关键词： Educational robotics   Robotics competitions   STEM education   Computational thinking   Engineering skills   21st century skills  

摘要： RoboCupJunior is an international educational robotics initiative, aiming to promote STEM content and skill learning among participating youth through educational robotics competition inaugurated in 2000. What makes RoboCupJunior quite unique is its relationship with RoboCup which aims to promote robotics and AI research, by offering a publicly appealing, but formidable challenge including development of soccer robots, search and rescue robots, and robots functions at home and at work. This paper introduces a case of RoboCupJunior and the effectiveness of its practice for enhancing learning of STEM contents and skills for innovation and creativity among participating students. It presents the survey results from one of the World Championships held in 2012, the anecdotal and personal account of participating US students on their learning experience from their participation in 2013 World Championship, and participating students' technological and innovative contributions to highlight the impacts RoboCupJunior has had through over a decade of its practice. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Robotics   Automation   In-pipe inspection robots   Tank inspection robots   NDT   UAV   Wireless sensor networks (WSN)   Oil and gas exploration  

摘要： With ever increasing global demand and depleting resources for fossil fuels, oil and gas industry is now positively looking for advanced robotic solutions to increase their productivity and safety. With time easy resources of the fossil fuels are shrinking and newly searched reservoirs, to feed supply demands of global consumption, are mostly located in extreme environmental conditions such as hot deserts, deep water and arctic zone etc. Production of the fossil fuels, in such inhospitable environmental conditions, poses difficult challenges to health, safety and environment (HSE). Tragic incidents like Exxon Valdez and Deepwater Horizon oil spills are examples of such challenges. Therefore, oil and gas industry has lot to learn from successful implementation of robotics and automation for dull, dirty and dangerous (3D) tasks of manufacturing industry. Most of the robotics technologies, currently used in the oil and gas industry, are mainly focused on inspection, maintenance and repair (IMR) of plant facilities with higher frequency and accuracy. Fundamental idea, involved in the automatization of these processes, is based on the principle of teleoperation with skilled operator. Automation of 3D tasks not only improves HSE standards but also lead to much needed economic efficiency by reducing production cycle, floor space and number of staff members required for continuous inspection and manipulation of plant facilities. Considering the risks involved in this industry usage of completely autonomous robots, first without achieving very high reliability, is still a far fetch choice. Therefore, semi-autonomous robots, where actions are performed by robots but cognitive decisions are still taken by skilled operator, is an excellent choice for this industry as a near future solution. In the onshore oil and gas industry robotic solutions are used both in upstream and downstream processes, such as site survey, drilling, production and transportation, mainly focused in the

关键词： Wheeled mobile robots   Formation control   Engineering education  

摘要： This paper describes the development of a motivating and innovative multi-robot formation control platform for laboratory experiments with mobile robots. The platform is composed of two components: a simulator and an environment to experiment with low cost wheeled mobile robots. The environment constitutes a ready to use test tool that provides to engineering students the opportunity to simulate and test many different formation and cooperation control strategies with a real system. Currently the platform is used in the Systems and Control Engineering Master program offered by the National University of Distance Education (UNED) and the Complutense University of Madrid (UCM) in Spain. The use of the platform exposes students to hands-on laboratory sessions, contributing to their development as engineers.

关键词： Robotics   Automation   Underwater manipulator   Underwater welding   Production structure   NDT   ROV   AUV   WSN   Oil spill  

