Demonstration-based learning and control for automatic grasping

We present a method for automatic grasp generation based on object shape primitives in a Programming by Demonstration framework. The system first recognizes the grasp performed by a demonstrator as well as the object it is applied on and then generates a suitable grasping strategy on the robot. We start by presenting how to model and learn grasps and map them to robot hands. We continue by performing dynamic simulation of the grasp execution with a focus on grasping objects whose pose is not perfectly known.     

一种自动翻页扫描机器人的研究

本文介绍一种自动翻页扫描机器人,它能根据设定的扫描参数自动完成翻页、通过数码相机拍摄文字图片、页码识别,然后进行简单地图像处理并按指定的格式存贮,可实现图书电子化过程的自动化。本机器人主要用于代替扫描中繁杂的手动操作,在办公室、图书馆等需要大量扫描书本等印刷物的场所具有广泛的应用前景。     

专题报道：机器鱼水球赛技巧与技术——基于角度和加速度传感器的仿生机器鱼自我定位技术研究

本文分析角度传感器和加速度传感器的技术特点,总结欧拉角法、方向余弦法,四元数法三种常用坐标换算方法,对机器鱼实现自我定位、获得自身位置信息（游速,游向、游动距离、深度等）和姿态信息（鱼头仰角、鱼体转角等）的可行性进行论证,研究了在机器鱼水球比赛环境中,传感器的安装、校准、数据计算以及信息记录的     

基于扩张状态观测的机器人分散鲁棒跟踪控制

针对模型不确定性多关节机器人的轨迹跟踪控制问题, 提出一种基于扩张状态观测补偿的关节独立分散鲁棒控制方法. 设计多个并联的扩张状态观测器, 分别对每个独立关节的未知模型动态与外部扰动进行动态估计和补偿, 采取非线性状态反馈控制以提高系统的控制性能. 各个关节的控制完全独立, 因而控制器结构简单、可靠、易于实现. 对所设计的关节分散鲁棒控制器的 Lyapunov 稳定性进行了分析, 证明系统是指数收敛全局一致最终有界稳定的. 对 PUMA560 机械手的大量控制仿真验证了本文方法的有效性.     

湍流烟羽环境下多机器人主动嗅觉实现方法研究

给出了一种用于实现主动嗅觉(也称气味/气体源定位或化学烟羽跟踪)的多机器人协同搜索策略. 将蚁群算法与逆风搜索相结合用于协调多机器人的运动方向. 蚁群算法可有效调动机器人朝信息素高的区域运动且保证机器人之间的距离不会过大; 逆风搜索可降低算法过早地陷入局部最优的概率. 为正确判断转移方向, 蚁群算法中还增加了对历史信息的考虑. 在源头确认方面, 本文提出了气味/气体浓度持久性判断结合机器人旋转计算流体质量通量散度的方法. 仿真表明, 本文的主动嗅觉搜索策略可适用于湍流烟羽环境, 且可有效地逃脱浓度局部最优和风场的漩涡, 另外可最终确认源头位置.     

A force–impedance controlled industrial robot using an active robotic auxiliary device

A strategy to improve the performance of current commercial industrial robots is presented in this paper. This strategy involves cooperation of two robotic manipulators: the robotic controlled impedance device (RCID) and a commercial industrial robot. The RCID is a small six degrees-of-freedom (DOF) high bandwidth force–impedance controlled parallel manipulator, developed at the School of Engineering of the University of Porto (Portugal). The RCID works attached in series with a position controlled commercial industrial robot. Combination of the two manipulators behaves as a single manipulator having the impedance and force control dynamic performance of the RCID, as well as the workspace and trajectory tracking bandwidth of the industrial robot. Force–impedance control of the RCID, and experimental results on typical tasks that involve end-effector contact with uncertain environments of unknown stiffness are presented.     

Determination of optimum robot base location considering discrete end-effector positions by means of hybrid genetic algorithm

The performance of a robot manipulator during a process depends on its position relative to the corresponding path. An ill-placed manipulator risks inefficient operation as well as blocks due to singularities. The paper deals with an optimization algorithm to determine the base position and the joint angles of a spatial robot, when the end-effector poses are prescribed, avoiding the singular configurations. The optimization problem is solved through a hybrid heuristic method that combines the advantages of a genetic algorithm, a quasi-Newton algorithm and a constraints handling method. Six cases of a 6-DOF manipulator are studied to verify the feasibility of the proposed algorithm.     

小型双足步行机器人的机构设计及其运动仿真

小型双足步行机器人具有多关节、多驱动器、多自由度的特点,本文以人体全身17个主要关节及其运动特性为研究对象,利用三维设计软件CATIA设计出小型双足步行机器人的全身机构,根据ZMP理论,以正常人行走的“X”形交叉动作为原则,规划出其各关节转角,在ADAMS下对其虚拟样机进行运动仿真,确保实现机器人的稳定步行和做舞蹈动作。     

Facial expression recognition and tracking for intelligent human-robot interaction

For effective interaction between humans and socially adept, intelligent service robots, a key capability required by this class of sociable robots is the successful interpretation of visual data. In addition to crucial techniques like human face detection and recognition, an important next step for enabling intelligence and empathy within social robots is that of emotion recognition. In this paper, an automated and interactive computer vision system is investigated for human facial expression recognition and tracking based on the facial structure features and movement information. Twenty facial features are adopted since they are more informative and prominent for reducing the ambiguity during classification. An unsupervised learning algorithm, distributed locally linear embedding (DLLE), is introduced to recover the inherent properties of scattered data lying on a manifold embedded in high-dimensional input facial images. The selected person-dependent facial expression images in a video are classified using the DLLE. In addition, facial expression motion energy is introduced to describe the facial muscle’s tension during the expressions for person-independent tracking for person-independent recognition. This method takes advantage of the optical flow which tracks the feature points’ movement information. Finally, experimental results show that our approach is able to separate different expressions successfully.