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Risk-Sensitive Cubature Filtering for Jump Markov Nonlinear systems and Its Application to Land Vehicle Positioning ⋆

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IFAC Proceedings Volumes 2011年第1期44卷 20-25页

作者： Wenling Li Yingmin Jia Junping Du Fashan Yu The Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Key Laboratory of Mathematics Informatics and Behavioral Semantics (LMIB) Ministry of Education SMSS Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

Abstract In this paper, a risk-sensitive filter for a class of jump Markov nonlinear systems is proposed. By using a set of weighted cubature points to approximate the intractable risk-sensitive recursions, the proposed filter could exhibit improved numerical stability with respect to the derivation of the square-root covariance, for which the unscented transform technique might halt the operations due to the presence of non-positive definite covariance. The performance of the proposed filter is illustrated through a simulation study of tracking a land vehicle with maneuvers.

关键词： Markov models Kalman filters estimation theory target tracking

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Robotic test bed for autonomous surface exploration of Titan, Mars, and other planetary bodies

Robotic test bed for autonomous surface exploration of Titan...

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IEEE Conference on Aerospace

作者： Wolfgang Fink Mark A. Tarbell Roberto Furfaro Linda Powers Jeffrey S. Kargel Victor R. Baker Jonathan Lunine Visual and Autonomous Exploration Systems Research Laboratory Division of Physics Mathematics and Astronomy California Institute of Technology Pasadena CA USA Visual and Autonomous Exploration Systems Research Laboratory Departments of Electrical & Computer Engineering Biomedical Engineering and Ophthalmology and Vision Science University of Arizona Tucson Tucson AZ USA Systems and Industrial Engineering Department University of Arizona Tucson Tucson AZ USA Department of Electrical & Computer Engineering University of Arizona Tucson Tucson AZ USA Department of Hydrology and Water Resources University of Arizona Tucson Tucson AZ USA Lunar and Planetary Laboratory University of Arizona Tucson Tucson AZ USA

Tier-scalable robotic reconnaissance missions are called for in extreme space environments, including planetary atmospheres, surfaces (both solid and liquid), and subsurfaces (e.g., oceans), as well as in potentially hazardous or inaccessible operational areas on Earth. Such future missions will require increasing degrees of operational autonomy: (1) Automatic mapping of an operational area from different vantages (i.e., spaceborne, airborne, surface, subsurface); (2) automatic sensor deployment and sensor data gathering; (3) automatic feature extraction and target/region-of-interest/anomaly identification within the mapped operational area; (4) automatic target prioritization for follow-up or close-up (in-situ) examination; and (5) subsequent automatic, targeted deployment and navigation/relocation of agents/sensors (e.g., to follow up on transient events). We report on recent progress in developing an Earth-based (outdoors) robotic test bed for Tier-scalable Reconnaissance at the University of Arizona and Caltech for distributed, science-driven, and significantly less constrained (compared to state-of-the-art) reconnaissance of prime locations on a variety of planetary bodies, with particular focus on Saturn's moon Titan with its methane/hydrocarbon lakes and Mars. The test bed currently comprises several computer-controlled robotic surface vehicles, i.e., rovers and lake landers/boats equipped with a variety of sensors. To achieve a fully operational Tier-scalable Reconnaissance test bed, aerial platforms will be integrated as a next step. The robotic surface vehicles can be interactively or automatically controlled from anywhere in the world in near real-time via the Internet. The test bed enables the implementation, field-testing, and validation of algorithms and strategies for navigation, exploration, sensor deployment, sensor data gathering, feature extraction, anomaly detection, and science goal prioritization for autonomous planetary exploration. Furthermor

关键词： Robot sensing systems Sea surface Cameras Reconnaissance Boats Lakes

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Adaptive Iterative Learning Control for Uncertain Delay systems Based on Model Matching Technique

Adaptive Iterative Learning Control for Uncertain Delay Syst...