摘要： Demands for oil and gas are increasing with urbanization and industrialization of the world's increasing population. Giant oil fields are declining in their production worldwide and this situation is creating need for search of new conventional and non-conventional fossil reserves. With steep depletion of major onshore and shallow-water-offshore oil fields new search of fossil fuel is moving towards deep-water and ultra-deep water offshore fields. Obviously new reserves are located in extreme, hostile and hard-to-reach environmental conditions. Exploration, development and production of oil from such difficult offshore fields have many serious challenges to health, safety and environment (HSE) therefore, require sophisticated technological innovations to support increasing energy demand. Biggest oil spill accidents in explosion of Deepwater Horizon offshore oil platform are burning example of such challenges which human society cannot risk to repeat. Therefore, development of advance drilling system, more accurate and intelligent inspection mechanism, faster responsive system in cases of unfortunate incidence and efficient damage control system is need of the safer future. Successful implementation of robotics, in space and manufacturing industry, is an critical example of how robotic assistance and automation is the only option for safe and cost-effective production of oil in foreseeable future. Teleoperation of unmanned drilling and production platforms, remote operated vehicles (ROVs), autonomous underwater vehicles (AUVs), under-water welding, welding robots for double hulled ships and under-water manipulator are such key robotic technologies which have facilitated smooth transition of offshore rigs from shallow waters to ultra-deep waters in modern time. Considering the sensitivity of product and difficulty of environment, most of these technologies fall under semi-autonomous category, where human operator is in loop for providing cognitive assistance to the ov

关键词： Convolutional neural networks   natural language processing   object retrieval   object detection  

摘要： We address the problem of retrieving and detecting objects based on open-vocabulary natural language queries: given a phrase describing a specific object, for example the corn flakes box, the task is to find the best match in a set of images containing candidate objects. When naming objects, humans tend to use natural language with rich semantics, including basic-level categories, fine-grained categories, and instance-level concepts such as brand names. Existing approaches to large-scale object recognition fail in this scenario, as they expect queries that map directly to a fixed set of pre-trained visual categories, for example ImageNet synset tags. We address this limitation by introducing a novel object retrieval method. Given a candidate object image, we first map it to a set of words that are likely to describe it, using several learned image-to-text projections. We also propose a method for handling open vocabularies, that is, words not contained in the training data. We then compare the natural language query to the sets of words predicted for each candidate and select the best match. Our method can combine category- and instance-level semantics in a common representation. We present extensive experimental results on several datasets using both instance-level and category-level matching and show that our approach can accurately retrieve objects based on extremely varied open-vocabulary queries. Furthermore, we show how to process queries referring to objects within scenes, using state-of-the-art adapted detectors. The source code of our approach will be publicly available together with pre-trained models at http://*** and could be directly used for robotics applications.

关键词： Computational thinking   Educational robotics   Secondary education   Skill development  

摘要： This work investigates the development of students' computational thinking (CT) skills in the context of educational robotics (ER) learning activity. The study employs an appropriate CT model for operationalising and exploring students' CT skills development in two different age groups (15 and 18 years old) and across gender. 164 students of different education levels (Junior high: 89;High vocational: 75) engaged in ER learning activities (2 hours per week, 11 weeks totally) and their CT skills were evaluated at different phases during the activity, using different modality (written and oral) assessment tools. The results suggest that: (a) students reach eventually the same level of CT skills development independent of their age and gender, (b) CT skills in most cases need time to fully develop (students' scores improve significantly towards the end of the activity), (c) age and gender relevant differences appear when analysing students' score in the various specific dimensions of the CT skills model, (d) the modality of the skill assessment instrument may have an impact on students' performance, (e) girls appear in many situations to need more training time to reach the same skill level compared to boys. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Learning curve   Robotic sacral colpopexy  

摘要： Study Objective: To determine the learning curve of the following segments of a robotic sacral colpopexy: preoperative setup, operative time, postoperative transition, and room turnover. Design: A retrospective cohort study to determine the number of cases needed to reach points of efficiency in the various segments of a robotic sacral colpopexy (Canadian Task Force II-2). Setting: A university-affiliated community hospital. Patients: Women who underwent robotic sacral colpopexy at our institution from 2009 to 2013 comprise the study population. Interventions: Patient characteristics and operative reports were extracted from a patient database that has been maintained since the inception of the robotics program at Winthrop University Hospital and electronic medical records. Based on additional procedures performed, 4 groups of patients were created (A-D). Measurements and Main Results: Learning curves for each of the segment times of interest were created using penalized basis spline (B-spline) regression. Operative time was further analyzed using an inverse curve and sequential grouping. A total of 176 patients were eligible. Nonparametric tests detected no difference in procedure times between the 4 groups (A-D) of patients. The preoperative and postoperative points of efficiency were 108 and 118 cases, respectively. The operative points of proficiency and efficiency were 25 and 36 cases, respectively. Operative time was further analyzed using an inverse curve that revealed that after 11 cases the surgeon had reached 90% of the learning plateau. Sequential grouping revealed no significant improvement in operative time after 60 cases. Turnover time could not be assessed because of incomplete data. Conclusions: There is a difference in the operative time learning curve for robotic sacral colpopexy depending on the statistical analysis used. The learning curve of the operative segment showed an improvement in operative time between 25 and 36 cases when using B-spline

