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- 저자 : Hongxuan Ma (검색결과 3 건)
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Hongxuan Ma,Wei Zou,Siyang Sun,Zheng Zhu,Zhaobing Kang 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.11
In visual servoing tasks, it is an important problem to maintain the observability to feature points on objects, which are usually used to calculate the pose between objects and robots. In particular, when the robot’s vision has a limited field of view (FOV) and the points on objects are distributed separately, the problem is more serious. In this paper, based on FOV constraint region analysis and path planning, we propose a novel method for a mobile robot equipped with a pan-tilt camera to keep all points on objects in its view. According to the HorizontalFOV and Vertical-FOV angular aperture of camera, bounding boxes assisting to calculate the regions with FOV constraint are acquired firstly. Then the region where the robot inside it cannot keep all points in its view can be obtained. Finally the mobile robot plans a shortest path from the current position to the destination, which can avoid the region with FOV constraint. The results of simulations and experiments prove that our method can make mobile robot keep all feature points in its view when it is moving.
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Adaptive Trajectory Tracking of Wheeled Mobile Robots Based on a Fisheye Camera
Zhaobing Kang,Wei Zou,Hongxuan Ma,Zheng Zhu 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.9
This paper presents a novel adaptive trajectory tracking control method, which can precisely control wheeled mobile robots only using an uncalibrated fish-eye camera fixed on the ceiling. Different from existing approaches, the inertial device, distorted image correction, and the trajectory expression are not required in the control system. The position and orientation of the mobile robot in the camera coordinate system are estimated by the extended POSIT (Pose from Orthography and Scaling with Iteration) algorithm in real-time. Based on estimation results, the controller considering both tracking errors and parameter estimated errors is designed by linear parameterization, where the camera intrinsic parameters are online updated. The asymptotic convergence of the tracking error and the estimated error to zero is proved by the Barbalat lemma. Circular trajectory and irregular trajectory tracking experiments have been conducted to verify the performance of our controller.
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Auditory Feature Driven Model Predictive Control for Sound Source Approaching
Zhiqing Wang,Wei Zou,Hongxuan Ma,Chi Zhang,Yuxin Guo,Wei Zhang 제어·로봇·시스템학회 2024 International Journal of Control, Automation, and Vol.22 No.2
Sound source approaching is a typical task for the robot with auditory sensing. Many existing methods are based on sound source localization (SSL), and utilize the explicit location as the control input. To reduce the localization computation cost and improve the robustness against noise and reverberation, we propose a novel auditory feature driven model predictive control (AFD-MPC) method, which directly uses the auditory feature as the control input. First, a new convolution-ternarization based interaural time difference (CT-ITD) estimation method is proposed, which is more robust to noise and reverberation by eliminating signal spikes and irrelevant components. Second, a new system model is derived and established, which directly links the robot motions and the interaural time difference (ITD) feature. Third, AFD-MPC is realized based on the proposed CT-ITD feature estimation and system model. The states at multiple future time steps are predicted based on the system model, and a control objective function considering both target approaching and motion smoothness is designed. By involving the multi-step future states in the control objective function, the control outcome is more smooth on motion trajectory and more robust to instantaneous interferences. A series of experiments such as static and dynamic sound source approaching are conducted on a mobile robot equipped with a small-sized 6-microphone array to validate the effectiveness of our methods.
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