关键词： 仿生机器人   北京航空航天大学   《科学》杂志   应用   壁虎   水下   机器人学   国际合作  

摘要： 近日,国际顶级期刊《科学》杂志机器人子刊《科学·机器人学》以长篇封面刊登北航文力课题组牵头、与哈佛大学合作的科研团队最新研究成果——仿生？鱼软体吸盘机器人。北京航空航天大学文力副教授牵头的国际合作团队,近日揭示了？鱼软体吸盘的仿生学原理并首次制作出仿生机器人样机。据文力介绍,？鱼可以在游动中通过头部的吸盘完成对鲨鱼、海豚、海龟等不同海洋生物的快速吸附。

关键词： Multidimensional-Multiscale   Feature-histograms   Laplacian feature   Histogram pyramid   Histogram Taylor series   Reduced complexity   Multidimensional indexing   Training-less object recognition  

摘要： This paper looks at the challenge of object recognition from the perspective of achieving the final goals of practical real-world autonomous robot-vision applications;that of identifying a target of interest in the robot's field of view and properly localizing its position in preparation for the higher-level goal of tracking and navigation. A unified framework is introduced that combines a multidimensional feature histogram approach with a multiscale pyramid approach for training-less color object recognition and localization, with direct application to autonomous robotic agents. This framework addresses the high computational cost associated with multidimensional processing by deriving the Multidimensional "Laplacian Feature Histogram Pyramid", a novel approach to a unified multidimensional-multiscale histogram representation. Furthermore, a Taylor series formulation is employed to combine the multiscale levels of the multidimensional Laplacian feature histogram pyramid into one efficient multidimensional-multiscale "Laplacian-Taylor Feature Histogram" for rapid object recognition and localization. The paper describes the criteria for target detection and localization by autonomous robots and how this newly developed framework fits these needs. Comparative results demonstrate the robustness of this recognition framework to noise and localization of target objects in cluttered scenes. (C) 2017 Elsevier Inc. All rights reserved.

关键词： Elastic Modulus   elastic bodies   Classes of materials   Fluid drives   Materials   Soft Robotics   Manufacturing costs   Fluid   Robot  

摘要： The emerging field of soft robotics makes use of many classes of materials including metals, low glass transition temperature (Tg) plastics, and high Tg elastomers. Dependent on the specific design, all of these materials may result in extrinsically soft robots. Organic elastomers, however, have elastic moduli ranging from tens of megapascals down to kilopascals;robots composed of such materials are intrinsically soft - they are always compliant independent of their shape. This class of soft machines has been used to reduce control complexity and manufacturing cost of robots, while enabling sophisticated and novel functionalities often in direct contact with humans. This review focuses on a particular type of intrinsically soft, elastomeric robot - those powered via fluidic pressurization.

关键词： Robotics  

摘要： Reports on the RAS 2017 Humanitarian Robotics and Automation Technology Challenge.

关键词： Micro aerial vehicle   Insect-scale vehicle   Hovering flight   Stability   Nonlinear dynamics   Limit cycle  

摘要： Most hovering aircraft such as helicopters and animal-inspired flapping-wing flyers are dynamically unstable in flight, quickly tumbling in the absence of feedback control. The addition of feedback loops can stabilize, but at the cost of additional sensing and actuation components. This can add expense, weight, and complexity. An alternative to feedback is the use of passive mechanisms such as aerodynamic drag to stabilize attitude. Previous work has suggested that small aircraft can be stabilized by adding air dampers above and below the center of mass. We present flight tests of an insect-scale robot operating under this principle. When controlled to a constant altitude, it remains stably upright while undergoing cyclic attitude oscillations. To characterize these oscillations, we present a nonlinear analytic model derived from first principles that reproduces the observed behavior. Using numerical simulation, we analyze how changing damper size, position, mass, and midpoint offset affect these oscillations, building on previous work that considered only a single configuration. Our results indicate that only by increasing damper size can lateral oscillation amplitude be significantly reduced, at the cost of increased damper mass. Additionally, we show that as scale diminishes, the damper size must get relatively larger. This suggests that smaller damper-equipped robots must operate in low-wind areas or in boundary-layer flow near surfaces.

