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IEEE/RSJ International Conference on intelligent Robots and systems, IROS 2015

作者： Yi, Yang Geng, Zhou Zhang, Jianqing Cheng, Siyuan Fu, Mengyin School of Automation and State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781479999941

This paper describes a novel amphibious robot, which adopts a dual-swing-legs propulsion mechanism, proposing a new locomotion mode. The robot is called FroBot, since its structure and locomotion are similar to frogs. Our inspiration comes from the frog scooter and breaststroke. Based on its swing leg mechanism, an unusual universal wheel structure is used to generate propulsion on land, while a pair of flexible caudal fins functions like the foot flippers of a frog to generate similar propulsion underwater. On the basis of the prototype design and the dynamic model of the robot, some locomotion control simulations and experiments were conducted for the purpose of adjusting the parameters that affect the propulsion of the robot. Finally, a series of underwater experiments were performed to verify the design feasibility of FroBot and the rationality of the control algorithm. © 2015 IEEE.

关键词： Propulsion

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key technologies of GNSS/INS/VO deep integration for UGV navigation in urban canyon 11

Key technologies of GNSS/INS/VO deep integration for UGV nav...

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2017 11th Asian control Conference, ASCC 2017

作者： Meiling, Wang Yafeng, Li Guoqiang, Feng Yi, Yang Tong, Liu Xiao, Xuan School of Automation State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781509015733

As a new emerging integrated navigation technology, the GNSS/INS/VO deep integration system can fully leverage the synergistic and complementary characteristics of the three involved subsystems to achieve cost reduction while improving navigation accuracy, availability, and robustness, by mutual aiding between subsystems. In this paper, firstly, based on a brief review of the technical background and research status of the GNSS/INS/VO deep integration technology, the processing flows of this deep integration mode in both signal and information domains are analyzed, and its performance advantages are summarized. Then, the top-level technology roadmap of the GNSS/INS/VO deep integration for UGV navigation in the urban canyon is presented, and several key technical issues from scheme demonstration to engineering implementation are explored. At last, the short and medium term development prospects of the GNSS/INS/VO deep integration are envisaged. The proposed research ideas and system design concept for GNSS/INS/VO deep integration could be used as a reference for relevant technicians in navigation field. © 2017 IEEE.

关键词： Navigation

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Target tracking trajectory generation for quadrotors in static complex environments 4

Target tracking trajectory generation for quadrotors in stat...

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4th International Conference on Industrial Artificial Intelligence, IAI 2022

作者： Ji, Yang School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System Beijing100081 China

ISBN: (数字)9781665451208

ISBN: (纸本)9781665451208

This paper mainly focuses on the problem of target tracking trajectory generation for quadrotors in static complex environments. In this paper, a trajectory planning framework is proposed that can be used to address the occlusion problem caused by obstacles in target tracking situations. The main innovations are: First, a visibility function is introduced that is constructed based on a signed Euclidean distance field (ESDF) map. Based on this function, the favorable view direction is derived to track the target distinctly. Second, the distance between the target and chaser is optimized as one of the cost functions, resulting in a smooth and comfortable distance between them. Finally, the effectiveness of the algorithm is verified on the Rviz platform. © 2022 IEEE.

关键词： Target tracking

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Dynamic multi-team antagonistic games model with incomplete information and its application to multi-UAV

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IEEE/CAA Journal of Automatica Sinica 2015年第1期2卷 74-84页

作者： Zha, Wenzhong Chen, Jie Peng, Zhihong School of Automation Beijing Institute of Technology Beijing100081 China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

