关键词： 虚拟实验室   机器人学   坐标变换   Qt   Ogre3D  

摘要： 为满足机器人学学习过程中的实验需求,描述了一个基于Qt和Ogre3D机器人学坐标变换虚拟实验室的设计和使用。本虚拟实验室针对机器人学的坐标变换,在虚拟环境中通过实验来表明欧拉角、RPY角、转轴/角度、单位四元数和齐次变换矩阵的关系,并且使用虚拟手段阐述了DH矩阵的空间意义,通过数值计算和虚拟显示详细地解释这些概念的意义。其描述了这些虚拟实验的使用方法。为了判断此虚拟实验室的有效性,设计了一个教学实验,实验的结果表明虚拟实验可使教学过程更加合理,证明虚拟实验室在未来机器人学教学中将会扮演重要的角色。

关键词： 下肢外骨骼康复机器人   动力学   ADAMS仿真  

摘要： 下肢外骨骼康复机器人动力学模型的准确建立,是实现机器人精确控制的前提条件。文中将下肢外骨骼机器人简化为7杆模型,并将下肢运动周期划分为单腿支撑和双腿支撑两个阶段,采用拉格朗日方法建立外骨骼康复机器人系统的整体动力学模型。通过人体下肢运动的实时动作捕捉及其运动轨迹的数据分析,得到人体正常行走时的关节运动规律,推导出各个关节所需的驱动力矩。利用SolidWorks建立机器人三维简化模型并导入ADAMS软件进行动力学仿真,验证了理论推导的准确性,为机器人电机的选型和控制系统的设计提供了理论依据。

关键词： 机器人学   科幻小说   科普   人工智能   高水   教育教学   高新技术   智能控制  

摘要： 2018年3月,蔡自兴教授与夫人翁环合著完成长篇机器人学小说《探秘机器人王国》(约20万字),该书是一部以机器人学、人工智能知识和机器人技术为中心内容的科普与科幻小说,书中通过形象与连续的故事和插图,介绍机器人的发展历史、基本结构与分类,在工矿业与农林业、空间与海洋探索、国防与安保、医疗卫生、家庭服务、文化娱乐、教育教学等方面的应用,以及智能化工厂、未来宇宙开发与星际航行和发展方向等。此外,本书也展望了其他一些新技术或潜在高新技术的未来应用。我国著名机器人技术专家蔡鹤皋院士特为此书撰写书评,在该书的前言中,作者对本刊同仁给予的支持与帮助亦表示感谢。蔡自兴,中南大学教授,国际导航与运动控制科学院院士、纽约科学院院士、美国电气与电子工程师学会院士(IEEE Fellow),是我国智能控制、人工智能、机器人学诸多学科的学术带头人之一,被誉为"中国智能控制的奠基者"和"中国人工智能教学第一人"。

关键词： 滑动   轨迹跟踪   动力学模型   机器人  

摘要： 针对三轮全向移动机器人在运动过程中产生的滑动现象,提出一种基于滑动动力学模型的轨迹跟踪控制方法。在三轮全向移动机器人运动学以及动力学建模的基础上,通过分析轮毂滚动方向和滚子滚动方向上的车轮接触摩擦力,提出了一种滑动动力学模型,并将该模型引入三轮全向移动机器人闭环运动控制系统,以提高其轨迹跟踪控制精度。在Matlab/Simulink平台上进行轨迹跟踪控制仿真。结果表明,基于滑动动力学模型的三轮全向移动机器人运动控制系统具有较好的稳定性和准确性。

