关键词： Aerodynamics   Satellites   Numerical models   Robots   Space vehicles   Aerospace electronics  

摘要： Maneuverable tethered space net robot (TSNR) is promising for active debris removal due to its flexibility and controllability. However, the contact dynamics of TSNR is not completely understood. Therefore, the contact dynamics is analyzed and the net does not close completely after contact. A super-twisting sliding mode control scheme is designed to make the net completely closed and avoid the risk of tether cut. The efficacy of the controller is validated by simulation results.

关键词： action representations   robotics   taxonomy  

摘要： Understanding and defining the meaning of "action" is substantial for robotics research. This becomes utterly evident when aiming at equipping autonomous robots with robust manipulation skills for action execution. Unfortunately, to this day we still lack both a clear understanding of the concept of an action and a set of established criteria that ultimately characterize an action. In this survey, we thus first review existing ideas and theories on the notion and meaning of action. Subsequently, we discuss the role of action in robotics and attempt to give a seminal definition of action in accordance with its use in robotics research. Given this definition we then introduce a taxonomy for categorizing action representations in robotics along various dimensions. Finally, we provide a meticulous literature survey on action representations in robotics where we categorize relevant literature along our taxonomy. After discussing the current state of the art we conclude with an outlook towards promising research directions.

关键词： Rehabilitation robotic devices   end-effector   exoskeleton   hand rehabilitation  

摘要： This article aims to give an overall review of research status in hand rehabilitation robotic technology, evaluating a number of devices. The main scope is to explore the current state of art to help and support designers and clinicians make better choices among varied devices and components. The review also focuses on both mechanical design, usability and training paradigms since these parts are interconnected for an effective hand recovery. In order to study the rehabilitation robotic technology status, the devices have been divided in two categories: end-effector robots and exoskeleton devices. The end-effector robots are more flexible than exoskeleton devices in fitting the different size of hands, reducing the setup time and increasing the usability for new patients. They suffer from the control of distal joints and haptic aspects of object manipulation. In this way, exoskeleton devices may represent a new opportunity. Nevertheless their design is complex and a deep investigation of hand biomechanics and physical human-robot interaction is required. The main hand exoskeletons have been developed in the last decade and the results are promising demonstrated by the growth of the commercialized devices. Finally, a discussion on the complexity to define which design is better and more effective than the other one is summarized for future investigations.

摘要： The article offers information on the role of the robotics and navigation in orthopaedics. Topics discussed include the goal of machine-assisted surgery regarding preventing errors and improving accuracy and precision; research on machine-assistance for orthopaedic tumor resection and reconstruction, orthopaedic trauma and spine instrumentation; and considering machine-assistance as a training tool.

关键词： Swarm robotics   Multi-target search   Swarm intelligence optimization   Deep learning   Evolutionary algorithm   Strategy imitation  

摘要： As a distributed system with a large number of individuals, swarm robotics is particularly suitable for multi-target search problems. Most existing work is about strategic design while this article focuses on strategy imitation. Sometimes we can observe the behavior of individuals and obtain a large amount of data, but we do not know the specific details of the strategy behind the behavior. Imitating the self-organizing behavior of organisms is of great significance for us to design efficient swarm strategies and to reveal the underlying mechanisms. The actual strategy adopted by individuals can be called the target strategy, and in this article, a two-stage imitation learning framework is proposed to approach the target strategy. In the first stage, a deep neural network is trained using the behavioral data of individuals, and in the second stage, the parameters of the neural network are further fine-tuned using the evolutionary algorithm. After two stages of learning and evolution, the resulting strategy RNSE is very close to the target strategy in terms of multiple indicators, including search efficiency, stability, parallel processing capability, and collaborative processing capability. In addition to multi-target search, the framework can also be used for other collective tasks such as aggregation and dispersion. In this paper, the design of neural networks and the settings of the evolutionary algorithm are discussed in detail, which is of great significance for the migration application of the framework. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Mechanical engineering   Software  

摘要： Biological organisms achieve robust high-level behaviours by combining and coordinating stochastic low-level components(1-3). By contrast, most current robotic systems comprise either monolithic mechanisms(4,5) or modular units with coordinated motions(6,7). Such robots require explicit control of individual components to perform specific functions, and the failure of one component typically renders the entire robot inoperable. Here we demonstrate a robotic system whose overall behaviour can be successfully controlled by exploiting statistical mechanics phenomena. We achieve this by incorporating many loosely coupled 'particles', which are incapable of independent locomotion and do not possess individual identity or addressable position. In the proposed system, each particle is permitted to perform only uniform volumetric oscillations that are phase-modulated by a global signal. Despite the stochastic motion of the robot and lack of direct control of its individual components, we demonstrate physical robots composed of up to two dozen particles and simulated robots with up to 100,000 particles capable of robust locomotion, object transport and phototaxis (movement towards a light stimulus). Locomotion is maintained even when 20 per cent of the particles malfunction. These findings indicate that stochastic systems may offer an alternative approach to more complex and exacting robots via large-scale robust amorphous robotic systems that exhibit deterministic behaviour.

