title: Novel hybrid adaptive controller for manipulation in complex perturbation environments.
abstract: In this paper we present a hybrid control scheme, combining the advantages of task-space and joint-space control. The controller is based on a human-like adaptive design, which minimises both control effort and tracking error. Our novel hybrid adaptive controller has been tested in extensive simulations, in a scenario where a Baxter robot manipulator is affected by external disturbances in the form of interaction with the environment and tool-like end-effector perturbations. The results demonstrated improved performance in the hybrid controller over both of its component parts. In addition, we introduce a novel method for online adaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledge from the experimenter. This mechanism of meta-learning induces further improvement in performance and avoids the need for tuning through trial testing.
authors.affiliation: Centre for Robotics and Neural Systems, Plymouth University, Plymouth, UK.
authors.forename: Alex M C
authors.initials: AM
authors.lastname: Smith
authors.affiliation: Centre for Robotics and Neural Systems, Plymouth University, Plymouth, UK; College of Automation Science and Engineering, South China University of Technology, Guangzhou, China.
authors.forename: Chenguang
authors.initials: C
authors.lastname: Yang
authors.affiliation: State Key Laboratory of Intelligent Control and Decision of Complex Systems, Beijing Institute of Technology, Beijing, China; School of Automation, Beijing Institute of Technology, Beijing, China.
authors.forename: Hongbin
authors.initials: H
authors.lastname: Ma
authors.affiliation: Centre for Robotics and Neural Systems, Plymouth University, Plymouth, UK.
authors.forename: Phil
authors.initials: P
authors.lastname: Culverhouse
authors.affiliation: Centre for Robotics and Neural Systems, Plymouth University, Plymouth, UK.
authors.forename: Angelo
authors.initials: A
authors.lastname: Cangelosi
authors.affiliation: Department of Bioengineering, Imperial College London, London, UK.
authors.forename: Etienne
authors.initials: E
authors.lastname: Burdet
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D004777:Environment; D017143:Fuzzy Logic; D006801:Humans; D007858:Learning; D008962:Models, Theoretical; D012371:Robotics / Q000295:instrumentation* / Q000379:methods