Despite the advances in automated vulnerability detection approaches,security vulnerabilities caused by design flaws in software systems are continuously appearing in real-world systems.Such security design flaws can ...Despite the advances in automated vulnerability detection approaches,security vulnerabilities caused by design flaws in software systems are continuously appearing in real-world systems.Such security design flaws can bring unrestricted and misimplemented behaviors of a system and can lead to fatal vulnerabilities such as remote code execution or sensitive data leakage.Therefore,it is an essential task to discover unrestricted and misimplemented behaviors of a system.However,it is a daunting task for security experts to discover such vulnerabilities in advance because it is timeconsuming and error-prone to analyze the whole code in detail.Also,most of the existing vulnerability detection approaches still focus on detecting memory corruption bugs because these bugs are the dominant root cause of software vulnerabilities.This paper proposes SMINER,a novel approach that discovers vulnerabilities caused by unrestricted and misimplemented behaviors.SMINER first collects unit test cases for the target system from the official repository.Next,preprocess the collected code fragments.SMINER uses pre-processed data to show the security policies that can occur on the target system and creates a test case for security policy testing.To demonstrate the effectiveness of SMINER,this paper evaluates SMINER against Robot Operating System(ROS),a real-world system used for intelligent robots in Amazon and controlling satellites in National Aeronautics and Space Administration(NASA).From the evaluation,we discovered two real-world vulnerabilities in ROS.展开更多
在停车场、隧道中GPS、Wi-Fi信号受限的情况下,提出一种基于激光雷达的车辆自主定位方法。采用激光雷达SLAM(simultaneous localization and mapping)算法,通过三维激光雷达点云匹配获取车辆的估计位姿;根据图优化方法和非线性优化方法...在停车场、隧道中GPS、Wi-Fi信号受限的情况下,提出一种基于激光雷达的车辆自主定位方法。采用激光雷达SLAM(simultaneous localization and mapping)算法,通过三维激光雷达点云匹配获取车辆的估计位姿;根据图优化方法和非线性优化方法,对所有位姿进行后端调整,进而得到分辨率可控的环境信息平面栅格地图;基于蒙特卡洛方法,采用粒子滤波器进行实时车辆定位,并提出了粒子采样的一种改善方式,实现了较高精度的激光雷达自主定位。结果表明:粒子滤波器能够有效地实现车辆在停车场等无GPS环境下的定位,定位精度在10 cm之内。展开更多
Traditional cochlear implantation surgery has problems such as high surgical accuracy requirement and large trauma,which cause the difficulty of the operation and the high requirements for doctors,so that only a few d...Traditional cochlear implantation surgery has problems such as high surgical accuracy requirement and large trauma,which cause the difficulty of the operation and the high requirements for doctors,so that only a few doctors can complete the operation independently.However,there is no research on robotic cochlear implantation in China.In response to this problem,a robotic cochlear implantation system is proposed.The robot is controlled by robot operating system(ROS).A simulation environment for the overall surgery is established on the ROS based on the real surgery environment.Through the analysis of the kinematics and the motion planning algorithm of the manipulator,an appropriate motion mode is designed to control the motion of the manipulator,and perform the surgery under the simulation environment.A simple and feasible method of navigation is proposed,and through the model experiment,the feasibility of robotic cochlear implantation surgery is verified.展开更多
Currently, due to the detrimental effects on surface finish and machining system, chatter has been one crucial factor restricting robotic drilling operations, which improve both quality and efficiency of aviation manu...Currently, due to the detrimental effects on surface finish and machining system, chatter has been one crucial factor restricting robotic drilling operations, which improve both quality and efficiency of aviation manufacturing. Based on the matrix notch filter and fast wavelet packet decomposition, this paper presents a novel pre-generated matrix-based real-time chatter monitoring method for robotic drilling. Taking vibration characteristics of robotic drilling into account, the matrix notch filter is designed to eliminate the interference of spindle-related components on the measured vibration signal. Then, the fast wavelet packet decomposition is presented to decompose the filtered signal into several equidistant frequency bands, and the energy of each sub-band is obtained. Finally, the energy entropy which characterizes inhomogeneity of energy distribution is utilized as the feature to recognize chatter on-line, and the effectiveness of the presented algorithm is validated by extensive experimental data. The results show that the proposed algorithm can effectively detect chatter before it is fully developed. Moreover, since both filtering and decomposition of signal are implemented by the pre-generated matrices, calculation for an energy entropy of vibration signal with 512 samples takes only about 0.690 ms. Consequently, the proposed method achieves real-time chatter monitoring for robotic drilling, which is essential for subsequent chatter suppression.展开更多
