Novel Hybrid Adaptive Controller for Manipulation in Complex Perturbation Environments - Chenguang Yang (PLOS ONE, 2015)
In this paper we present a hybrid control scheme, combining the advantages of task-spaceand joint-space control. The controller is based on a human-like adaptive design, which minimisesboth control effort and tracking error. Our novel hybrid adaptive controller has beentested in extensive simulations, in a scenario where a Baxter robot manipulator is affectedby external disturbances in the form of interaction with the environment and tool-like end-effectorperturbations. The results demonstrated improved performance in the hybrid controllerover both of its component parts. In addition, we introduce a novel method for onlineadaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledgefrom the experimenter. This mechanism of meta-learning induces further improvementin performance and avoids the need for tuning through trial testing.