首页|Recent Studies from Nankai University Add New Data to Robotics (Visual Servoing Trajectory Tracking and Depth Identification for Mobile Robots With Velocity Saturation Constraints)
Recent Studies from Nankai University Add New Data to Robotics (Visual Servoing Trajectory Tracking and Depth Identification for Mobile Robots With Velocity Saturation Constraints)
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Data detailed on Robotics have been presented. According to news reporting originating in Tianjin, People’s Republic of China, by NewsRx journalists, research stated, “The paper proposes a novel visual servoing trajectory tracking controller satisfying velocity saturation constraints for mobile robots, which can simultaneously realize the unknown image depth identification. Compared with existing saturation controllers, the boundness of velocity commands can be explicitly determined though the control law is coupled with the unknown depth.” Funders for this research include National Key Research and Development Project, Tianjin Science Fund for Distinguished Young Scholars, National Natural Science Foundation of China (NSFC), Fundamental Research Funds for the Central Universities. The news reporters obtained a quote from the research from Nankai University, “In addition, the asymptotic stability (generally realizing UUB) is achieved theoretically in the presence of both velocity saturation constraints and the unknown depth parameter. To guarantee the velocity commands within the allowed speed limit, the saturation function is introduced into the visual servo control law to reshape tracking errors. Furthermore, to deal with the unknown depth, an adaptive updating law is skillfully constructed, which can simultaneously identify it under the persistent excitation (PE) condition. Also, to explicitly demonstrate the saturation performance of the designed visual servo controller, the boundness of velocity commands is analyzed, following which parameter selection rules are provided. The asymptotic convergence of tracking errors is theoretically proved with Lyapunov techniques.”
TianjinPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningNano-robotRoboticsNankai University
NETL
NSTL
IEEE