In this article,a new trajectory programming system that allows non-expert users to intuitively and efficiently program trajectories for robots is proposed.The system tracks a pen-shaped marker and obtains its positio...In this article,a new trajectory programming system that allows non-expert users to intuitively and efficiently program trajectories for robots is proposed.The system tracks a pen-shaped marker and obtains its position and orientation by processing the point cloud data of the workspace.A graphical user interface,which enables users to save and execute the acquired trajectory immediately after performing trajectory demonstration,is designed and developed for the system.The performance of the developed system is experimentally evaluated by using it to program trajectories for a UR5 robot.The results indicate that compared with traditional kinesthetic programming,the developed system has the potential of significantly reducing the ergonomic stress and workload of users.The system is developed based on the robot operating system,which facilitates its integration with different robot control systems.展开更多
With the continuous development of robotics and artificial intelligence,robots are being increasingly used in various applications.For traditional navigation algorithms,such as Dijkstra and A*,many dynamic scenarios i...With the continuous development of robotics and artificial intelligence,robots are being increasingly used in various applications.For traditional navigation algorithms,such as Dijkstra and A*,many dynamic scenarios in life are difficult to cope with.To solve the navigation problem of complex dynamic scenes,we present an improved reinforcement-learning-based algorithm for local path planning that allows it to perform well even when more dynamic obstacles are present.The method applies the gmapping algorithm as the upper layer input and uses reinforcement learning methods as the output.The algorithm enhances the robots’ability to actively avoid obstacles while retaining the adaptability of traditional methods.展开更多
基金This work was supported in part by the National Research Foundation of Korea(NRF)funded by the Ministry of Science and ICT(MSIT)Future Planning under Grant NRF-2020R1A2C2014336 and Grant NRF-2021R1A4A1029650.
文摘Despite the advances in automated vulnerability detection approaches,security vulnerabilities caused by design flaws in software systems are continuously appearing in real-world systems.Such security design flaws can bring unrestricted and misimplemented behaviors of a system and can lead to fatal vulnerabilities such as remote code execution or sensitive data leakage.Therefore,it is an essential task to discover unrestricted and misimplemented behaviors of a system.However,it is a daunting task for security experts to discover such vulnerabilities in advance because it is timeconsuming and error-prone to analyze the whole code in detail.Also,most of the existing vulnerability detection approaches still focus on detecting memory corruption bugs because these bugs are the dominant root cause of software vulnerabilities.This paper proposes SMINER,a novel approach that discovers vulnerabilities caused by unrestricted and misimplemented behaviors.SMINER first collects unit test cases for the target system from the official repository.Next,preprocess the collected code fragments.SMINER uses pre-processed data to show the security policies that can occur on the target system and creates a test case for security policy testing.To demonstrate the effectiveness of SMINER,this paper evaluates SMINER against Robot Operating System(ROS),a real-world system used for intelligent robots in Amazon and controlling satellites in National Aeronautics and Space Administration(NASA).From the evaluation,we discovered two real-world vulnerabilities in ROS.