关键词： trajectory segmentation   surgical robotics   robot learning  

摘要： Demonstration trajectories collected from a supervisor in teleoperation are widely used for robot learning, and temporally segmenting the trajectories into shorter, less-variable segments can improve the efficiency and reliability of learning algorithms. Trajectory segmentation algorithms can be sensitive to noise, spurious motions, and temporal variation. We present a new unsupervised segmentation algorithm, transition state clustering (TSC), which leverages repeated demonstrations of a task by clustering segment endpoints across demonstrations. TSC complements any motion-based segmentation algorithm by identifying candidate transitions, clustering them by kinematic similarity, and then correlating the kinematic clusters with available sensory and temporal features. TSC uses a hierarchical Dirichlet process Gaussian mixture model to avoid selecting the number of segments a priori. We present simulated results to suggest that TSC significantly reduces the number of false-positive segments in dynamical systems observed with noise as compared with seven probabilistic and non-probabilistic segmentation algorithms. We additionally compare algorithms that use piecewise linear segment models, and find that TSC recovers segments of a generated piecewise linear trajectory with greater accuracy in the presence of process and observation noise. At the maximum noise level, TSC recovers the ground truth 49% more accurately than alternatives. Furthermore, TSC runs 100x faster than the next most accurate alternative autoregressive models, which require expensive Markov chain Monte Carlo (MCMC)-based inference. We also evaluated TSC on 67 recordings of surgical needle passing and suturing. We supplemented the kinematic recordings with manually annotated visual features that denote grasp and penetration conditions. On this dataset, TSC finds 83% of needle passing transitions and 73% of the suturing transitions annotated by human experts.

关键词： mobile robot   STEM education   robot competition  

摘要： The purpose of our education approach is the giving the knowledge and the experience for the research activity to the freshman student who assigned the Lab. We think that "the interaction between the robot and the real world information which is observed by sensor" is important for the student education for student's research in the Lab. Here, the interaction means how perform the robot based on the real world information which is observed by sensors. The development of the mobile robot which work in Robot competition (Tsukuba Challenge) requires "the interaction between the mobile robot and real world." For this reason, we think that this activity (participating in the Tsukuba Challenge anf development of the mobile robot) is effective for the student education, and we educate the student by utilizing the development of the mobile robot for Tsukuba Challenge. Although our approach performed in short span, we achieve the good result. For example, the students achieves the research outcome by utilizing the learned skill, and submitted the paper to the academic conference. We verified that our education approach is effective for improvement the student education and motivation.

摘要： In the last years, simple service robots such as autonomous vacuum clean- ers and lawn mowers have become commercially available and increasingly common. The next generation of service robots should perform more ad- vanced tasks, such as to clean up objects. Robots then need to learn to robustly navigate, and manipulate, cluttered environments, such as an un- tidy living room. In this thesis, we focus on representations for tasks such as general cleaning and fetching of objects. We discuss requirements for these specific tasks, and argue that solving them would be generally useful, because of their object-centric nature. We rely on two fundamental insights in our approach to understand envi- ronments on a fine-grained level. First, many of today's robot map represen- tations are limited to the spatial domain, and ignore that there is a time axis that constrains how much an environment may change during a given period. We argue that it is of critical importance to also consider the temporal do- main. By studying the motion of individual objects, we can enable tasks such as general cleaning and object fetching. The second insight comes from that mobile robots are becoming more ro- bust, enabling month-long operations in one single indoor environment. They can therefore collect large amounts of data from those environments. With more data, unsupervised learning of models becomes feasible, allowing the robot to adapt to changes in the environment, and to scenarios that the de- signer could not foresee. We view these capabilities as vital for robots to become truly autonomous. The combination of unsupervised learning and dynamics modelling creates an interesting symbiosis: the dynamics vary be- tween different environments and between the objects in one environment, and learning can capture these variations. A major difficulty when modeling environment dynamics is that the whole environment can not be observed at one time, since the robot is moving between different plac

关键词： Switched reluctance machine (SRM)   Cloud robotics   Network latency   Package loss   Predictive control  

摘要： Cloud robotics has undergone rapid development. As an important candidate for direct-drive manipulator, switched reluctance machines (SRMs) face significant challenge in terms of control used in cloud robotics because of latency and package losses in network communication. In this paper, predictive current control of SRMs is extended to use in controller upon cloud in the face of latency and package losses. The starting point of predictive model is modified to eliminate errors caused by latency in sensor-controller communication, and the execution of control command sequence is dynamically regulated according to the arrival time of the following sequence to adapt for latency and package losses in controller-actuator communication. The proposed control method is evaluated in a 1.5 kW SRM test platform and comparison with a conventional control method is performed;the results show that the proposed control method has better tracking performance in face of time delay and package losses in transmission.

摘要： Presents information on various RAS Society chapters.