关键词： pedicle screws   robotics   spine surgery  

摘要： Although it is impossible to predict the future, we can learn from trends of the past, and from the activities of our surgical colleagues. Spine robotics has been available in the United States since 2004 with the Mazor SpineAssist system (Mazor Robotics, Caesarea, Israel). SpineAssist did not, however, see significant use until 2011 with a handful of installations, to still under 100 installed by 2015. The number of procedures per system has increased steadily, however, implying greater utilization and acceptance of spine robots in the operating room (OR), and by 2015, over 3000 procedures were performed annually in the United States. Perhaps this trend will mimic the Intuitive Surgical robot (Intuitive Surgical, Inc., Sunnyvale, CA) used for prostate and ob-gyn surgeries, with 700,000 procedures executed in 2015. It is also likely that both market and training trends will push medical systems towards the use of robotics in spine surgery. Already, there is a push for commoditization of spinal procedures, with the expectation of more complex procedures to be performed by more spine surgeons in more varied hospital settings. In parallel, residency work hour restrictions provide less and less opportunity for indepth spine procedural training. Thus, less-trained spine surgeons are expected to do more and more, especially in physician-based settings. Robotics could allow for increased safety even with increased complexity of surgery, bringing such cases into the capability of less experienced surgeons. The robotics industry is expected to increase from $4 billion in 2016 to $6.8 billion in 2021, and spine surgery robotics will likely follow that growth rate. Currently, spine robots simply act as guides to help position tools in an ideal position or trajectory. This allows for accurate placement of pedicle screws; however, tremendous opportunity exists for the future. Examples might include the use of robots that are passive but provide "no-fly zones" around protected

关键词： Robotics   Robotic surgery   Robot-assisted surgery   Transoral robotic surgery (TORS)   Nipple-sparing mastectomy   Muscular flap   Latissimus dorsi flap   Rectus abdominis flap   Microsurgery   supermicrosurgery  

摘要： Robot-assisted surgery is more and more widely used in urology, general surgery and gynecological surgery. The interest of robotics in plastic and reconstructive surgery, a discipline that operates primarily on surfaces, has yet to be conclusively proved. However, the initial applications of robotic surgery in plastic and reconstructive surgery have been emerging in a number of fields including transoral reconstruction of posterior oropharyngeal defects, nipplesparing mastectomy with immediate breast reconstruction, microsurgery, muscle harvesting for pelvic reconstruction and coverage of the scalp or the extremities. (C) 2018 Elsevier Masson SAS. All rights reserved.

关键词： Industrial robots   Motion control devices   Manufacturing process automation   Decision making   Design for reuse (Electronics)   Installation of equipment  

摘要： The article presents 10 questions to consider by organizations before deciding to install robotics or motion control devices to their business operations. Topics include the need to determine if a box-like or cylinder-like robots can fit the work area, the compliance of robotics or motion control devices to multiple projects with different mechanical requirements, and the reuse and repurpose of the equipment.

关键词： Robotics   Locomotion   Physical model   Biomimetics   Mechanical device  

摘要： For centuries, designers and engineers have looked to biology for inspiration. Biologically inspired robots are just one example of the application of knowledge of the natural world to engineering problems. However, recent work by biologists and interdisciplinary teams have flipped this approach, using robots and physical models to set the course for experiments on biological systems and to generate new hypotheses for biological research. We call this approach robotics-inspired biology;it involves performing experiments on robotic systems aimed at the discovery of new biological phenomena or generation of new hypotheses about how organisms function that can then be tested on living organisms. This new and exciting direction has emerged from the extensive use of physical models by biologists and is already making significant advances in the areas of biomechanics, locomotion, neuromechanics and sensorimotor control. Here, we provide an introduction and overview of robotics-inspired biology, describe two case studies and suggest several directions for the future of this exciting new research area.

关键词： Robotics   deep learning   machine learning   robotic vision  

摘要： The application of deep learning in robotics leads to very specific problems and research questions that are typically not addressed by the computer vision and machine learning communities. In this paper we discuss a number of robotics-specific learning, reasoning, and embodiment challenges for deep learning. We explain the need for better evaluation metrics, highlight the importance and unique challenges for deep robotic learning in simulation, and explore the spectrum between purely data-driven and model-driven approaches. We hope this paper provides a motivating overview of important research directions to overcome the current limitations, and helps to fulfill the promising potentials of deep learning in robotics.

关键词： Swarm robotics   Positioning   Model matching   Feature detection and description  

摘要： In this study, a positioning algorithm which is inspired by model matching type positioning systems is presented for swarm robotics. Unlike the conventional model matching systems, the system is designed to be operated as distributed. The algorithm consists of online and offline stages. While specific data collection and positioning are computed in the offline stage, specific data exchange is performed in the online stage. In the positioning algorithm to be used, a swarm robot system where each robot receives an image from a camera located under itself and where the robots share these images with each other and perform positioning is taken as a basis. The positions computed are the positions of the robots with respect to each other. Position estimation is based on feature detection and description from images. To determine the optimal positioning algorithm, performance comparison is performed among different combinations of feature detection and description algorithms. (C) 2016 Elsevier Ltd. All rights reserved.