At present, the studies on multi-team antagonistic games (MTAGs) are still in the early stage, because this complicated problem involves not only incompleteness of information and conflict of interests, but also selection of antagonistic targets. Therefore, based on the previous researches, a new framework is proposed in this paper, which is dynamic multi-team antagonistic games with incomplete information (DMTAGII) model. For this model, the corresponding concept of perfect Bayesian Nash equilibrium (PBNE) is established and the existence of PBNE is also proved. Besides, an interactive iteration algorithm is introduced according to the idea of the best response for solving the equilibrium. Then, the scenario of multiple unmanned aerial vehicles (UAVs) against multiple military targets is studied to solve the problems of tactical decision making based on the DMTAGII model. In the process of modeling, the specific expressions of strategy, status and payoff functions of the games are considered, and the strategy is coded to match the structure of genetic algorithm so that the PBNE can be solved by combining the genetic algorithm and the interactive iteration algorithm. Finally, through the simulation the feasibility and effectiveness of the DMTAGII model are verified. Meanwhile, the calculated equilibrium strategies are also found to be realistic, which can provide certain references for improving the autonomous ability of UAV systems. © 2014 Chinese Association of Automation.

关键词： Genetic algorithms

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Small-scale intersection scan model for UGV in urban environment

Small-scale intersection scan model for UGV in urban environ...

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2017 American control Conference, ACC 2017

作者： Yang, Yi Hao, Li Zhu, Hao Ningyi, Lyu Wenjie, Song School of Automation State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781509059928

Intersection detection is a critical capacity for an Unmanned Ground Vehicle (UGV) to drive safely in structured urban environment. Large-scale intersections stamped on maps have plenty of features for detection while some unmapped small-scale urban intersections are hard to be identified. In this paper, we propose a novel intersection detection method conducted on the basis of Hidden Markov Model (HMM). This method is based on the intersection scan model to obtain the traversable directions to classify the intersection. The scan model is effective in dealing with both LIDAR and visual data. Combination of the scan model and the HMM can accurately estimate the traversable directions in consideration of both real-time and historic data. Results from simulations and real-world experiments have shown the functionality of the presented approach. © 2017 American Automatic control Council (AACC).

关键词： Hidden Markov models

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UAV-aided Large-scale Map Building and Road Extraction for UGV 7

UAV-aided Large-scale Map Building and Road Extraction for U...

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7th IEEE Annual International Conference on CYBER Technology in Automation, control, and intelligent systems, CYBER 2017

作者： Meiling, Wang Huachao, Yu Guoqiang, Feng Yi, Yang Yafeng, Li Tong, Liu School of Automation Beijing Institute of Technology State Key Laboratory of Complex System Intelligent Control and Decision Beijing100081 China

ISBN: (纸本)9781538604892

Due to the limited visual field of UGV, it is difficult to detect the accessible zone in a wide range of area in real time. This paper proposes a UAV-aided autonomous road network construction method where roads are previously unknown for UGV navigation. First, SIFT and RANSAC algorithms are applied to obtain the homography of UAV sequential images, through which these images are stitched to a large-scale map. Next, least square fitting algorithm and RDP algorithm are applied to extract initial road area and then obtain road network suitable for UGV navigation by topological processing and skeleton extraction. The experiments show that this UAV-aided method is effective in generating a large-scale road network map for UGV driving through unknown environment without human intervention. © 2017 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Object tracking based on multi-bandwidth mean shift with convergence acceleration

Object tracking based on multi-bandwidth mean shift with con...

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2nd International Conference on Image Analysis and Signal Processing, IASP'2010

作者： Bin, Zhou Jun-Zheng, Wang Wei, Shen Key Laboratory of Complex System Intelligent Control and Decision School of Automatic Control Beijing Institute of Technology Beijing China

ISBN: (纸本)9781424455553

A multi-bandwidth based tracking algorithm was proposed to search for the global kernel mode when the probability density has multiple peak modes. Firstly, a monotonically decreasing sequence of bandwidths was fixed according to the target scale. At each bandwidth, using mean shift to And out the maximum probability, and starting the next iteration at the previous convergence location. Finally, the best optimal mode could be obtained at the last bandwidth. To accelerate the convergence, over-relaxed strategy was introduced to enlarge the step size. Under the convergence rule, the learning rate was adaptively adjusted by Bhattacharyya coefficients of consecutive iteration convergence. The experimental results show that the proposed multi-bandwidth mean shift tracker is robust in high-speed object tracking, and perform well in occlusions. The adaptive over-relaxed strategy is effective to lower the convergence iterations by enlarging the step size. © 2010 IEEE.

