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Parallel Seeds:From Foundation Models to Foundation Intelligence for Agricultural Sustainability

IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 481-484页

作者： Laiyi Fu Shunkang Ling Danyang Wu Mengzhen Kang Fei-Yue Wang Hequan Sun the Shool of Automation Science and Engineering Faculty of Electronic and Information Engineering Xi'an Jiaotong University the College of Information Engineering Northwest A&F University IEEE the State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences

THE development of agriculture faces significant challenges due to population growth, climate change, land depletion, and environmental pollution, threatening global food security [1]. This necessitates the development of sustainable agriculture, where a fundamental step is crop breeding to improve agronomic or economic traits, e.g., increasing yields of crops while decreasing resource usage and minimizing pollution to the environment [2].

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Efficient-Learning Grasping and Pushing in Dense Stacking via Mask Function and Pixel Overlap Rate 7

Efficient-Learning Grasping and Pushing in Dense Stacking vi...

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7th International Symposium on Autonomous Systems, ISAS 2024

作者： Lian, Jie Jiang, Juncheng Qiu, Chaochao Pan, Qinghui Dong, Yongxiang Wang, Zhao Wang, Dong Dalian University of Technology School of Control Science and Engineering Dalian China University of Science and Technology Liaoning Shool of Computer Science and Software Engineering China

ISBN: (纸本)9798350363173

In the field of robotic grasping, grasping tightly stacked objects is a formidable challenge. The presence of non-target objects significantly increases the risk of grasping failure. To solve this problem, the aim is to take action while grasping, reduce clutter, and effectively complete grasping tasks. Based on deep reinforcement learning, the Efficient Learning Grasping(ELG) framework is proposed that integrates pushing actions alongside grasping to efficiently pick up objects from cluttered environments with reduced training time. However, in the process of grasping, the agent is rewarded only when the grasp is successful, so the data collection is extremely inefficient and spends a lot of time on the training of grasping strategy. In our work, two strategies are proposed to improve the training efficiency. First, two mask functions are introduced as prior knowledge to enable the agent to focus on more meaningful regions while ignoring some unnecessary regions, aiming at effective learning. Second, The Pixel Overlap Rate (POR) is introduced to quantify the environment clutter level, and set a new push action reward function based on the POR. The implementation of the above ideas in a simulation environment and transferred the learned models to the real world and verified them in practice. Compared with existing method, our method improves the training efficiency of the initial algorithm while having a higher success rate of grasping. Detailed grasping video at https://***/CqtSvaVl60M. © 2024 IEEE.

关键词： Reinforcement learning

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An IRVS based human-machine interaction system using head-and-eye coordination movement

An IRVS based human-machine interaction system using head-an...

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2009 International Workshop on Intelligent Systems and Applications, ISA 2009

作者： Sheng, He Yu, Lei Yong-xin, Ma Yun, Meng Lei, Huang School of Instrument Science and Opto-electronic Engineering Beihang University Beijing China School of Mechanical and Electronic Control Engineering Beihang University Beijing Jiaotong University Beijing China Shool of Computer Engineering and Science Beijing China Shool of Mechanical engineering and Automation Beihang University Beijing China

ISBN: (纸本)9781424438945

In this paper we introduce an eye-gaze tracking system using the changes of the user's head position. The system presents a new optical structure. In this structure we propose an algorithm based on the projection of the line of sight. With this algorithm, we can say goodbye to complicated arithmetic operations, and improve the system's response time, which indeed, ensures synchronization. We modify the algorithm so the system can match eye features of Asian users. Test of the system shows it has high accuracy and a good real-time response, which makes the users feel more comfortable when they are using this system. © 2009 IEEE.

关键词： Human computer interaction

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Persistent Tracking of a Dynamic Target by a Mobile Robot 33

Persistent Tracking of a Dynamic Target by a Mobile Robot

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第三十三届中国控制会议

作者： LIANG Xiao FANG Yongchun YANG Dedong Institute of Robotics and Automatic Information System Nankai University Tianjin Key Laboratory of Intelligent Robotics Nankai University Shool of Control Science and Engineering Hebei University of Technology

ISBN: (纸本)9781479947249

A novel pursuing algorithm, together with a new experiment method, is introduced to drive a nonholonomic mobile robot tracking a dynamic target in the framework of pursuit-evasion game. Specifically, a pan-tilt with an on-board camera is attached to the mobile robot to construct a tracking system, which greatly improves the maneuverability compared with the traditional method. To keep the target close enough to the vision center of the camera, a control technique is devised according to its kinematic model and Lyapunov theory. By utilizing game theory, the viability set is determined. A tracking controller is employed to guarantee persistent tracking for the dynamic target, where the relative position between the target and the robot is successfully acquired from the visual measurements by the utilization of geometric analysis. Both simulation and experimental results are provided to illustrate the performance of the controller.

