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IEEE/RSJ International Conference on intelligent Robots and systems (IROS)

作者： Liang Wang Tianwei Niu Shoukun Wang Shuai Wang Junzheng Wang Key Laboratory of Drive and Control of Servo Motion System School of Automation Beijing Institute of Technology Beijing China The State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology School of Automation Beijing Institute of Technology Beijing China

In order to guarantee autonomous vehicles' autonomy, mobility, and ride quality in rugged environments, a real-time speed planning method based on the time-frequency transformation of terrain characteristics is designed to achieve adaptive speed planning of autonomous vehicles in rough ground. On the one hand, the vertical profile of the lidar's point cloud data is converted from the time domain to the frequency domain in real time, and the integrated area of the sub-frequency range in the frequency domain is chosen as the relative roughness quantification value to realize the roughness quantification under various terrains. On the other hand, to model the relationship between vehicle speed and relative roughness, iterative search is utilized to create a speed and roughness model, and sliding windows are employed to update the roughness to achieve continuous mapping between speed and roughness. Ultimately, a number of tests were conducted on various rough roads using the oil exploration vehicle EV-56 as the study object. The experimental results show that the proposed method can identify the terrain roughness changes under complex terrain and change their speed within 0.2 m accuracy.

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LQG control for sampled-data systems under stochastic sampling

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Journal of the Franklin Institute 2020年第5期357卷 2773-2790页

作者： Haoyuan Sun Jian Sun Jie Chen Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing 100081 PR China College of Electronic and Information Tongji University Shanghai China

This paper studies the linear-quadratic-Gaussian (LQG) problem for sampled-data systems with a stochastic sampling interval obeying a certain probability distribution. An optimal estimator of the system state is presented by the standard Kalman filter , and the Vandermonde matrix and Kronecker product operation are used to calculate the mathematical expectation caused by stochastic sampling in the process of designing the LQG controller. Moreover, it was proved that the controller can ensure the system is exponentially mean square stable. Finally, some simulation results are given to verify the effectiveness and practicability of the proposed controller design method.

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Decentralized Valley-fill Charging control of Large-population Plug-in Electric Vehicles

Decentralized Valley-fill Charging Control of Large-populati...

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The 24th Chinese control and decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

作者： Zhongjing Ma School of Automation Beijing Institute of Technology (BIT) and the Key Laboratory of Complex System Intelligent Control and Decision (BIT) Ministry of Education

Optimal charging control of large-population autonomous plug-in electric vehicles (PEVs) in power grid can be formulated as a class of constrained non-linear timevariant optimization problems. To overcome the computational complexity of this class of optimization problems, the author and his collaborators proposed a game-based decentralized control method such that individual agents update their best charging strategies simultaneously with respect to a common electricity price signal which is determined by the total demand in the grid. Due to the heterogeneity of individual PEVs, the game systems converge to a nearly valley-fill NE strategy with nontrivial deviation costs due to the heterogeneity property of individual PEV charging characteristics. In this paper the author proposed a novel algorithm to implement the optimal decentralized valley fill strategies for the charging problems of the PEV population which is composed of disjoint homogeneous subpopulations. The author introduces a cost which penalizes against the deviation of strategy of individual agent in a subpopulation from the average value of the subpopulation. It can be shown that in case that the update algorithm converges, the system reaches the optimal valley-fill equilibrium strategy where the introduced agent deviation cost vanishes. Simulation examples are used to illustrate the results developed in this paper.

关键词： Decentralized charging control Plug-in electric vehicles (PEVs) Valley-fill (VF) Nash equilibrium (NE)

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Improved ICCP algorithm and its application in gravity matching aided inertial navigation system

Improved ICCP algorithm and its application in gravity match...

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Chinese control Conference (CCC)

作者： Meiqi Liu Bo Wang Zhihong Deng Mengyin Fu School of Automation and National Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing Beijing CN

Considering two disadvantages in traditional gravity matching aided inertial navigation system, low matching accuracy and error accumulation, we propose an improved gravity matching algorithm and aided method for inertial navigation system. Instead of using the sequence sampling, the single point sampling is applied to improve the structure of proposed algorithm, enhancing the matching speed and efficiency. In the aided navigation system method, we use combination of Sage-Husa adaptive filter and strong-tracked Kalman filter to make further optimal estimation of the matching trajectory. Simulation results show the effectiveness of the real-time ICCP algorithm and the combined filter algorithm. Comparing to the traditional methods, proposed method provides higher matching and navigation accuracy.

关键词： Gravity Filtering algorithms Algorithm design and analysis Navigation Accuracy Filtering theory

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Human-like walking patterns with pelvic rotation for a humanoid robot

Human-like walking patterns with pelvic rotation for a human...

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World Congress on intelligent control and Automation (WCICA)

作者： Wen Zhang Qiang Huang Zhangguo Yu Gao Huang Xuechao Chen Jing Li Gan Ma Libo Meng Yan Liu Si Zhang Weimin Zhang Junyao Gao Ministry of Education Beijing Institute of Technology Beijing China Key Laboratory of Intelligent Control and Decision of Complex System Beijing China

Fast and stable walking is one of the important prerequisite for humanoid robots to serve the people. Pelvic rotations play a significant role when one walks fast. This paper proposes a method to generate human-like walking patterns with pelvic rotation in the transverse plane for a humanoid robot to effectively improve its quickness and stability. First, the regularities of pelvic rotation in the transverse plane during human walking are studied. Second, the mechanism design of a humanoid robot waist for pelvic rotations is presented. Then, a walking trajectory planning with pelvic rotation to improve the stability margin is proposed. Finally, the effectiveness of the method is demonstrated through simulations and experiments on BHR-5.

