摘要： Building general purpose autonomous robots that suit a wide range of user-specified applications, requires a leap from today's task-specific machines to more flexible and general ones. To achieve this goal, one should move from traditional prepro- grammed robots to learning robots that easily can acquire new skills. Learning from Demonstration (LfD) and Imitation Learning (IL), in which the robot learns by observing a human or robot tutor, are among the most popular learning tech- niques. Showing the robot how to perform a task is often more natural and intuitive than figuring out how to modify a complex control program. However, teaching robots new skills such that they can reproduce the acquired skills under any circum- stances, on the right time and in an appropriate way, require good understanding of all challenges in the field. Studies of imitation learning in humans and animals show that several cognitive abilities are engaged to learn new skills correctly. The most remarkable ones are the ability to direct attention to important aspects of demonstrations, and adapting observed actions to the agents own body. Moreover, a clear understanding of the demonstrator's intentions and an ability to generalize to new situations are essential. Once learning is accomplished, various stimuli may trigger the cognitive system to execute new skills that have become part of the robot's repertoire. The goal of this thesis is to develop methods for learning from demonstration that mainly focus on understanding the tutor's intentions, and recognizing which elements of a demonstration need the robot's attention. An architecture containing required cognitive functions for learning and reproduction of high-level aspects of demonstrations is proposed. Several learning methods for directing the robot's attention and identifying relevant information are introduced. The architecture integrates motor actions with concepts, objects and environmental states to ensure correct reproduction

摘要： This issue of Autonomous Robots presents journal articles that are based on papers originally presented at the 2013 Robotics Science and Systems conference, held in Berlin, Germany. Although these were selected by a committee to exemplify the best papers presented that year, the decision over which papers to include was a difficult one due to the substantial number of very strong papers in the cohort. While the strength of these papers can be partially attributed to the fact that the conference itself generally attracts strong papers, it is also a sign of the maturation of our field. The papers in this issue reflect a few broad themes that are currently attracting the attention of the robotics research community: the development of multi-agent systems (where the agents can be either multiple robots, or a mixture of humans and robots), the link between sensing and manipulation in robotic systems, and the continuing use of sophisticated probabilistic representations in robot control.

关键词： goal-directed   decision-making   prediction   computational model   neural mechanism   robotics  

摘要： The brain has evolved to act in a complex and unpredictable world, and it must continuously select among many goals and action options. In the past 20 years, research in neuroscience and robotics has principally focused on the neural underpinnings of habitual choice, linked to stimulus-response mechanisms in restricted contexts. However, a recent trend of research is to focus on goal-directed choice mechanisms that select among anticipated action outcomes in a context-dependent way. These goal-oriented processes provide the foundations of many everyday human and animal decisions.

关键词： Agent-based modeling   Computer and information sciences   Engineering and technology   Mathematics   Mechanical engineering   Physical sciences   Research and analysis methods   Research Article   Robotics   Robotics systems   Simulation and modeling   Systems science  

摘要： We present a unified approach to describing certain types of collective decision making in swarm robotics that bridges from a microscopic individual-based description to aggregate properties. Our approach encompasses robot swarm experiments, microscopic and probabilistic macroscopic-discrete simulations as well as an analytic mathematical model. Following up on previous work, we identify the symmetry parameter, a measure of the progress of the swarm towards a decision, as a fundamental integrated swarm property and formulate its time evolution as a continuous-time Markov process. Contrary to previous work, which justified this approach only empirically and a posteriori, we justify it from first principles and derive hard limits on the parameter regime in which it is applicable.

关键词： hydraulic system   bionic   legged robot   efficiency  

摘要： To improve the efficiency of hydraulic system of legged robot, a particular driving system is presented in this paper by imitating the multi-stage energy supplement from biological creatures. With respect to this design, it comes up with a double-stage energy supply system (DSS) using small accumulators. The DSS is a composition of a low-pressure variable pump and some other distributed instantaneous high power sources. The former provides energy for most continuous works under low pressure, while the latter is established to satisfy instant high-pressur demands by accumulators. DSS is able to achieve smaller energy loss than the energy supply system in which single-stage energy supply system (SSS) is used. The principle of DSS is described and DSS is analyzed for low energy loss. The DSS was applied in a quadruped robot as an example, and the efficiencies were calculated and compared with that of SSS when the robot makes squats, turns, and trots. Finally, some other performances were compared between DSS and SSS. The result shows that the efficiency is higher but the trim control is more difficult for DSS than SSS.

关键词： 机器人竞赛   《地球的奥秘》   计算机编程   档案   创新   兴趣爱好   湖南师大   结构设计  

摘要： 姓名：李早一 学校：湖南师大附中在校职务：校机器人队队长年龄：17岁生日：4.15星座：白羊座生肖：牛兴趣爱好：街舞、结构设计特长：计算机编程、机器人搭建最敬佩的人：安德烈·弥勒最喜欢看的书：《地球的奥秘》最喜欢看的电影：《创战纪》最想做的事：探索人体密码最自豪的事：在今年5月举行的湖南省青少年机器人竞赛上,30分钟内即兴写完-整套机器人程序,并赢得擂台赛冠军;比赛结束后对这套新颖的程序书写方法进行总结,将其命名为“图形化逻辑编程法”

关键词： 水下机器人   系统辨识   动力学模型   非参数辨识   正交小波级数  

摘要： 动力学模型辨识是机器人控制设计的基础,是水下机器人研究的核心内容之一。以Falcon水下机器人的动力学模型为研究对象,在模型适当简化的基础上,提出基于小波级数模型的水下机器人动力学在线辨识方法,选取DOG(Derivative of Gaussian)小波作为小波函数,对Falcon水下机器人纵向自由度动力学模型进行自适应辨识。针对水下机器人动力学模型的时变特性,研究负载特性变化情况下的系统辨识,得出了基于DOG小波级数模型的水下机器人动力学在线算法更加有效。

关键词： 机器视觉   机器人学   国际合作   混合学生团体  

摘要： 比利时托马斯莫里应用科技大学、荷兰海牙应用科技大学和德国波鸿应用科技大学于2013年夏季学期组织了2个国际学生团队,每个团队6人,由3所大学各派2人参加,通过互联网进行机器视觉应用的研讨,以检验国际机电一体化教育项目(IMEP)的目标,即创建跨国学生共同学习的环境——使学生能与其他国家的学生合作,共同解决机电一体化领域的问题,从而获得机器人与机器视觉的更全面培训。参与合作的大学希望能够在此基础上发展出一种增强学生国际交流能力、以及机器视觉和机器人技术知识的教学方法。

关键词： Collision detection   Human-robot physical interaction   Manipulator safety   Disturbance observer  

摘要： This paper presents the development and experimental evaluation of a collision detection method for robotic manipulators sharing a workspace with humans. Fast and robust collision detection is important for guaranteeing safety and preventing false alarms. The main cause of a false alarm is modeling error. We use the characteristic of the maximum frequency boundary of the manipulator's dynamic model. The tendency of the frequency boundary's location in the frequency domain is applied to the collision detection algorithm using a band pass filter (band designed disturbance observer, BdDOB) with changing frequency windows. Thanks to the band pass filter, which considers the frequency boundary of the dynamic model, our collision detection algorithm can extract the collision caused by the disturbance from the mixed estimation signal. As a result, the collision was successfully detected under the usage conditions of faulty sensors and uncertain model data. The experimental result of a collision between a 7-DOF serial manipulator and a human body is reported.