文摘在停车场、隧道中GPS、Wi-Fi信号受限的情况下,提出一种基于激光雷达的车辆自主定位方法。采用激光雷达SLAM(simultaneous localization and mapping)算法,通过三维激光雷达点云匹配获取车辆的估计位姿;根据图优化方法和非线性优化方法,对所有位姿进行后端调整,进而得到分辨率可控的环境信息平面栅格地图;基于蒙特卡洛方法,采用粒子滤波器进行实时车辆定位,并提出了粒子采样的一种改善方式,实现了较高精度的激光雷达自主定位。结果表明:粒子滤波器能够有效地实现车辆在停车场等无GPS环境下的定位,定位精度在10 cm之内。
基金the National Natural Science Foundation of China(Nos.61973211,62133009,51911540479 and M-0221)the Science and Technology Commission of Shanghai Municipality(Nos.21550714200 and 20DZ2220400)+1 种基金the Research Project of Institute of Medical Robotics of Shanghai Jiao Tong Universitythe Interdisciplinary Program of Shanghai Jiao Tong University(Nos.YG2017ZD03 and ZH2018QNB31)。
文摘Traditional cochlear implantation surgery has problems such as high surgical accuracy requirement and large trauma,which cause the difficulty of the operation and the high requirements for doctors,so that only a few doctors can complete the operation independently.However,there is no research on robotic cochlear implantation in China.In response to this problem,a robotic cochlear implantation system is proposed.The robot is controlled by robot operating system(ROS).A simulation environment for the overall surgery is established on the ROS based on the real surgery environment.Through the analysis of the kinematics and the motion planning algorithm of the manipulator,an appropriate motion mode is designed to control the motion of the manipulator,and perform the surgery under the simulation environment.A simple and feasible method of navigation is proposed,and through the model experiment,the feasibility of robotic cochlear implantation surgery is verified.
基金supported by the National Key R&D Program of China (No. 2017YFB1302601 and 2018YFB1702503)
文摘Currently, due to the detrimental effects on surface finish and machining system, chatter has been one crucial factor restricting robotic drilling operations, which improve both quality and efficiency of aviation manufacturing. Based on the matrix notch filter and fast wavelet packet decomposition, this paper presents a novel pre-generated matrix-based real-time chatter monitoring method for robotic drilling. Taking vibration characteristics of robotic drilling into account, the matrix notch filter is designed to eliminate the interference of spindle-related components on the measured vibration signal. Then, the fast wavelet packet decomposition is presented to decompose the filtered signal into several equidistant frequency bands, and the energy of each sub-band is obtained. Finally, the energy entropy which characterizes inhomogeneity of energy distribution is utilized as the feature to recognize chatter on-line, and the effectiveness of the presented algorithm is validated by extensive experimental data. The results show that the proposed algorithm can effectively detect chatter before it is fully developed. Moreover, since both filtering and decomposition of signal are implemented by the pre-generated matrices, calculation for an energy entropy of vibration signal with 512 samples takes only about 0.690 ms. Consequently, the proposed method achieves real-time chatter monitoring for robotic drilling, which is essential for subsequent chatter suppression.
基金supported by the Major Projects of Guangzhou City of China(Grant Nos.201907010012,201704030091 and 201607010041)the Guangdong Innovative and Entrepreneurial Research Team Program(Grant No.2014ZT05G132)+3 种基金Shenzhen Peacock Plan(Grant No.KQTD2015033117354154)the Major Projects of Guangdong Province of China(Grant No.2015B010919002)the Major Projects of Dongguan City of China(Grant No.2017215102008)the Nansha District International Science and Technology Cooperation Project of Guangzhou City of China(Grant No.2016GJ004).
文摘In this article,a new trajectory programming system that allows non-expert users to intuitively and efficiently program trajectories for robots is proposed.The system tracks a pen-shaped marker and obtains its position and orientation by processing the point cloud data of the workspace.A graphical user interface,which enables users to save and execute the acquired trajectory immediately after performing trajectory demonstration,is designed and developed for the system.The performance of the developed system is experimentally evaluated by using it to program trajectories for a UR5 robot.The results indicate that compared with traditional kinesthetic programming,the developed system has the potential of significantly reducing the ergonomic stress and workload of users.The system is developed based on the robot operating system,which facilitates its integration with different robot control systems.
基金supported in part by the National Key Research and Development Project of China(No.2019YFB2102500)the Natural Science Foundation of Hebei Province(No.F2018201115).
文摘With the continuous development of robotics and artificial intelligence,robots are being increasingly used in various applications.For traditional navigation algorithms,such as Dijkstra and A*,many dynamic scenarios in life are difficult to cope with.To solve the navigation problem of complex dynamic scenes,we present an improved reinforcement-learning-based algorithm for local path planning that allows it to perform well even when more dynamic obstacles are present.The method applies the gmapping algorithm as the upper layer input and uses reinforcement learning methods as the output.The algorithm enhances the robots’ability to actively avoid obstacles while retaining the adaptability of traditional methods.
