Maneuverability modeling and trajectory tracking for fish robot

This study develops a 6-DOF mathematical model for a robotic fish that considers surge, sway, heave, roll, pitch, and yaw. The model considers the conditions of a fish swimming in ocean current perturbations similar to the ocean current perturbations of the slender-body autonomous underwater vehicles. For swimming and turning behaviors, a nonlinear, dynamic, carangiform locomotion model is derived by using a planar four-link model. A 2-DOF barycenter mechanism is proposed to provide body stabilization and to serve as an actuating device for active control design. A barycenter control scheme is developed to change the center of gravity of the robot fish body by moving balancing masses along two axes. The projected torque on x and y axes propel pitch and roll angles to the desired settings. A Stabilizing controller, fish-tail mechanism, rigid body dynamics, and kinematics are incorporated to enable the fish robot to move in three dimensional space. Simulation results have demonstrated maneuverability and control system performance of the developed controller which is proposed to conduct path tracking of the robot fish as it swims under current perturbations.     

Variability in stepping direction explains the veering behavior of blind walkers.

Walking without vision results in veering, an inability to maintain a straight path that has important consequences for blind pedestrians. In this study, the authors addressed whether the source of veering in the absence of visual and auditory feedback is better attributed to errors in perceptual encoding or undetected motor error. Three experiments had the following results: No significant differences in the shapes of veering trajectories were found between blind and blindfolded participants; accuracy in detecting curved walking paths was not correlated with simple measures of veering behavior; and explicit perceptual cues to initial walking direction did not reduce veering. The authors present a model that accounts for the major characteristics of participants' veering behavior by postulating 3 independent sources of undetected motor error: initial orientation, consistent biases in step direction, and, most important, variable error in individual steps. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

人体步行规律与仿人机器人步态规划

从仿生学角度分析了人体的步行运动规律,提出了一种基于人体运动规律的仿人机器人步态参数设定方法.首先对人体步行运动数据进行捕捉并分析,得出人体各步态参数间的函数关系,以人体步行相似性作为评价指标,提出仿人机器人步态参数的设定方法.其次,通过分析人体在步行过程中的补偿支撑脚偏航力矩的基本原理,提出了基于双臂及腰关节协调运动的仿人机器人偏航力矩补偿算法,以提高仿人机器人行走的稳定性.最后通过仿真及实验验证了所提出的步态规划方法的正确性及有效性.     

基于目标导向行为和空间拓扑记忆的视觉导航方法

针对在具有动态因素且视觉丰富环境中的导航问题,受路标机制空间记忆方式启发,提出一种可同步学习目标导向行为和记忆空间结构的视觉导航方法.首先,为直接从原始输入中学习控制策略,以深度强化学习为基本导航框架,同时添加碰撞预测作为模型辅助任务;然后,在智能体学习导航过程中,利用时间相关性网络祛除冗余观测及寻找导航节点,实现通过情景记忆递增描述环境结构;最后,将空间拓扑地图作为路径规划模块集成到模型中,并结合动作网络用于获取更加通用的导航方法.实验在3D仿真环境DMlab中进行,实验结果表明,本文方法可从视觉输入中学习目标导向行为,在所有测试环境中均展现出更高效的学习方法和导航策略,同时减少构建地图所需数据量;而在包含动态堵塞的环境中,该模型可使用拓扑地图动态规划路径,从而引导绕路行为完成导航任务,展现出良好的环境适应性.     

一种基于VINS/FINS组合导航方法

针对视觉惯性组合导航系统中微惯性器件精度偏低,以及足部惯性导航系统航向角误差可观测性差的问题,研究了一种基于上述两种系统的信息双向融合的导航定位方案. 该方法的系统结构由安装于双足步行机器人躯干部分的惯性导航系统和安装于其足部惯性导航系统两部分组成. 惯性导航系统通过视觉同时定位与地图构建数据融合方法可以获得相对准确的航向角,足部惯性导航系统利用零速修正后的位置信息实时修正惯性导航系统中的低精度惯性器件误差,从而构建视觉与惯性信息双向融合的组合导航系统结构. 实验结果表明,该组合导航方案可以有效提高双足步行机器人的航向精度和定位精度.     

