Novel hybrid adaptive controller for manipulation in complex perturbation environments

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 simulat...

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Bibliographic Details
Published in:PloS one 2015-06, Vol.10 (6), p.e0129281-e0129281
Main Authors: Smith, Alex M C, Yang, Chenguang, Ma, Hongbin, Culverhouse, Phil, Cangelosi, Angelo, Burdet, Etienne
Format: Article
Language:English
Subjects:
Adaptation
Adaptive control
Algorithms
Automation
Computer Simulation
Controllers
Design
Distance learning
Environment
Fuzzy control
Fuzzy Logic
Fuzzy sets
Humans
Hybrid control
Kinematics
Learning
Metabolism
Models, Theoretical
Nervous system
Robot arms
Robotics
Robotics - instrumentation
Robotics - methods
Robots
Tracking control
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Summary: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.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0129281