关键词： Legged locomotion Humanoid robots Trajectory Joints Pelvis Stability analysis

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Synchronization of Networked Multi-agent system with Delayed Information from Neighbors

Synchronization of Networked Multi-agent System with Delayed...

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The 24th Chinese control and decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

作者： Lijing Dong Senchun Chai Baihai Zhang School of Automation Beijing Institute of Technology Beijing 100081 Key Laboratory of Intelligent Control and Decision of Complex SystemBeijing 100081

—In this paper, a synchronization of discrete multi-agent systems with random network delays was studied. By employing the graph and matrix theory, a model based predictive control algorithm is proposed to achieve leader-following consensus in a network of agents. Furthermore, a consensus protocol is developed based on this strategy. Numerical simulation examples are provided to illustrate the effectiveness of the theoretical results.

关键词： Multi-agent Synchronization and Time Delay

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Fast trajectory planning of reactive operation considering manipulability for a humanoid

Fast trajectory planning of reactive operation considering m...

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World Congress on intelligent control and Automation (WCICA)

作者： Yan Liu Jing Li Zhangguo Yu Wen Zhang Qiang Huang Xuechao Chen Gan Ma Libo Meng Si Zhang Fei Meng Weimin Zhang Junyao Gao Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Beijing China Key Laboratory of Intelligent Control and Decision of Complex System Beijing China

For humanoid robots, there exist a class of challenging tasks, e.g. playing table tennis, which are non-repeatedly, triggered randomly by sensor events, and compelling the robots to produce reactive operations in very short time. Additionally, some key poses of the robot are partially constrained to accomplish the operations, and are usually adjusted during the operation execution. In this paper, efforts are made to generate trajectory for these operations. Firstly, an extended manipulability index is proposed to optimize the key poses so that the humanoid robot has the manipulability considering joint limits at the key poses, which makes it convenient to adjust the trajectory. Secondly, a fast approach to generating the whole trajectory consisting of all the key poses and the strategies to realize the trajectory adjustment when specifications change are proposed. Finally, the ZMP (Zero Moment Point) displacement excited by the reactive operations is also given to decide whether the generated trajectory is feasible. The effectiveness of the method is demonstrated through simulations.

关键词： Trajectory Joints Humanoid robots Indexes Jacobian matrices Optimization

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complex Terrain Perception based on Hidden Markov Model

Complex Terrain Perception based on Hidden Markov Model

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IEEE International Conference on intelligent Transportation systems

作者： Meiling WANG Liang ZUO Yi YANG Qiangrong YANG Tong LIU School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Intelligent Control and Decision of Complex System Beijing China

Terrain perception in complex environment is important for Autonomous Land Vehicle to drive automatically. In order to access the terrain information, in this paper, we present a terrain perception method based on Hidden Markov Model (HMM) which combines LIDAR with machine vision. On the basis of spatial fan-shaped model, terrain feature extraction is performed to acquire the observation model. Hidden markov models describe the vertical structure of the driving space and Viterbi algorithm is used for terrain classification. Then the navigation decision is given based on the perception of the complex environment. Experiment results show that the method can give an accurate environment description for ALV.

关键词： terrain perception sensor fusion feature extraction principal component analysis multihidden markov models

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Adaptive robust control for electric linear actuator using modified LuGre model with fast load-based parameter estimation

Adaptive robust control for electric linear actuator using m...

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Chinese control Conference (CCC)

作者： Renjian Hao Junzheng Wang Jiangbo Zhao Key laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing P. R. China

This paper addresses the position tracking control problem of electric linear actuator in the presence of nonlinearities due to its transmission process. A torque decoupling approach for electric linear actuator is proposed to achieve respective compensation. To improve the speed of time varying parameters estimating, a load-based adaption law is proposed by designing a new projection mapping which has both variable bounds and good robust performance. An adaptive robust controller is designed such that it combines decoupled torque and dead-zone compensation to preserve robustness to both parametric and nonparametric uncertainties. The modified LuGre model is used for friction compensation making a continuous transition from static model. A Lyapunov stability analysis demonstrates that all signals including tracking errors have guaranteed convergent and bounded performance. The co-simulation results show the effectiveness and the achievable control performance of the proposed control strategy with sinusoidal and point-to-point tracking experiments.

关键词： Friction Torque Load modeling Force Mathematical model Robustness Actuators

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3D Semantic Mapping Based on Convolutional Neural Networks

3D Semantic Mapping Based on Convolutional Neural Networks

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Chinese control Conference

作者： Jing Li Yanyu Liu Junzheng Wang Min Yan Yanzhi Yao Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing P. R. China

As an important part of environmental perception, maps guarantee the accuracy of intelligent robots in navigation, localization and path planning. The traditional 3D maps mainly focus on the spatial structure of the objects, which lacks the semantic information. A method is proposed in the paper, this method combines convolutional neural networks (CNNs) and Simultaneous Localization and Mapping (SLAM) to create global dense 3D semantic maps for indoor scenes. The deep neural network that includes convolution and deconvolution is designed to predict semantic category of every pixel. RGB-D camera is used to obtain scene information, accomplish localization and build 3D maps simultaneously. The semantic information is integrated into the 3D scene, we present an octree map method to replace traditional point clouds method, which can reduce the error from pose estimation and single frame labeling. By this method, the accuracy of semantic information is greatly improved.

关键词： Three-dimensional displays Semantics Cameras Simultaneous localization and mapping Octrees Feature extraction

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