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2011 American Control Conference (ACC)

作者： Haixia Su Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University Beijing China Key Laboratory of Mathematics Informatics and Behavioral Semantics (LMIB) Ministry of Education SMSS Beihang University Beijing China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo Henan China

In this paper, an adaptive iterative learning control (ILC) scheme is proposed for trajectory tracking of uncertain delay systems based on model matching technique. The reference model is a delay system operating over in a finite time interval. An iterative model matching controller is designed and an iteration domain adaptive law is chosen to estimate the unknown parameters. It shows that the model matching technique can be applied in a straightforward method to ILC problem. A simulation example is included to illustrate the designed scheme.

关键词： Adaptation models Polynomials Adaptive systems Delay effects Delay systems

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Gaussian Mixture PHD Smoother for Jump Markov Models in Multiple Maneuvering Targets Tracking

Gaussian Mixture PHD Smoother for Jump Markov Models in Mult...

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2011 American Control Conference (ACC)

作者： Wenling Li Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University Beijing China Key Laboratory of Mathematics Informatics and Behavioral Semantics (LMIB) Ministry of Education SMSS Beihang University Beijing China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo Henan China

This paper presents a Gaussian mixture probability hypothesis density (GM-PHD) smoother for tracking multiple maneuvering targets that follow jump Markov models. Unlike the generalization of the multiple model GM-PHD filters, our aim is to approximate the dynamics of the linear Gaussian jump Markov system (LGJMS) by a best-fitting Gaussian (BFG) distribution so that the GM-PHD smoother can be carried out with respect to an approximated linear Gaussian system. Our approach is inspired by the recognition that the BFG approximation provides an accurate performance measure for the LGJMS. Furthermore, the multiple model estimation is avoided and less computational cost is required. The effectiveness of the proposed smoother is verified with a numerical simulation.

关键词： Target tracking Approximation methods Markov processes Covariance matrix Smoothing methods Radar tracking Computational efficiency

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Design of a Robot Cloud Center

Design of a Robot Cloud Center

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International Symposium on Autonomous Decentralized systems (ISADAS)

作者： Zhihui Du Weiqiang Yang Yinong Chen Xin Sun Xiaoying Wang Chen Xu Tsinghua National Laboratory for Information Science and Technology Department of Computer Science and Technology Tsinghua University Beijing China School of Software and Microelectronics Peking University Beijing China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ USA International School Beijing University of Posts and Telecommunications Beijing China

Service-oriented architecture and cloud computing have become the prevalent computing paradigm. In this paradigm, computing resources can be accessed like other utility services available in today's society. In the meantime, robotics applications are joining the trend. More and more robot applications are shifting from manufacture to non-manufacture and service industries. However, for the on-demand supply of the large-scale heterogeneous robots, It is still a problem have not yet been studied, including the fundamental management and efficiency issues in using of these resources. In this paper, we design a framework of "Robot Cloud Center" (RCC) following the general cloud computing paradigm to address the current limitations in capacity and versatility of robotic applications. In this framework, a robot can be provided as a service just like a public utility service so that everyone can access the powerful robotic services easily, efficiently, and cheaply. Based on a given scenario, a robot scheduling algorithm in RCC is proposed to take advantage of the heterogeneous robot resources to meet the end user's requirement with the minimum cost.

关键词： Service robots computer architecture Service oriented architecture Hardware Cloud computing Computational modeling

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Robust L_(2) - L_(infinity) Consensus Control of the Second-order Multi-agent systems with Time-delay

Robust L_(2) - L_(infinity) Consensus Control of the Second-...

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IEEE Conference on Decision and Control

作者： Yan Cui Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

ISBN: (纸本)9781612848006

Robust L_(2) - L_(infinity) consensus control is studied for the second-order multi-agent systems with external disturbances and parameter uncertainties. By defining an appropriate controlled output, the consensus problem of the systems is transformed into a normal L_(2) - L_(infinity) control problem, and distributed state feedback protocols with time-delay are proposed. Sufficient conditions are established for the convergence to consensus of the network under fixed or switching topology. Numerical simulations are provided to demonstrate the effectiveness of our theoretical results.

