications such as navigation, but in tasks that require benchmarking the multiple processes that involve registering measures about the performance of the humanoid during walking. Small robots represent an additional challenge due to their size and mechanic limitations which may generate unstable swinging while walking. This paper presents a strategy for the active localization of a humanoid robot in environments that are monitored by external devices. The problem is faced using a particle filter method over depth images captured by an RGB-D sensor in order to effectively track the position and orientation of the robot during its march. The tracking stage is coupled with a locomotion system controlling the stepping of the robot toward a given oriented target. We present an integral communication framework between the tracking and the locomotion control of the robot based on the robot operating system, which is capable of achieving real-time locomotion tasks using a NAO humanoid robot.     

Symmetry position/force hybrid control for cooperative object transportation using multiple humanoid robots

A symmetry position/force hybrid control framework for cooperative object transportation tasks with multiple humanoid robots is proposed in this paper. In a leader-follower type cooperation, follower robots plan their biped gaits based on the forces generated at their hands after a leader robot moves. Therefore, if the leader robot moves fast (rapidly pulls or pushes the carried object), some of the follower humanoid robots may lose their balance and fall down. The symmetry type cooperation discussed in this paper solves this problem because it enables all humanoid robots to move synchronously. The proposed framework is verified by dynamic simulations.