关键词： Neural model   Cognition   Perception   Action   Inverse model   Observational learning   DARWIN robot  

摘要： In this paper, we describe a brief survey of observational learning, with particular emphasis on how this could impact on the use of observational learning in robots. We present a set of simulations of a neural model which fits recent experimental data and such that it leads to the basic idea that observational learning uses simulations of internal models to represent the observed activity, so allowing for efficient learning of the observed actions. We conclude with a set of recommendations as to how observational learning might most efficiently be used in developing and training robots for their variety of tasks.

关键词： Reinforcement learning   learning control   robot   survey  

摘要： Reinforcement learning offers to robotics a framework and set of tools for the design of sophisticated and hard-to-engineer behaviors. Conversely, the challenges of robotic problems provide both inspiration, impact, and validation for developments in reinforcement learning. The relationship between disciplines has sufficient promise to be likened to that between physics and mathematics. In this article, we attempt to strengthen the links between the two research communities by providing a survey of work in reinforcement learning for behavior generation in robots. We highlight both key challenges in robot reinforcement learning as well as notable successes. We discuss how contributions tamed the complexity of the domain and study the role of algorithms, representations, and prior knowledge in achieving these successes. As a result, a particular focus of our paper lies on the choice between model-based and model-free as well as between value-function-based and policy-search methods. By analyzing a simple problem in some detail we demonstrate how reinforcement learning approaches may be profitably applied, and we note throughout open questions and the tremendous potential for future research.

关键词： Active contours   3D segmentation   3D reconstruction   Robot vision systems   RGB-D sensors  

摘要： In this paper, a simultaneous 3D volumetric segmentation and reconstruction method, based on the so-called Generic Fitted Shapes (GFS) is proposed. The aim of this work is to cope with the lack of volumetric information encountered in visually controlled mobile manipulation systems equipped with stereo or RGB-D cameras. Instead of using primitive volumes, such as cuboids or cylinders, for approximating objects in point clouds, their volumetric structure has been estimated based on fitted generic shapes. The proposed GFSs can capture the shapes of a broad range of object classes without the need of large a-priori shape databases. The fitting algorithm, which aims at determining the particular geometry of each object of interest, is based on a modified version of the active contours approach extended to the 3D Cartesian space. The proposed volumetric segmentation system produces comprehensive closed object surfaces which can be further used in mobile manipulation scenarios. Within the experimental setup, the proposed technique has been evaluated against two state-of-the-art methods, namely superquadrics and 3D Object Retrieval (3DOR) engines. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Dataset   autonomous driving   mobile robotics   field robotics   computer vision   cameras   laser   GPS   benchmarks   stereo   optical flow   SLAM   object detection   tracking   KITTI  

摘要： We present a novel dataset captured from a VW station wagon for use in mobile robotics and autonomous driving research. In total, we recorded 6 hours of traffic scenarios at 10-100 Hz using a variety of sensor modalities such as high-resolution color and grayscale stereo cameras, a Velodyne 3D laser scanner and a high-precision GPS/IMU inertial navigation system. The scenarios are diverse, capturing real-world traffic situations, and range from freeways over rural areas to inner-city scenes with many static and dynamic objects. Our data is calibrated, synchronized and timestamped, and we provide the rectified and raw image sequences. Our dataset also contains object labels in the form of 3D tracklets, and we provide online benchmarks for stereo, optical flow, object detection and other tasks. This paper describes our recording platform, the data format and the utilities that we provide.

摘要： The article reports that Imperial College London has been awarded a grant for research in robotics by David Willets, British Minister for universities and science, from Engineering and Physical Sciences Research Council (EPSRC) funds.

关键词： 复合式越障机器人   Recurdyn   硬质路面   软性路面  

摘要： 基于研发可适应多种结构化及非结构化地形的移动机器人平台的需求,就复合式越障机器人动力学性能展开研究。首先在Recurdyn平台上建立了主从履带复合式越障机器人的虚拟样机,建立了其与平地硬质及软性地面的接触模型,并在这两种路面上进行行驶仿真。根据仿真结果,得到机器人平地前进的动力学数据,并对机器人的结构设计提出一定建议。

关键词： 机器人竞赛   中国科协   吉林省   青少年   党组副书记   长春市   一等奖   副主席  

摘要： 7月20日，为期4天的第十三届中国青少每：机器人竞赛在吉林省长春市闭幕。犬赛共决出一、二、三等奖共1461项，其中一等奖255项，二等奖481项，三等奖725项。中国科协副主席、党组副书记、

关键词： 全地面起重机   塔臂工况   回转运动   机器人动力学   吊重摆振特性  

摘要： 为了提高全地面起重机塔臂工况吊装定位精度及作业效率,有必要对回转运动中吊重摆振特性进行研究.基于机器人动力学理论,将全地面起重机等效成串联开链机器人系统,运用牛顿-欧拉正向递推公式,建立吊重摆振动力学方程,对吊重摆振特性进行计算机仿真.研究结果表明回转过程产生的惯性力和离心力导致吊重在空间产生复杂的振动,启动加速时间、吊重绳长及工作幅度对吊重偏摆角大小有重要影响.所得结论可为全地面起重机结构设计提供参考.

关键词： 机器人   动力学   B&R控制器   Lagrange方程   参数辩识  

摘要： 利用B&R控制器良好的实时特性和它的AS软件平台,获得机器人关节实时位置q(t)、速度q觶(t)、加速度q(t)以及力矩数据,完成机器人静态参数辩识,得到精确的机器人系统数学模型。有了数学模型以及机器人轨迹规划器输出的位置、速度、加速度参数,利用机器人动力学方程基本方程,就可以规划出机器人运动的各轴力矩,从而实现机器人力矩前馈控制,保证机器人具有良好的动态性能。