关键词： Topology Europe

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Collision Avoidance Maneuver Design Based on Equidistance Interpolation

Collision Avoidance Maneuver Design Based on Equidistance In...

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IEEE Conference on Decision and Control

作者： Yongqiang Qi Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

ISBN: (纸本)9781612848006

This paper deals with the active collision avoidance maneuver for the chaser along the specified trajectory, and presents a maneuver approach with constant thrust. Using the 3D stereo vision measurement, The relative position parameters of the target spacecraft for analyzing the collision possibility are obtained by using the vision measurement and the target maneuver positions are calculated through the equidistance interpolation method. The working times of thrusters in three axes can be respectively computed by the time series analysis method. In particular, the perturbation and fuel consumption are addressed during the computation of working time. Furthermore, the acceleration sequences and the corresponding working time series can be employed to determine a switching control law for the active collision avoidance maneuver. The simulation results show that the switch control law can effectively guarantee the chaser moving along the specified trajectory.

关键词： Constant thrust Vision measurement Switch control law The specified trajectory Equidistance interpolation

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Two alternative approaches to stochastic discrete-time iterative learning control systems

Two alternative approaches to stochastic discrete-time itera...

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IEEE Conference on Decision and Control

作者： Deyuan Meng Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

ISBN: (纸本)9781612848006

This paper aims to address the robust convergence problem that arises from discrete-time iterative learning control (ILC) systems subject to random disturbances. Two alternative approaches are considered in order to achieve the perfect output tracking of the stochastic discrete-time ILC systems in the sense of both expectation and variance, which use the tracking error and the input error for analysis, respectively. It is shown that the convergence results of two approaches to ILC can be established by developing some statistical expressions in super-vector forms. Moreover, it is demonstrated that the convergence results of two approaches to ILC are not always equal, and they can keep the same only in the case where the controlled plants are square.

关键词： Iterative learning control discrete-time systems random disturbances

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Gaussian mixture PHD filter for multiple maneuvering extended targets tracking

Gaussian mixture PHD filter for multiple maneuvering extende...

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IEEE Conference on Decision and Control

作者： Wenling Li Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

ISBN: (纸本)9781612848006

This paper addresses the problem of tracking multiple maneuvering extended targets in the framework of random finite set theory. An elliptical model is adopted for exploiting sensor measurements of target extent, and the target dynamics is described by a jump Markov linear system which combines the shape parameters into the kinematic state vector. As each extended target gives rise to unlabeled multiple measurements per time step, all the received measurements are partitioned into a number of subsets so that the measurements in each subset are expected to stem from the same source. In addition, the best-fitting Gaussian approximation approach is employed to circumvent the difficulty of multiple model mixing in the Gaussian mixture probability hypothesis density (GM-PHD) filter. A numerical example is provided to compare the performance of the proposed filter with that of the GM-PHD filter without measurement partition.

关键词： Maneuvering Filters shape parameter extended target Gauss Subset numerical example

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Column Formation Control of Multi-robot systems with Input Constraints

Column Formation Control of Multi-robot Systems with Input C...

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IEEE Conference on Decision and Control

作者： Xiaohan Chen Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

ISBN: (纸本)9781612848006

This paper is concerned with the column formation control of multi-robot systems that are subject to input constraints. A new leader-follower setup is proposed, under which the Lyapunov method can provide a simple controller in terms of two feedback parameters. It is shown that using an elliptic approximation to input constraints, the two feedback parameters can be obtained directly with a geometric analysis method. Moreover, a sufficient condition is presented for the leader robot to guarantee that the desired column formation can be achieved, with which a particular controller is designed by selecting two appropriate functions for the feedback parameters. Simulation results are included to verify the effectiveness of the proposed theoretical results.

关键词： Column formation control multi-robot systems leader-follower input constraints elliptic approximation

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