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1.
Semantic information can help robots understand unknown environments better. In order to obtain semantic information efficiently and link it to a metric map, we present a new robot semantic mapping approach through human activity recognition in a human–robot coexisting environment. An intelligent mobile robot platform called ASCCbot creates a metric map while wearable motion sensors attached to the human body are used to recognize human activities. Combining pre-learned models of activity–furniture correlation and location–furniture correlation, the robot determines the probability distribution of the furniture types through a Bayesian framework and labels them on the metric map. Computer simulations and real experiments demonstrate that the proposed approach is able to create a semantic map of an indoor environment effectively.  相似文献   
2.
ContextThere are several empirical principles related to the distribution of faults in a software system (e.g. the Pareto principle) widely applied in practice and thoroughly studied in the software engineering research providing evidence in their favor. However, the knowledge of the underlying probability distribution of faults, that would enable a systematic approach and refinement of these principles, is still quite limited.ObjectiveIn this paper we study the probability distribution of faults detected during verification in four consecutive releases of a large-scale complex software system for the telecommunication exchanges. This is the first such study analyzing closed software system, replicating two previous studies for open source software.MethodWe take into consideration the Weibull, lognormal, double Pareto, Pareto, and Yule–Simon probability distributions, and investigate how well these distributions fit our empirical fault data using the non-linear regression.ResultsThe results indicate that the double Pareto distribution is the most likely choice for the underlying probability distribution. This is not consistent with the previous studies on open source software.ConclusionThe study shows that understanding the probability distribution of faults in complex software systems is more complicated than previously thought. Comparison with previous studies shows that the fault distribution strongly depends on the environment, and only further replications would make it possible to build up a general theory for a given context.  相似文献   
3.
ContextMemory safety errors such as buffer overflow vulnerabilities are one of the most serious classes of security threats. Detecting and removing such security errors are important tasks of software testing for improving the quality and reliability of software in practice.ObjectiveThis paper presents a goal-oriented testing approach for effectively and efficiently exploring security vulnerability errors. A goal is a potential safety violation and the testing approach is to automatically generate test inputs to uncover the violation.MethodWe use type inference analysis to diagnose potential safety violations and dynamic symbolic execution to perform test input generation. A major challenge facing dynamic symbolic execution in such application is the combinatorial explosion of the path space. To address this fundamental scalability issue, we employ data dependence analysis to identify a root cause leading to the execution of the goal and propose a path exploration algorithm to guide dynamic symbolic execution for effectively discovering the goal.ResultsTo evaluate the effectiveness of our proposed approach, we conducted experiments against 23 buffer overflow vulnerabilities. We observed a significant improvement of our proposed algorithm over two widely adopted search algorithms. Specifically, our algorithm discovered security vulnerability errors within a matter of a few seconds, whereas the two baseline algorithms failed even after 30 min of testing on a number of test subjects.ConclusionThe experimental results highlight the potential of utilizing data dependence analysis to address the combinatorial path space explosion issue faced by dynamic symbolic execution for effective security testing.  相似文献   
4.
The present work concerns model predictive control (MPC) of centrifugal gas compressors and describes the development of an MPC application for the tasks of anti-surge and process control. More specifically, the MPC formulation focuses on the question of how the transient manipulation of driver torque can be used to improve the performance of anti-surge and process control. For the purpose of testing and validating the proposed control algorithm, an experimental compressor test rig is presented, which is designed to mimic a typical centrifugal compressor application in the oil and gas industry. Modeling and parameter identification of the experimental setup is followed by the realization of the MPC solution on an embedded system to comply with the stringent real-time requirements for anti-surge control. Testing is performed with experiments using suction and discharge side disturbances, which are created by rapid valve closures. For comparison the same tests are repeated with conventional control approaches. The test results indicate improvements in maintaining the distance to surge by up to 11%, while at the same time reducing the process control settling time by up to 50%.  相似文献   
5.
