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Multiple Time-Varying Formation of Networked Heterogeneous Robotic Systems via Estimator-Based Hierarchical Cooperative Algorithms

Ming‐Feng Ge, Chang‐Duo Liang, Xisheng Zhan, Chaoyang Chen, Guanghui Xu, Jie Chen

Year
2020
Citations
5
Access
Open access

Abstract

This paper investigates both the time-varying formation and multiple time-varying formation tracking problems of networked heterogeneous robotic systems (NHRSs) with parameter uncertainties and external disturbances in the task space. Each robot inside can be either redundant or nonredundant. Several novel estimator-based hierarchical cooperative (EBHC) algorithms are designed to achieve both the tracking task and the possible preset subtasks for redundant robots. Besides, the designed estimator algorithms guarantee that each robot can obtain the accurate information of their corresponding leaders. By employing Lyapunov stability and input-to-state stability, sufficient conditions on the asymptotic stability of the error closed-loop system are derived. Finally, two simulation examples are presented to verify the effectiveness of the proposed algorithms.

Keywords

EstimatorComputer scienceStability (learning theory)RobotState estimatorTask (project management)Control theory (sociology)Lyapunov functionRobot manipulatorTracking (education)

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