學術活動

浙江大學控制科學與工程學院陳劍教授應邀來校講學

作者: | 來源: | 發布日期:2019-05-27
 
學術講座
 
報告題目:智能車和機器人的感知與控制
 
人:陳劍,浙江大學控制科學與工程學院教授
 
報告時間:2019529  下午430
 
報告地點:信息樓417學術會議室
 
報告人介紹:浙江大學控制科學與工程學院教授广东11选5走势图,博導,青年千人計劃,浙江省特聘專家, IEEE Senior Member,中國自動化學會控制理論專委會委員、新能源控制學組主任,浙江省氫電混合動力系統創新團隊負責人。主持和參與自然基金重點項目各一項。主要研究方向包括燃料電池系統控制、機器視覺广东11选5走势图、智能車、電池管理系統广东11选5走势图广东11选5走势图。出版英文學術專著一部,發表了110SCI/EI學術論文。
 
報告摘要:
Abstract: Computer vision provides general and abundant information for the environment and task description. Multiple view geometry can be used for the unified geometric modeling of visual perception and control tasks. In this talk, visual perception and control results of intelligent vehicles and robotics will be presented.
    Visual perception provides the necessary feedback, such as the vehicle’s motion states and drivable road regions, for control systems. Since the 3D information might be lost and image noises exist in the imaging process, the effective pose estimation and motion identification of vehicles are challenging. Besides, intelligent vehicles are generally involved in complex scenarios. Therefore, it is difficult to robustly detect the drivable road space for safe vehicle maneuvers. Optimization and observer theories are applied to reconstruct the geometric information of the scene based on multiple view geometry. Then, real-time vehicle states and drivable road region can be identified effectively based on the reconstructed geometric information.
    Visual control exploits the visual information for task descriptions and for controlling intelligent vehicles and robotics through appropriate visual feedback control laws. Since the depth information is lost in the imaging process of monocular cameras, there exist model uncertainties for the controller design. Moreover, the limited field of view of the camera and the physical non-holonomic constraints of intelligent vehicles also have great influences on the stability and robustness of the closed-loop system. Multiple view geometry is used for the geometric modeling and scaled pose estimation. Then, Lyapunov methods are applied to design stabilizing control laws in the presence of model uncertainties and multiple constraints.

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广东11选5走势图
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