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。     

七连杆双足机器人建模和控制系统仿真

研究双足机器人稳定性控制问题,步行机器人作为一种载运工具适应地况能力强,结构复杂,运动控制难.实现类人型机器人动态行走,针对行走的稳定性,必须对机器人进行动力学建模、步态设计和稳定姿态控制算法设计.研究了一种七连杆双足机器人的动力学建模和控制系统仿真方法.建立两足步行机器人腿的可参数化仿真模型,对七平面双足机器人的运动情况和控制输入输出进行仿真,得出试验结果.并对影响步行机器人稳定性能的参数进行分析,为后面机器人样机的研制提供理论及数据依据.     

基于Bezier曲线的机器人路径规划

本文将机器人路径规划与跟踪控制问题合并在一起,研究机器人运动控制中基于Bezier曲线的路径规划算法,介绍该曲线的基本特点、优良特性以及两条曲线的拼接,并提出控制算法和路径规划的方法,简要分析控制精度。     

舵机控制步行机器人系统设计

首先设计了两足步行机器人的本体结构,并选择舵机作为驱动源。然后,基于广义坐标对该机器人进行了运动学建模,该方法运算简便、直观易懂。重点讨论了动态步行的算法设计,详细分析了基于零力矩点的仿人机器人动态步行运动规划方法。结合机器人的几何约束和运动约束,推导机器人参数化步态设计的推导公式,机器人步态的参数化设计大大方便了机器人的运动学和动力学分析。最后,介绍了运动规划的实验设计,并对关节调试作了总结和分析,指出了存在的问题和解决的办法。     

基于改进蚁群算法的四足机器人步态规划

四足机器人关节众多、运动方式复杂,步态规划是四足机器人运动控制的基础。传统的算法多基于仿生原理,缺乏广泛适应性。 在建立运动学方程的基础上,提出了一种基于改进蚁群算法的步态规划算法。该算法利用了四足机器人4条腿运动的线性无关性,将步态规划问题转换为在四维空间里求取最长路径问题。仿真结果表明,该算法得出了满足约束条件的所有步态,最后通过机器人样机检验,验证了该算法求取结果的有效性和合理性。     

本期摘要

舵机控制步行机器人系统设计 首先设计了两足步行机器人的本体结构,并选择舵机作为驱动源。然后．基于广义坐标对该机器人进行了运动学建模,该方法运算简便直观易懂。重点讨论了动态步行的算法设计,详细分析了基于零力矩点的仿人机器人动态步行运动规划方法。结合机器人的几何约束和运动约束．推导机器人参数化步态设计的推导公式,机器人步态的参数化设计大大方便了机器人的运动学和动力学分析。     

全方位六足步行机器人分析——腿机构、运动学、静力学分析、步态规划与步行软件

本文对全方位六足步行机器人步行中所涉及的步态规划、步行算法及步行软件,稳定性分析、能耗分析等问题进行了深入地研究.首先依据相对运动学原理建立全方位六足步行机器人的运动学。并对其工作空间进行了详细地分析,接着讨论了步行机器人的单腿静力学分析及多腿触地情况下足端力的分力求解问题.把 M-P 广义逆与求解超静定力问题的解法相结合,对足端力的分布特性及求解方法进行了研究.     

RoboCup中型组足球机器人的改进模糊HSIC运动控制

针对RoboCup中型组三轮全向足球机器人路径规划和轨迹跟踪的特点,结合仿人智能控制(human-simulated intelligent control,HSIC)算法,提出了改进模糊仿人智能运动控制算法,并将其运用于该系统的运动控制.实验研究证明,该算法具有控制精度高、稳定性好、能实时逼近期望路径的特点,完全满足RoboCup足球机器人运动控制的要求.另外,模糊控制的控制规则表可以由改进HSIC的逻辑控制规则所确定,使模糊控制器的设计更易于实现.     

双足步行机器人转弯步态规划及其实现

针对双足步行机器人的转弯步态规划及其实现问题进行了研究.首先介绍了双足步行机器人转弯步态规划方法和所涉及的关键问题,包括关键点轨迹插值和逆运动学解算,然后给出了实现双足步行机器人转弯步态规划的具体步骤,最后通过对实验室新研制的双足步行机器人转弯运动进行仿真和实验研究,证实了本文所提出的几何约束加修正补偿的双足步行机器人转弯步态规划方法的有效性和可行性.     

基于栅格法的移动机器人运动规划研究

研究移动机器人运动规划问题.为实现机器人独立自主地完成任务行为,提出了一种利用栅格法对移动机器人运动进行规划,算法将运动规划分解为路径规划和运动控制两部分.在路径规划时,对栅格环境设定机器人的假想窗口栅格,并根据假想窗口和环境信息的可信度,设定实现环境信息优化的路径规划策略.根据机器人的运动学模型推导出机器人的运动控制律,以实现问题的求解.最后对运动规划方法进行了仿真验证,仿真结果证明了控制律的有效性.     