关键词： Nonholonomic Constraint,Camera Tracking,Mobile control,Lyapunov Theory

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On initial value problem for fractional-order Kalman filters of linear continuous-time fractional-order systems 10

On initial value problem for fractional-order Kalman filters...

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10th IEEE Data Driven control and Learning Systems Conference, DDCLS 2021

作者： Yang, Chuang Gao, Zhe Ma, Xiaoou Miao, Yue Shool of Mathematics Liaoning University Shenyang110036 China College of Light Industry Liaoning University Shenyang110036 China Department of Control Science and Engineering Jilin University Changchun130025 China Liaoning Science and Technology Museum Shenyang110067 China

ISBN: (纸本)9781665424233

To realize the state estimation of linear continuous-time fractional-order systems, the fractional-order Kalman filter (FOKF) is designed to solve problem on the initial value influence. By using the model transformation, an equivalent equation is obtained such that the state estimation of the transformed model is independent of the initial value. The dimension of the equivalent equation is the same as that of the original system, and the proposed FOKF algorithm based on equivalent equation can effectively reduce the initial value influence on the state estimation. Finally, the effectiveness of the solutions for initial value problem for FOKF is validated by the given simulation example. © 2021 IEEE.

关键词： State estimation

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Efficient-Learning Grasping and Pushing in Dense Stacking via Mask Function and Pixel Overlap Rate

Efficient-Learning Grasping and Pushing in Dense Stacking vi...

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International Symposium on Autonomous Systems (ISAS)

作者： Jie Lian Juncheng Jiang Chaochao Qiu Qinghui Pan Yongxiang Dong Zhao Wang Dong Wang School of Control Science and Engineering Dalian University of Technology Dalian China Shool of Computer Science and Software Engineering University of Science and Technology Liaoning

ISBN: (数字)9798350363173

ISBN: (纸本)9798350363180

关键词： Training Stacking Grasping Production Data collection Deep reinforcement learning Classification algorithms

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Robust Stabilizing control for Oscillatory Base Manipulators by Implicit Lyapunov Method

Research Square

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Research Square 2021年

作者： Guo, Yufei Hou, Baolin Xu, Shengyue Mei, Ruilin Wang, Zhigang Huynh, Van Thanh Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education School of Machinery and Automation Wuhan University of Science and Technology Wuhan430081 China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan430081 China Shool of Mechanical Engineering Nanjing University of Science and Technology Nanjing210094 China Shool of Engineering Deakin University GeelongVIC3217 Australia

Oscillatory base manipulators (OBMs) are a kind of mechanical systems suffering from unexpected base oscillations. The oscillations affect tremendously system stability. Various control methods have been explored, but most of them require measurement or prediction of the oscillations. This study is concerned with a novel OBM–the autoloader, which are used in modern, autonomous main battle tanks. The base oscillation of the autoloader is hard to be obtained in practice. Furthermore, control synthesis for autoloaders is complicated with intrinsic payload uncertainty and actuator saturation. To address these issues, a novel robust control scheme is proposed in this work relying on the implicit Lyapunov method. Moreover, a novel two-Degree-of-Freedom manipulator operating on a vibrating base is constructed to realize the proposed control. To the best of the authors’ knowledge, this is the first study considering both control and hardware implementation for the OBM-like autoloaders. Experimental results demonstrate that, although without prior information of the base oscillation, the proposed controller exhibits good robustness against the base oscillation and payload uncertainty. © 2021, CC BY.

关键词： Manipulators

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Persistent tracking of a dynamic target by a mobile robot

Persistent tracking of a dynamic target by a mobile robot

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Chinese control Conference (CCC)

作者： Xiao Liang Yongchun Fang Dedong Yang Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin P. R. China Shool of Control Science and Engineering Hebei University of Technology Tianjin P. R. China

关键词： Target tracking Mobile robots Games Robot kinematics Heuristic algorithms

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