关键词： 轮式移动机器人   模型预测控制   神经动力学   跟踪   稳定性  

摘要： 为了对轮式移动机器人(WMR)进行光滑、鲁棒、稳定的轨迹跟踪控制,分析了生物激励神经动力学原理,研究了非线性模型预测控制策略,提出了一种基于神经动力学思想的模型预测终端控制方法。首先,针对传统控制方法存在的初始速度跳变问题,利用神经动力学在信息处理方面的优良特性,设计了神经动力学控制模块;然后,根据模型预测控制原理给出了一个优化控制模块;最后,设计了终端域和线性反馈终端控制器来保证系统的全局渐近稳定性。仿真结果表明:利用所设计的控制方法进行曲线跟踪时,被控WMR系统收敛到参考轨迹的时间可从12s降到5s,初始线速度/角速度分别从[-3,4]m/s和[-5,6]rad/s缩小到[0,2]m/s和[-3,3]rad/s,且系统输出有界光滑,使WMR在完成轨迹跟踪的同时实现了全局渐进稳定。由于文中核心算法的推导过程不受WMR运动学模型限制,故该研究结论亦可应用于其他结构的移动机器人。

关键词： 计算智能   图像处理   电力系统   自动化控制   数学工具   信号处理   机器人学   模糊系统  

摘要： 基于计算智能的技术作为可行的、数学工具已经有超过十年的时间，它们广泛地应用于许多系统和领域，诸如：信号处理、自动化控制、机器人学、电力系统等。图像处理也吸引了众多对基于计算智能的技术应用感兴趣的研究者，是一个很受关注的研究问题及现实问题。最初，大部分的研究工作，主要集中在发展常规模糊系统、

关键词： 关节型机器人   惯量参数   参数辨识   连接组合体法  

摘要： 为获得不受负载影响的机器人动力学参数的独立值,采用连接组合体方法辨识机器人动力学参数,即辨识时按照一定的方式及次序锁定其他关节,每次仅让某几个关节运动,从而辨识出全部参数的独立值。编写了机器人动力学参数辨识程序,对某确定工业机器人进行了动力学参数辨识计算。结果表明:该方法能够获得独立的机器人动力学参数;绝大多数参数能够获得理想的辨识精度;受噪声影响,部分参数辨识结果与理想值差距较大,原因在于这些参数对力矩的贡献很小,在噪声存在的情况下,其信息被淹没;基于辨识结果的力矩计算结果与机器人控制理想力矩具有很高的吻合度,验证了该方法的正确性。

关键词： Robotics   Laparoscopy   Sacrocolpopexy   Prolapse   Vagina   Pelvic prolapse surgery  

摘要： Pelvic organ prolapse is a common condition affecting a significant number of women in the United States. There are currently three restorative abdominal surgical approaches for pelvic organ prolapse, including open, laparoscopic, and robotic sacrocolpopexy. Robotic sacrocolpopexy has been on the rise since its advent in 2004. Robotic surgery is a new and exciting technology that currently demonstrates long and short-term outcome equivalence with other abdominal approaches to sacrocolpopexy, as well as great potential for future improvements.

摘要： The article evaluates the SR-48 robotic collision sensor from ATI Industrial Automation.

关键词： Human-robot social interaction   Non-verbal communication   Experienced engagement   Robotics knowledge  

摘要： Communication between socially assistive robots and humans might be facilitated by intuitively understandable mechanisms. To investigate the effects of some key nonverbal gestures on a human's own engagement and robot engagement experienced by humans, participants read a series of instructions to a robot that responded with nods, blinks, changes in gaze direction, or a combination of these. Unbeknown to the participants, the robot had no form of speech processing or gesture recognition, but simply measured speech volume levels, responding with gestures whenever a lull in sound was detected. As measured by visual analogue scales, engagement of participants was not differentially affected by the different responses of the robot. However, their perception of the robot's engagement in the task, its likability and its understanding of the instructions depended on the gesture presented, with nodding being the most effective response. Participants who self-reported greater robotics knowledge reported higher overall engagement and greater success at developing a relationship with the robot. However, self-reported robotics knowledge did not differentially affect the impact of robot gestures. This suggests that greater familiarity with robotics may help to maximise positive experiences for humans involved in human robot interactions without affecting the impact of the type of signal sent by the robot. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Concurrent design   multidisciplinary systems   mechatronics   robot manipulator   fuzzy logic  

