关键词： 冗余驱动并联机器人   ADAMS   驱动力优化   动力学仿真  

摘要： 为使机器人具有良好的结构性能和工作性能,其结构系统必须具有良好的动力学特性.针对动力学特性问题,以ADAMS仿真软件为平台建立了简化的二自由度冗余驱动并联机器人模型,求出了运动学逆解,采用冗余驱动力控制电机的方法,完成了动力学仿真.结果表明该方法能减小驱动力变化范围和降低驱动力峰值,优化电机驱动力,提高并联机器人的驱动性能.研究所得的方法和结论具有较强的通用性,对相关冗余驱动并联机器人的动力学研究具有普遍的应用意义,同时为并联机器人的调试与控制提供了理论依据.

关键词： 机器人竞赛   实验学校   湖南师大   赛中   学生   天津市   青少年   初中  

摘要： 本刊讯2012年7月16-20日，第二届中国青少年机器人竞赛在天津市举行，共有来自全国各地的40支初中代表队参赛。湖南师大附中博才实验学校杨天诚、雷石林、

关键词： 《机器人学》   工程教学法   视觉运动平台  

摘要： 针对当前本科生《机器人学》课程理论与实践教学效果差的情况,探索实践教学的改革与创新,提出了基于视觉运动平台的项目实践及与理论创新相结合的工程教学理念,提高了学生学习《机器人学》课程的兴趣,发挥了学生的主动性和创新能力,使得课程教学效果得到了提高,实现了教学目的。

关键词： 自治水下机器人   生物启发模型   运动控制   全局渐近稳定  

摘要： 本文提出一种生物启发神经动力学模型的自治水下机器人(autonomous underwater vehicles,AUV)三维轨迹跟踪控制算法.将AUV在三维空间的运动分为水平面运动和垂直面运动,针对传统反步轨迹跟踪控制器出现的速度跳变问题,采用生物启发神经动力学模型,通过构造一种简单的中间虚拟变量,同时结合Lyapunov函数设计出轨迹跟踪控制律,使其控制效果在水平面和垂直面都能够达到全局渐近稳定并且有平滑连续的输出结果,克服AUV反步轨迹跟踪控制的速度跳变问题.仿真结果证明了所提控制律的有效性.

关键词： Robotics   Automation   Investments  

摘要： The author presents his views regarding the unwillingness of companies to invest in automation and robotics.

关键词： Self-organizing skill learning   Skill decomposition   Skill synthesis   Neuro-fuzzy network   Reinforcement learning  

摘要： Endowing robots with the ability of skill learning enables them to be versatile and skillful in performing various tasks. This paper proposes a neuro-fuzzy-based, self-organizing skill-learning framework, which differs from previous work in its capability of decomposing a skill by self-categorizing it into significant stimulus-response units (SRU, a fundamental unit of our skill representation), and self-organizing learned skills into a new skill. The proposed neuro-fuzzy-based, self-organizing skill-learning framework can be realized by skill decomposition and skill synthesis. Skill decomposition aims at representing a skill and acquiring it by SRUs, and is implemented by stages with a five-layer neuro-fuzzy network with supervised learning, resolution control, and reinforcement learning to enable robots to identify a sufficient number of significant SRUs for accomplishing a given task without extraneous actions. Skill synthesis aims at organizing a new skill by sequentially planning learned skills composed of SRUs, and is realized by stages, which establish common SRUs between two similar skills and self-organize a new skill from these common SRUs and additional new SRUs by reinforcement learning. Computer simulations and experiments with a Pioneer 3-DX mobile robot were conducted to validate the self-organizing capability of the proposed skill-learning framework in identifying significant SRUs from task examples and in common SRUs between similar skills and learning new skills from learned skills.

关键词： Robotic   Surgery   Gynecology   Benign pathology   Oncology  

摘要： Robot-assisted laparoscopic gynecologic surgery has undergone widespread development in recent years. The surgical literature on this subject continues to grow. The goal of this article is to summarize the principal indications for robotic assistance in gynecologic surgery and to offer a general overview of the principal articles dealing with robotic surgery for both benign and malignant disease. (C) 2012 Elsevier Masson SAS. All rights reserved.

关键词： Cognitive architecture principles   Cognitive Robotics   Requirements for cognitive robotics  

摘要： Research in robotic systems has traditionally been identified with approaches that are characterized by the use of carefully crafted representations and processes to find optimal solutions. The use of such representations and processes, which we refer to as the algorithmic approach, is uniquely suited for problems requiring strong models, i.e., tasks and domains that are well defined, and/or involve close interaction with the environment. These problems have historically been the focus of robotics research because they exercise perceptual, motor and manipulation capabilities that form the basic foundational abilities required for every robotic agent. Recent work (for example ROS and Tekkotsu) on the abstraction and encapsulation of perception and motor functionality has standardized the above mentioned foundational abilities and allowed researchers to study problems in less clearly defined and open-ended domains: problems that have previously been considered the province of Al and Cognitive Science. In this paper, we argue that the study of these problems (examples of which include multi-agent interaction, instruction following and reasoning in complex domains) referred to under the rubric of Cognitive Robotics is best achieved via the use of cognitive architectures - unified computational frameworks developed specifically for general problem solving and human cognitive modeling. We lay out the relevant architectural concepts and principles and illustrate them using nine cognitive architectures that are under active development - Soar, ACT-R, CLARION, GMU-BICA, Polyscheme, Co-JACK, ADAPT, ACT-R/E, and SS-RICS. (C) 2012 Elsevier B.V. All rights reserved.