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.     

Design and locomotion analysis of two kinds of rolling expandable mobile linkages with a single degree of freedom

Frontiers of Mechanical Engineering - This study presents two kinds of rolling robots that are able to roll by deforming their outer shapes with a single degree of freedom. Each robot is an...     

Mathematical programs with complementarity constraints in the context of inverse optimal control for locomotion

In this paper an inverse optimal control problem in the form of a mathematical program with complementarity constraints (MPCC) is considered and numerical experiences are discussed. The inverse optimal control problem arises in the context of human navigation where the body is modelled as a dynamical system and it is assumed that the motions are optimally controlled with respect to an unknown cost function. The goal of the inversion is now to find a cost function within a given parametrized family of candidate cost functions such that the corresponding optimal motion minimizes the deviation from given data. MPCCs are known to be a challenging class of optimization problems typically violating all standard constraint qualifications (CQs). We show that under certain assumptions the resulting MPCC fulfills CQs for MPCCs being the basis for theory on MPCC optimality conditions and consequently for numerical solution techniques. Finally, numerical results are presented for the discretized inverse optimal control problem of locomotion using different solution techniques based on relaxation and lifting.     

仿人机器人发展现状及其腰关节的作用

仿人机器人是研究人类智能的高级平台，是综合多种学科的复杂智能机械，其研制和开发涉及到各学科、多方面问题，目前已成为机器人领域的研究热点问题之一．本文对仿人机器人目前的发展现状进行了综述，分析了多种仿人机器人的自由度分布，介绍了具有不同结构特点的腰机构，分析了腰关节在仿人机器人的稳定动态步行、全身协调运动及有情感步行等方面的重要作用．本文还指出了仿人机器人目前的主要研究方向．     

沉浸式虚拟现实环境下走动对场景识别的影响

采用沉浸式虚拟现实技术,在典型空间更新范式下研究：①运动对场景识别的影响;②沉浸式虚拟现实技术本身在场景识别研究中的效度。组间变量是测试视点情况（与学习视点相同和与学习视点不同）,组内变量是桌子状况（桌子静止和旋转）。因变量是正确判断物体位置改变的比率。结果发现：①视点依赖效应：在相同测试视点的识别成绩显著好于在不同测试视点条件下的识别成绩。②空间更新效应：无论不同测试视点还是在相同视点条件下,桌子静止时的识别成绩显著好于桌子转动条件下的识别成绩。③沉浸式虚拟现实环境下获得与真实环境结果一致的模式,说明沉浸式虚拟现实技术是场景识别研究中的一种十分有效的方法。     

未知不平整地面上的双足步行稳定控制

 针对未知的不平整地面环境,提出了双足机器人稳定步行控制算法,该算法由步态规划和传感器反馈控制两部分组成.采用被动倒立摆模型设计双足机器人的步态,使得双足机器人能够自然、节能的稳定行走.实时反馈控制用来适应地面环境的凹凸不平以及处理外部环境的扰动.控制器包括上身姿态控制、期望ZMP控制以及非线性落地控制三部分.双足机器人机构柔性的存在对机器人稳定性以及控制效果造成很坏的影响,甚至使反馈控制造成负面的效果,因此柔性的影响也被考虑到步行控制器的设计当中.利用双足机器人不平地面上的步行实验验证所提出步行控制算法的有效性.     

Dissociation of conditioned locomotion and Fos induction in response to stimuli formerly paired with cocaine.

A discrete stimulus (flashing light) was paired with cocaine (20 mg/kg) to induce conditioned locomotion. To identify brain regions activated during this response, Fos was measured with immunohistochemistry. Although paired subjects displayed robust conditioned locomotion, Fos was not increased in any limbic brain regions analyzed. In contrast, pairing of cocaine with generalized contextual cues (whole room) produced conditioned locomotion and Fos activation in the prelimbic portion of prefrontal cortex and the nucleus accumbens core. These results suggest that the pattern of neuronal activation during cocaine-conditioned activity differs depending on whether a discrete or contextual stimulus is used as a conditioned stimulus. The possibility that expectancy and frustrative nonreward contribute to Fos expression in rats conditioned to contextual cues is discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

面向离散地形的欠驱动双足机器人平衡控制方法

欠驱动双足机器人在行走中为保持自身的平衡, 双脚需要不间断运动. 但在仅有特定立足点的离散地形上很难实现调整后的落脚点, 从而导致欠驱动双足机器人在复杂环境中的适应能力下降. 提出了基于虚拟约束(Virtual constraint, VC)的变步长调节与控制方法, 根据欠驱动双足机器人当前状态与参考落脚点设计了非时变尺度缩放因子, 能够实时重构适应当前环境的步态轨迹; 同时构建了全身动力学模型, 采用反馈线性化的模型预测控制 (Model predictive control, MPC) 滚动优化产生力矩控制量, 实现准确的轨迹跟踪控制. 最终进行了欠驱动双足机器人的随机离散地形稳定行走的仿真实验, 验证了所提方法的有效性与鲁棒性.