摘要： This article details a holistic concurrent design framework, based on fuzzy logic, which is suitable for multidisciplinary systems. The methodology attempts to enhance communication and collaboration between different disciplines through introducing the universal notion of satisfaction and expressing the holistic behavior of multidisciplinary systems using the notion of energy. Throughout the design process, it uses fuzzy logic to formalize subjective aspects of design including the impact of the designer's attitude, resulting in the simplification of the multi-objective constrained optimization process. In the final phase, the methodology adjusts the designer's subjective attitude based on a holistic system performance by utilizing an energy-based model of multidisciplinary systems. The efficiency of the resulting design framework is illustrated by improving the design of a 5-degree-of-freedom industrial robot manipulator.

关键词： Adaptive learning   Cognitive robotics   Evolutionary computation   Dynamic problems  

摘要： Brain-like robotic approaches aim to reproduce the complex processes occurring within the biological brains to achieve a higher level of autonomy. One of the key aspects of these approaches is dynamic learning, that is, how to provide the cognitive architectures that control de robot with adaptive learning capabilities. Several options have been considered in this line in the field of Cognitive Robotics, although the development of a proper memory system has provided the best practical results up to now. This work also follows this approach, seeking to show the advantages of using a Long-Term Memory (LTM) for optimizing the adaptive learning capabilities of a cognitive robot in dynamic environments. Specifically, a procedural LTM that stores basic models and behaviours is included in the evolutionary-based Multilevel Darwinist Brain (MDB) cognitive architecture. The LTM management system that has been developed to control when a model must be stored or replaced is presented here in detail. Moreover, a ShortTerm Memory (STM) sub-system included in the MDB is also explained due to its strong relationship with the operation of the LTM. The LTM elements are tested in theoretical functions and in a simulated example using the AIBO robot in a dynamic context with successful adaptive learning results.

关键词： Image-guided intervention   Minimally invasive surgery   Neurosurgery   Robotic surgery  

摘要： BACKGROUND: Over the past decade, advances in image guidance, endoscopy, and tube-shaft instruments have allowed for the further development of keyhole transcranial endoscope-assisted microsurgery, utilizing smaller craniotomies and minimizing exposure and manipulation of unaffected brain tissue. Although such approaches offer the possibility of shorter operating times, reduced morbidity and mortality, and improved long-term outcomes, the technical skills required to perform such surgery are inevitably greater than for traditional open surgical techniques, and they have not been widely adopted by neurosurgeons. Surgical robotics, which has the ability to improve visualization and increase dexterity, therefore has the potential to enhance surgical performance. OBJECTIVE: To evaluate the role of surgical robots in keyhole transcranial endoscope-assisted microsurgery. METHODS: The technical challenges faced by surgeons utilizing keyhole craniotomies were reviewed, and a thorough appraisal of presently available robotic systems was performed. RESULTS: Surgical robotic systems have the potential to incorporate advances in augmented reality, stereoendoscopy, and jointed-wrist instruments, and therefore to significantly impact the field of keyhole neurosurgery. To date, over 30 robotic systems have been applied to neurosurgical procedures. The vast majority of these robots are best described as supervisory controlled, and are designed for stereotactic or image-guided surgery. Few telesurgical robots are suitable for keyhole neurosurgical approaches, and none are in widespread clinical use in the field. CONCLUSION: New robotic platforms in minimally invasive neurosurgery must possess clear and unambiguous advantages over conventional approaches if they are to achieve significant clinical penetration.