The relative sliding motion of two elastic bodies in contact induces wear process and contact shape evolution. In the case of a punch sliding on a substrate the transient process tends to a steady state for which the fixed contact stress and strain distribution develops in the contact zone. This state usually corresponds to a minimum of the wear dissipation power. The optimality conditions of the wear dissipation functional provide the contact stress distribution and the wear rate compatible with the rigid body punch motion. The present paper is aimed to extend the previous analyses [1], [2], [3], [4], [5] of steady state conditions to cases of periodic sliding of punch, assuming cyclic steady state conditions for both mechanical and thermal fields.  相似文献   
6.
The paper presents an improved sectional discretization method for evaluating the response of reinforced concrete sections. The section is subdivided into parametric subdomains that allow the modelization of any complex geometry while taking advantage of the Gauss quadrature techniques. In particular, curved boundaries are dealt with two nested parametric transformations, reducing the modeling approximation. It is shown how the so-called fiber approach is simply a particular case of the present more general method. Many benchmarks are presented in order to assess the accuracy of the results. The influence of the discretization into subdomains and of the quadrature rules, chosen for integration, is discussed. The numerical tests highlight also the effects of spurious stress distributions in the tensile concrete zone, due the interpolation functions adopted for the Gauss integration. It is shown how balancing the number of subdomains and the number of sampling points such spurious effects vanish. The method shows to be accurate, very flexible in the discretization process and robust in analyzing any sectional state. Moreover, it converges faster than the fiber method, reducing the computational demand. All these properties are of great importance when the computations are iteratively repeated, as for the case of the sectional analysis within a computational procedure for a R.C. frame analysis.  相似文献   
7.
In practical applications of structural health monitoring technology, a large number of distributed sensors are usually adopted to monitor the big dimension structures and different kinds of damage. The monitored structures are usually divided into different sub-structures and monitored by different sensor sets. Under this situation, how to manage the distributed sensor set and fuse different methods to obtain a fast and accurate evaluation result is an important problem to be addressed deeply. In the paper, a multi-agent fusion and coordination system is presented to deal with the damage identification for the strain distribution and joint failure in the large structure. Firstly, the monitoring system is adopted to distributedly monitor two kinds of damages, and it self-judges whether the static load happens in the monitored sub-region, and focuses on the static load on the sub-region boundary to obtain the sensor network information with blackboard model. Then, the improved contract net protocol is used to dynamically distribute the damage evaluation module for monitoring two kinds of damage uninterruptedly. Lastly, a reliable assessment for the whole structure is given by combing various heterogeneous classifiers strengths with voting-based fusion. The proposed multi-agent system is illustrated through a large aerospace aluminum plate structure experiment. The result shows that the method can significantly improve the monitoring performance for the large-scale structure.  相似文献   
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9.
对未知观测噪声的机器人同步定位与地图构建问题,提出基于神经网络PID自适应学习观测噪声的机器人同步定位与地图构建算法.已知系统噪声为高斯分布,噪声的方差未知,但其真值是在某个有限集合内.设计一个由神经网络PID控制器、观测噪声调整以及中值滤波构成的噪声在线辨识单元.通过自适应在线辨识观测噪声,并进行新息协方差平均值滤波,迭代修正观测噪声协方差,实现机器人同步定位精度的在线提高.实验表明,该算法可降低观测噪声先验信息不足的影响,减小定位误差.  相似文献   
10.
旋翼飞行机器人是面向空中自主作业需求,将旋翼飞行器与多自由度机械臂相结合所提出的新型机器人.该机器人作业过程中旋翼飞行器、机械臂与作业目标之间的动态相对运动以及与作业目标接触过程中未建模外力、力矩扰动使自主控制受到极大挑战.本文将针对旋翼飞行机器人的结构演变及关键技术、作业机构集成技术进行综述.从动力学建模及动力学特性分析、动态运动约束/力约束下的协调规划、非结构环境下的运动和作业控制、面向任务动态操作的环境感知、面向任务的实验系统构建与实验验证五个方面初步构建了旋翼飞行机器人自主作业理论体系.  相似文献   
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