A binary approximating method for graspable region determination of biped climbing robots

For a biped pole-climbing robot (BiPCR) with grippers, it is an essential demand to determine the target grasp configuration for climbing and transiting between poles, with the graspable region as a priori knowledge. The graspable region on the target pole is critically important for climbing path planning and motion control. To efficiently compute the graspable region for a BiPCR, we propose a novel binary approximating method in this paper. This method may also be applied to generate the three-dimensional (3-D) workspace of a manipulator with constant orientation. The grasping problem and the concept of graspable region for a BiPCR are first introduced. The binary approximating method and the corresponding algorithms are then presented to generate the graspable region. Additional constraints on a biped climbing robot with five degrees of freedom (DoFs) are presented as a supplement to the algorithm. A series of comprehensive simulations are conducted with the five-DoF and six-DoF climbing robots to verify the effectiveness of the proposed method. Finally, the dexterity of biped climbing robots with different DoFs is discussed.     

双足机器人稳定步行模式预测控制实现方法的研究

针对现有的预测控制生成步行模式方法中忽略了参数间关系和参数取值范围的问题进行探讨.预测控制通过控制质心运动生成步行模式以实现ZMP目标轨迹跟踪,根据预测控制器模型研究参数间的关系,并通过极点分析讨论其取值范围,提出关键参数在容许取值范围内,可以保证系统的稳定性,并生成满足稳定步行的质心运动.通过仿真实验分析了在存在扰动情况下,关键参数取适当值,能够生成稳定的步行模式.     

基于约束满足的多目标双足机器人动态步态参数优化*

目前的步态优化算法仅仅实现了对单一目标的优化,把双足机器人步态优化看做是多目标优化问题,构建了衡量稳定性、能量消耗、步行速度三个目标评价函数。考虑到直接对多个目标加权求和的方法不能很好地处理多目标问题,提出一种新的基于约束满足的多目标步态参数优化算法,其思想是把基于惩罚函数的SPEA2(strength Pareto evolutionary algorithm2 )应用到多目标双足机器人动态步态参数优化问题上,规划出了同时满足这三个目标的动态优化步态。通过仿真实验表明了算法的有效性。     

Online gait programming of humanoid walking via NMPC

In order to satisfy the requirement of realtime gait programming of humanoid walking with foot rotation,a kind of modified Nonlinear Model Predictive Control (NMPC) scheme was proposed. Based on setting suitable kinetic and kinematic virtual constraints of Single Support Phase (SSP) and three subphases of Double Support Phase (DSP) ,complex realtime gait programming problem was simplified to four online NMPC dynamic optimization problems. A numerical approach was proposed to transform the dynamical optimization problem to the finite dimensional static optimization problem which can be solved by Sequential Quadratic Programming (SQP) . It can be concluded from simulation that using this method on BIP model can realize online gait programming of dynamic walking with foot rotation and the biped stability can be satisfied such that there is no sliding during walking.     

Biomimetic Experimental Research on Hexapod Robot's Locomotion Planning

To provide hexapod robots with strategies of locomotion planning, observation experiments were operated on a kind of ant with the use of high speed digital photography and computer assistant analysis. Through digitalization of original analog video, locomotion characters of ants were obtained, the biomimetic foundation was laid for polynomial trajectory planning of multi-legged robots, which was deduced with mathematics method. In addition, five rules were concluded, which apply to hexapod robots marching locomotion planning. The first one is the fundamental strategy of multi-legged robots’ leg trajectory planning. The second one helps to enhance the static and dynamic stability of multi-legged robots. The third one can improve the validity and feasibility of legs’ falling points. The last two give criterions of multi-legged robots’ toe trajectory figures and practical recommendatory constraints. These five rules give a good method for marching locomotion planning of multi-legged robots, and can be expended to turning planning and any other special locomotion.