关键词： Bandwidth

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Stabilization of Perturbed Continuous-Time systems Using Event-Triggered Model Predictive control

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IEEE Transactions on Cybernetics 2022年第5期52卷 4039-4051页

作者： Wang, Mengzhi Sun, Jian Chen, Jie Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex System Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China

In this article, event-triggered model predictive control (EMPC) of continuous-time nonlinear systems with bounded disturbances is studied. Two novel event-triggered control schemes are proposed. In the first strategy, an event-triggering condition, designed based on the state error between the actual system state and the optimal one, with an absolute threshold is considered. In the second strategy, an event-triggering condition with a mixed threshold is designed to further save the computational resources. The minimal interevent times of both event-triggered control schemes are obtained to avoid the Zeno behavior. Sufficient conditions of recursive feasibility for these two triggering strategies, which refer to the prediction horizon, the triggering level, and the disturbance bound, are obtained, respectively. Input-to-state practical stability (ISpS) of both event-triggered control systems is established without requiring the system state entering the terminal set in finite time, respectively. Finally, the numerical simulation shows the effectiveness of the proposed methods. © 2013 IEEE.

关键词： Model predictive control

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High-adaption locomotion with stable robot body for planetary exploration robot carrying potential instruments on unstructured terrain

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Chinese Journal of Aeronautics 2021年第5期34卷 652-665页

作者： Kang XU Shoukun WANG Junzheng WANG Xiuwen WANG Zhihua CHEN Jinge SI School of Automation Beijing Institute of Technology.Beijing 100081China Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of TechnologyBeijing 100081China Key Laboratory Ministry of Industry and Information Technology Beijing Institute of TechnologyBeijing 100081China

There is a strong demand for Planetary Exploration Mobile robots(PEMRs)that have the capability of the traversability,stability,efficiency and high load while tackling the specialized tasks on planet *** this paper,an electric parallel wheel-legged hexapod robot which has high-adaption locomotion on the unstructured terrain is ***,the hybrid control framework,which enables robot to stably carry the heavy loads as well as to traverse the uneven terrain by utilizing both legged and wheeled locomotion,is also *** on this framework,robot controls the multiple DOF leg for performing high-adaption locomotion to negotiate obstacles via Gait Generator(GG).Additionally,by using Whole-Body control(WBC)of framework,robot has the capability of flexibly accommodating the uneven terrain by Attitude control(AC)kinematically adjusting the length of legs like an active suspension system,and by Force/torque Balance control(FBC)equally distributing the Ground Reaction Force(GRF)to maintain a stable *** simulation and experiment are employed to validate the proposed framework with the physical system in the planetary analog ***,to smoothly demonstrate the performance of robot transporting heavy loads,the experiment of carrying 3-person load of about 240 kg is deployed.

关键词： Attitude control Gait generation High-adaption locomotion Obstacle avoidance Planetary exploration robot

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TIEA: A tradeoff-based interactive multiobjective evolutionary algorithm 7

TIEA: A tradeoff-based interactive multiobjective evolutiona...

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7th International Symposium on Computational Intelligence and Industrial Applications, ISCIIA 2016

作者： Chen, Lu Xin, Bin Chen, Jie School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex System Beijing China

ISBN: (纸本)9784990534349

This paper proposes a tradeoff based interactive multiobjective evolutionary algorithm (TIEA). It can support the decision maker (DM) to guide the search towards the DM's most preferred solution by combing evolutionary algorithms with the framework of gradient projection. At each iteration, an evolutionary algorithm is used to generate an approximate Pareto optimal solution. Then, the DM is asked to provide preferences in terms of indifference tradeoffs, the projection of which onto the tangent hyperplane of the Pareto front provides a tradeoff direction. To calculate the projection, an approach to approximate the normal vector of the tangent hyperplane of the Pareto front is developed. Results on nine numerical examples by using TIEA show that TIEA is able to solve multiobjective optimization problems with more than three objectives. Moreover, it can find the Pareto optimal solution that the DM prefers most. © 2016, Fuji Technology Press. All rights reserved.

关键词： Evolutionary algorithms

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