Real-time seam tracking for robotic laser welding using trajectory-based control

In this paper a real-time seam tracking algorithm is proposed that can cope with the accuracy demands of robotic laser welding. A trajectory-based control architecture is presented, which had to be developed for this seam tracking algorithm. Cartesian locations (position and orientation) are added to the robot trajectory during the robot motion. In this way, sensor information obtained during the robot motion is used to generate the robot trajectory while moving. Experiments have been performed to prove the tracking capabilities of the seam tracking algorithm.     

基于马尔可夫决策过程的群体动画运动轨迹生成

近些年来,群体动画在机器人学、电影、游戏等领域得到了广泛的研究和应用,但传统的群体动画技术均涉及复杂的运动规划或碰撞避免操作,计算效率较低.本文提出了一种基于马尔可夫决策过程（MDPs）的群体动画运动轨迹生成算法,该算法无需碰撞检测即可生成各智能体的无碰撞运动轨迹.同时本文还提出了一种改进的值迭代算法用于求解马尔可夫决策过程的状态-值,利用该算法在栅格环境中进行实验,结果表明该算法的计算效率明显高于使用欧氏距离作为启发式的值迭代算法和Dijkstra算法.利用本文提出的运动轨迹生成算法在三维（3D）动画场景中进行群体动画仿真实验,结果表明该算法可实现群体无碰撞地朝向目标运动,并具有多样性.     

Extracting representative motion flows for effective video retrieval

In this paper, we propose a novel motion-based video retrieval approach to find desired videos from video databases through trajectory matching. The main component of our approach is to extract representative motion features from the video, which could be broken down to the following three steps. First, we extract the motion vectors from each frame of videos and utilize Harris corner points to compensate the effect of the camera motion. Second, we find interesting motion flows from frames using sliding window mechanism and a clustering algorithm. Third, we merge the generated motion flows and select representative ones to capture the motion features of videos. Furthermore, we design a symbolic based trajectory matching method for effective video retrieval. The experimental results show that our algorithm is capable to effectively extract motion flows with high accuracy and outperforms existing approaches for video retrieval.     

短道速滑运动中的轨迹建模

为探究在短道速滑比赛视频中检测、跟踪多个运动员目标并重建运动轨迹的问题, 针对目前的技术难以保证在遮挡频繁和位置交错的复杂运动视频中完整地跟踪各个目标并恢复 其运动轨迹,提出了一套完整的算法流程,能够快速并准确地检测、跟踪运动员目标并对其运 动轨迹进行建模。进一步地,提出了一种基于三次 B-样条曲线的轨迹重建算法,利用 B-样条曲 线的非均匀性和连续性,可以在缺失部分跟踪结果的情况下完整地拟合各个目标的光滑运动轨 迹。实验表明,该算法可以检测、跟踪多个运动员目标并重建其运动轨迹,所得结果可进一步 用于实际的技战术分析中。     

基于矢量场的无人机动力学规划算法

针对传统运动规划的分层策略导致生成的轨迹被限制在同伦类和快速搜索随机树算法的采样效率较低等问题,提出一种基于矢量场指导采样的动力学规划算法。首先,采用势场函数的梯度定义的矢量场来构造圆锥体,并利用该圆锥体约束RRT*的采样;然后,通过求解最优控制问题生成运动基元来解决两点边值问题,并给出运动基元的最佳持续时间的显式解,以便最佳地连接任意一对状态;最后,通过MATLAB仿真环境下的四旋翼飞行器验证所提出的运动规划算法的可行性。实验结果表明,提出的算法与现有的技术相比在相同的迭代次数下以更短的运行时间探索了更多的状态,并且生成的轨迹具有更小的到达时间和控制花销。     

基于QPSO算法的机器人时间最优轨迹规划

在考虑关节约束的前提下,为得到工业机器人时间最优的关节运动轨迹,提出一种工业机器人时间最优轨迹规划新算法。采用五次非均匀B样条插值法构造各关节运动轨迹,得到的机器人各关节位置准确,各关节速度、加速度和加加速度曲线连续。利用量子行为粒子群优化算法(Quantum-behaved Particle Swarm Optimization,简称QPSO)进行时间最优的轨迹规划,该算法可以在整个可行域上搜索,具有较强的全局搜索能力。与标准粒子群算法(Particle Swarm Optimization,简称PSO)和差分进化算法(Differential Evolution Algorithm,简称DE)相比较,结果显示使用该算法进行时间最优的轨迹规划得到的数值结果更小。     

