文献类型： 外文期刊
作者： Li, Tao 1 ; Yu, Jinpeng 2 ; Qiu, Quan 4 ; Zhao, Chunjiang 1 ;
作者机构： 1.Beijing Acad Agr & Forestry Sci, Intelligent Equipment Res Ctr, Beijing 100097, Peoples R China
2.Qingdao Univ, Sch Automat, Qingdao 266071, Peoples R China
3.Shandong Key Lab Ind Control Technol, Qingdao 266071, Peoples R China
4.Beijing Inst Petrochem Technol, Acad Artificial Intelligence, Beijing 102617, Peoples R China
关键词： Depth camera; object detection; robotics; tracking control; uncalibrated system; visual servoing (VS)
期刊名称：IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS （ 影响因子：7.7； 五年影响因子：8.6 ）
ISSN： 0278-0046
年卷期： 2023 年 70 卷 3 期
页码：
收录情况： SCI
摘要： Visual servoing (VS) control has seen wide adoption in harvesting robots. However, parameter calibration is cumbersome, which makes the use of VS robotic systems inconvenient. Besides, dynamic fruits usually lead to a degeneration of control while tracking. To overcome the drawbacks, we present a new image-based uncalibrated visual servoing (IBUVS) control approach, consisting of a hybrid visual configuration and an adaptive tracking controller, referred to as hybrid-IBUVS. Specifically, our hybrid-IBUVS employs an eye-in-hand camera and a fixed red-green-blue-depth camera to construct a hybrid VS system, basing on multiobject detection and edge-computing technologies. Meanwhile, we also propose adaptive laws to online estimate the uncalibrated parameters of the cameras and robot dynamics. Furthermore, our hybrid-IBUVS uses an adaptive tracking controller to guarantee the harvesting robot to track a predefined trajectory to approach a fruit target. By Lyapunov stability theory, asymptotic convergence of the proposed control scheme is rigorously proven. Experimental results demonstrate the effectiveness of the proposed scheme. All shown results supported the research claims.
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