关键词： graphene   wrinkle and crumple structures   strain-insensitive electrodes   stretchable pressure sensors   surgical robotics  

摘要： Stretchable skin-like pressure sensing with minimized and distinguishable strain-induced interference is essential for the development of collision-aware surgical robotics to improve the safety and efficiency of minimally invasive surgery in a confined space. Inspired by the multidimensional wrinkles of Shar-Pei dog's skin for tactile sensing, we developed a stretchable pressure sensor consisting of reduced graphene oxide (rGO) electrodes with biomimetic topographies to improve the robot-tissue collision detections. A facile fabrication route for stretchable rGO electrodes was first demonstrated by harnessing the surface instability during the sequential deformation processes. The wrinkle-crumple rGO electrodes exhibited high stretchability (similar to 100%) and strain-insensitive resistance profiles [a gauge factor (GF) < 0.05], which were next utilized to fabricate piezoresistive pressure sensors. The rGO pressure sensors were highly stretchable and exhibited high sensitivity under uniaxial strains (1.37, 1.30, and 0.98 kPa(-1) at 0, 30, and 50% stretching states, respectively) along with distinguishable and reduced stretching responsiveness (a small GF similar to 0.2 under 40% strains). The stretchable pressure sensors were next integrated with two surgical robots for the transoral robotic surgery procedure. During the cadaveric testing, the rGO sensors can detect the robot-tissue contacts under joint stretches in real time to enhance the surgeon's awareness for collision avoidance. The stretchable rGO pressure sensor that is highly sensitive under large strains provides great potential in the fields of wearable sensing and collision aware humanoid robots to improve the human-machine interactions.

关键词： Co-simulation   kinematics   multi-software platform   rigid-flexible coupling dynamics   3-revolute-prismatic-sphericalparallel robot  

摘要： Kinematics and dynamics are the most important and basic tool for robot research. With the help of computer technology and the respective advantages of three kinds of software, a new method of co-simulation of parallel robot based on multi-platform is proposed, and the mechanical model of multi-body system of 3-revolute-prismatic-spherical parallel robot is established. According to the mechanical analysis of the parallel robot, the rigid-flexible coupling analysis method is adopted. The displacement error shows a periodic change with a period of 4.2 s and the maximum error is 2x10-4m. The dangerous part of the structure is the root of the lower link, and its maximum stress is 202.64 MPa less than the yield strength of the material. The multi-software platform co-simulation improves the accuracy of the dynamic response analysis of the part under dynamic load, and provides an important theoretical basis for the design and optimization of the parallel robot.

关键词： differentiable physics engine   deep learning   gradient descent   neural network controller   robotics  

摘要： An important field in robotics is the optimization of controllers. Currently, robots are often treated as a black box in this optimization process, which is the reason why derivative-free optimization methods such as evolutionary algorithms or reinforcement learning are omnipresent. When gradient-based methods are used, models are kept small or rely on finite difference approximations for the Jacobian. This method quickly grows expensive with increasing numbers of parameters, such as found in deep learning. We propose the implementation of a modern physics engine, which can differentiate control parameters. This engine is implemented for both CPU and GPU. Firstly, this paper shows how such an engine speeds up the optimization process, even for small problems. Furthermore, it explains why this is an alternative approach to deep Q-learning, for using deep learning in robotics. Finally, we argue that this is a big step for deep learning in robotics, as it opens up new possibilities to optimize robots, both in hardware and software.

关键词： 机器人竞赛教学   实践创新   能力培养  

摘要： 中学生机器人竞赛教学是信息技术教学的重要亮点,对于调动中学生参与研制人工智能的兴趣,提高中学生信息技术水平具有重要意义。机器人竞赛教学的课堂实践重点培养了中学生动手组装机器人的实践能力,强化了中学生在机器人制作与控制实践中的探究创新意识,提升了中学生群策群力解决问题的团队合作精神,这三大能力是中学生素质教育要求的集中体现。