自动化立体仓库搬运机器人精定位视觉系统

本文介绍一个搬运机器人的视觉系统.该系统是为机器人在具有较大相对位置偏差的货架中准确存取而研制的.系统由 CCD 摄象机获取货架图象,经过处理,给出精定位数据,从而引导机器人准确定位.     

Stability and control of dynamic walking for a five-link planar biped robot with feet

During dynamic walking of biped robots, the underactuated rotating degree of freedom （DOF） emerges between the support foot and the ground, which makes the biped model hybrid and dimension-variant. This paper addresses the asymptotic orbit stability for dimension-variant hybrid systems （DVHS）. Based on the generalized Poincare map, the stability criterion for DVHS is also presented, and the result is then used to study dynamic walking for a five-link planar biped robot with feet. Time-invariant gait planning and nonlinear control strategy for dynamic walking with fiat feet is also introduced. Simulation results indicate that an asymptotically stable limit cycle of dynamic walking is achieved by the proposed method.     

RUNA: a multimodal command language for home robot users

This article describes a multimodal command language for home robot users, and a robot system which interprets users’ messages in the language through microphones, visual and tactile sensors, and control buttons. The command language comprises a set of grammar rules, a lexicon, and nonverbal events detected in hand gestures, readings of tactile sensors attached to the robots, and buttons on the controllers in the users’ hands. Prototype humanoid systems which immediately execute commands in the language are also presented, along with preliminary experiments of faceto-face interactions and teleoperations. Subjects unfamiliar with the language were able to command humanoids and complete their tasks with brief documents at hand, given a short demonstration beforehand. The command understanding system operating on PCs responded to multimodal commands without significant delay. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Guidance of a mobile robot using an array of static cameras located in the environment

This paper presents a new proposal for positioning and guiding mobile robots in indoor environments. The proposal is based on the information provided by static cameras located in the movement environment. This proposal falls within the scope of what are known as intelligent environments; in this case, the environment is provided with cameras that, once calibrated, allow the position of the robots to be obtained. Based on this information, control orders for the robots can be generated using a radio frequency link. In order to facilitate identification of the robots, even under extremely adverse ambient lighting conditions, a beacon consisting of four circular elements constructed from infrared diodes is mounted on board the robots. In order to identify the beacon, an edge detection process is carried out. This is followed by a process that, based on the algebraic distance, obtains the estimated ellipses associated with each element of the beacon. Once the beacon has been identified, the coordinates of the centroids for the elements that make up the beacon are obtained on the various image planes. Based on these coordinates, an algorithm is proposed that takes into account the standard deviation of the error produced in the various cameras in ascertaining the coordinates of the beacon’s elements. An odometric system is also used in guidance that, in conjunction with a Kalman Filter, allows the position of the robot to be estimated during the time intervals required to process the visual information provided by the cameras.

用奇异模型描述的受限机器人的学习控制

本文了一类受限机器人的迭代学习控制方案，控制器的设计是基于机器人模型的降阶形式。在存在有界未知干扰的情况下，对末端操纵器受线性、无摩擦约束面的受限机器人。本文给出的控制方案保证了机器人系统的完全运动跟踪，同时保证了力跟踪误差有界的，且界的大小是可调节的。     

微细电火花加工技术的最新进展及应用实例

介绍了微细电火花加工技术的最新进展，并以一些最新的应用实例反映了该技术的发展趋势和应用前景。     

用于移动机器人避障的人工神经网络和模糊逻辑控制技术

提出了一种用于移动机器人对当前感知环境进行了识别和分类进而实现避障的方法，分析和研究反映当前感知环境的特征向量的抽取技术，并建立反映期望环境类别的特征向量训练样本数据库；建立基于ＡＲＴ２神经网络的分类器模型，根据多传感器信息实现移动机器人对其当前感知环境进行快速识别和分类；利用模糊逻辑技术，设计用于移动机器人在未知环境下避障的三维模型控制器，在ＴＩＴ－１型移动机器人上进行实验。     

基于模糊神经网络的机器人滑模自适应控制

滑模控制（SMC）响应快,对系统参数和外部扰动呈不变性,可保证系统的渐近稳定性,但其缺点是控制存在很强的抖动;而模糊神经网络（FNN）具有模糊系统和神经网络共同的特点。将滑模控制和模糊神经网络控制有机结合,利用简单得到的学习信号对模糊神经网络进行在线学习,通过平滑切换函数实现直接自适应控制策略。对两连杆机械手的仿真研究表明,在存在模型误差和外部扰动的情况下,该方案既能达到高精度快速跟踪的目的,又能有效减小滑模控制的抖动问题。     

机器人卫星自主控制系统的研究

在国内首次研制成功了机器人卫星（或称空间自由飞行机器人）的自主控制系统及其地上实验平台。该自主控制系统在平台上实现的空间微重力环境条件下，通过运动规划系统能完成机器人卫星自主地避开障碍物，准确地捕捉目标的路径规划演示实验。这一成果对用机器人卫星捕捉失效卫星并对其进行维修、补给能量从而使其复活再生的研究具有实际应用意义。