摘要： Background: To report our initial experience and highlight the value of using intraoperative C-arm cone beam computed tomography (CT;DynaCT (R)) image fusion guidance along with steerable robotic endovascular catheter navigation to optimize vessel cannulation. Methods: Between May 2013 and January 2015, all patients who underwent endovascular procedures using DynaCT image fusion technique along with Hansen Magellan vascular robotic catheter were included in this study. As a part of preoperative planning, relevant vessel landmarks were electronically marked in contrast-enhanced multi-slice computed tomography images and stored. At the beginning of procedure, an intraoperative noncontrast C-arm cone beam CT (syngo DynaCT (R), Siemens Medical Solutions USA Inc.) was acquired in the hybrid suite. Preoperative images were then coregistered to intraoperative DynaCT images using aortic wall calcifications and bone landmarks. Stored landmarks were then overlaid on 2-dimensional (2D) live fluoroscopic images as virtual markers that are updated in real-time with C-arm, table movements and image zoom. Vascular access and robotic catheter (Magellan (R), Hansen Medical) was setup per standard. Vessel cannulation was performed based on electronic virtual markers on live fluoroscopy using robotic catheter. The impact of 3-dimensional (3D) image fusion guidance on robotic vessel cannulation was evaluated retrospectively, by assessing quantitative parameters like number of angiograms acquired before vessel cannulation and qualitative parameters like accuracy of vessel ostium and centerline markers. Results: All 17 vessels were cannulated successfully in 14 patients' attempted using robotic catheter and image fusion guidance. Median vessel diameter at origin was 5.4 mm (range, 2.3-13 mm), whereas 12 of 17 (70.6%) vessels had either calcified and/or stenosed origin from parent vessel. Nine of 17 vessels (52.9 %) were cannulated without any contrast injection. Median number of angiogra

关键词： 机器人学   人工智能   第二定律  

摘要： 不管你心情如何,我们终究经历了人类历史上又一个决战时刻——谷歌AI机器人(Alpha Go)vs围棋世界冠军李世石。这不是简单的科技圈PK围棋界,而是人工智能vs人类智能的巅峰对决。围棋人机大战,机器已经赢了,人类已经输了。有的人欢呼,有的人沮丧,有的人庆幸,有的人恐慌……心情各有不同,但所有人都需要面临一个共同的问题:未来,人类与机器究竟是什么关系?

摘要： Trajectory following is one of the complicated control problems because its dynamics are nonlinear, stochastic and includes large number of parameters. The problem has major difficulties including large number of trials required for data collection, and huge volume of computations required to find a closed-loop controller for high dimensional and stochastic domains. For solving this type of problems, if we have an appropriate reward function and dynamics model, finding an optimal control policy is possible by using model-based reinforcement learning and optimal control algorithms. As defining an accurate dynamics is not possible for complicated problems, Pieter Abbeel and & Andrew Ng recently presented an algorithm that requires only an approximate model, and only a small number of real-life trials. This algorithm has wide applicability, however there are some problems regarding to convergence of the algorithm. In this research required modifications are presented that provide more powerful assurance for converging to an optimal control policy. Also updated algorithm implemented to evaluate the efficiency of the new algorithm by comparing the acquired results with human expert performance. We are using DDP (Differential Dynamic Programming) as the locally trajectory optimizer and a 2D dynamics and kinematics simulator is used to evaluate the accuracy of the presented algorithm.