三焦点张量重投影视频稳像算法

目的 目前,特征点轨迹稳像算法无法兼顾轨迹长度、鲁棒性及轨迹利用率,因此容易造成该类算法的视频稳像结果扭曲失真或者局部不稳。针对此问题,提出基于三焦点张量重投影的特征点轨迹稳像算法。方法 利用三焦点张量构建长虚拟轨迹,通过平滑虚拟轨迹定义稳定视图,然后利用三焦点张量将实特征点重投影到稳定视图,以此实现实特征点轨迹的平滑,最后利用网格变形生成稳定帧。结果 对大量不同类型的视频进行稳像效果测试,并且与典型的特征点轨迹稳像算法以及商业软件进行稳像效果对比,其中包括基于轨迹增长的稳像算法、基于对极几何点转移的稳像算法以及商业软件Warp Stabilizer。本文算法的轨迹长度要求低、轨迹利用率高以及鲁棒性好,对于92%剧烈抖动的视频,稳像效果优于基于轨迹增长的稳像算法;对于93%缺乏长轨迹的视频以及71.4%存在滚动快门失真的视频,稳像效果优于Warp Stabilizer;而与基于对极几何点转移的稳像算法相比,退化情况更少,可避免摄像机阶段性静止、摄像机纯旋转等情况带来的算法失效问题。结论 本文算法对摄像机运动模式和场景深度限制少,不仅适宜处理缺少视差、场景结构非平面、滚动快门失真等常见的视频稳像问题,而且在摄像机摇头、运动模糊、剧烈抖动等长轨迹缺乏的情况下,依然能取得较好的稳像效果,但该算法的时间性能还有所不足。     

Fuzzy motion control strategy for cooperation of multiple automated vehicles with passengers comfort

This paper considers motion control for a cooperative system of automated passenger vehicles. It develops a cooperative scheme based on a decentralized planning algorithm which considers the vehicles in an initial open chain configuration. In this scheme the trajectories are intersections-free, and each trajectory is planned independently of the others. To ensure the stabilization of each vehicle in the planned trajectory, a fuzzy closed loop motion control is presented, where, based on the properties of the Fuzzy maps, the Lyapunov’s stability of the motion errors is demonstrated for all the vehicles. Based on the ISO 2631-1 standard, the saturation property of the Fuzzy maps guarantees low values of longitudinal and lateral accelerations, to ensure comfort of the human body during the motion. The validity of this control algorithm is supported by simulation experiments.     

A novel compound biped locomotion algorithm for humanoid robots to realize biped walking

In this paper, a compound biped locomotion algorithm for a humanoid robot under development is presented. This paper is organized in two main parts. In the first part, it mainly focuses on the structural design for the humanoid. In the second part, the compound biped locomotion algorithm is presented based on the reference motion and reference Zero Moment Point （ZMP）. This novel algorithm includes calculation of the upper body motion and trajectory of the Center of Gravity （COG） of the robot. First, disturbances from the environment are eliminated by the compensational movement of the upper body; then based on the error between a reference ZMP and the real ZMP as well as the relation between ZMP and CoG, the CoG error is calculated, thus leading to the CoG trajectory. Then, the motion of the robot converges to its reference motion, generating stable biped walking. Because the calculation of upper body motion and trajectory of CoG both depend on the reference motion, they can work in parallel, thus providing double insurances against the robot＇s collapse. Finally, the algorithm is validated by different kinds of simulation experiments.     

A TE-E Optimal Planning Technique Based on Screw Theory for Robot Trajectory in Workspace

In the previous study, the minimum time and energy have been both considered to improve the efficiency and reliability of the manipulator operations. For further guaranteeing the tracking precision of end effector, a TE-E optimal planning technique is presented in this paper to optimize the trajectory of end effector. TE-E means two optimization objectives and one constraint condition: T is the total motion time, the first E is the total kinetic energy consumption and the second E is the motion error due to trajectory planning. In this technique, a local optimization process is completed to find a time-energy optimal trajectory, which could improve the movement efficiency and reliability. In this local process, the screw theory is used to obtain the forward and inverse kinematic models for simplifying the computation. The multi-solution situation in inverse kinematic is considered. The modified cubic spline interpolation is applied in the joint space to obtain the good motion stability. The objective function is defined as the weighted sum of two optimization objectives. The local optimal trajectory is obtained by using the particle swarm optimization (PSO) algorithm. Finally, the motion errors are considered as a condition to determine the number of the path points and obtain the final optimal trajectory that has good tracking precision. The simulation experiment for QJ-1 welding manipulator is completed to verify the reliability and validity of this technique. In the optimal trajectory, the relationships between the motion time and parameters for each joint show a good performance in the motion. The comparison of motion errors obtained by using the previous and presented methods proves the validity of this presented technique.