Online parameter adaptive control of mobile robots based on deep reinforcement learning under multiple optimisation objectives

Abstract Fixed control parameters and various optimisation objectives significantly limit the robot control performance. To address such issues, a parameter adaptive controller based on deep reinforcement learning is introduced firstly to adjust control parameters according to the real‐time system s...

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Main Authors: Xiuli Sui, Haiyong Chen
Format: Article
Language:English
Published: Wiley 2024-12-01
Series:Cognitive Computation and Systems
Subjects:
Online Access:https://doi.org/10.1049/ccs2.12105
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author Xiuli Sui
Haiyong Chen
author_facet Xiuli Sui
Haiyong Chen
author_sort Xiuli Sui
collection DOAJ
description Abstract Fixed control parameters and various optimisation objectives significantly limit the robot control performance. To address such issues, a parameter adaptive controller based on deep reinforcement learning is introduced firstly to adjust control parameters according to the real‐time system state. Further, multiple evaluation mechanisms are constructed to take account of optimisation objectives so that the controller can adapt to different control performance indexes by different evaluation mechanisms. Finally, the target pedestrian tracking control with mobile robots is selected as the validation case study, and the Proportional‐Derivative Controller is chosen as the foundation controller. Several simulation and experimental examples are designed, and the results demonstrate that the proposed method shows satisfactory performance while taking account of multiple optimisation objectives.
format Article
id doaj-art-f56dd46aa1f94f888b0905ac5d6f6e21
institution Kabale University
issn 2517-7567
language English
publishDate 2024-12-01
publisher Wiley
record_format Article
series Cognitive Computation and Systems
spelling doaj-art-f56dd46aa1f94f888b0905ac5d6f6e212024-12-26T15:31:31ZengWileyCognitive Computation and Systems2517-75672024-12-0164869710.1049/ccs2.12105Online parameter adaptive control of mobile robots based on deep reinforcement learning under multiple optimisation objectivesXiuli Sui0Haiyong Chen1Software & Communication School Tianjin Sino‐German University of Applied Sciences Tianjin ChinaSchool of Artificial Intelligence Hebei University of Technology Tianjin ChinaAbstract Fixed control parameters and various optimisation objectives significantly limit the robot control performance. To address such issues, a parameter adaptive controller based on deep reinforcement learning is introduced firstly to adjust control parameters according to the real‐time system state. Further, multiple evaluation mechanisms are constructed to take account of optimisation objectives so that the controller can adapt to different control performance indexes by different evaluation mechanisms. Finally, the target pedestrian tracking control with mobile robots is selected as the validation case study, and the Proportional‐Derivative Controller is chosen as the foundation controller. Several simulation and experimental examples are designed, and the results demonstrate that the proposed method shows satisfactory performance while taking account of multiple optimisation objectives.https://doi.org/10.1049/ccs2.12105learning (artificial intelligence)mobile robots
spellingShingle Xiuli Sui
Haiyong Chen
Online parameter adaptive control of mobile robots based on deep reinforcement learning under multiple optimisation objectives
Cognitive Computation and Systems
learning (artificial intelligence)
mobile robots
title Online parameter adaptive control of mobile robots based on deep reinforcement learning under multiple optimisation objectives
title_full Online parameter adaptive control of mobile robots based on deep reinforcement learning under multiple optimisation objectives
title_fullStr Online parameter adaptive control of mobile robots based on deep reinforcement learning under multiple optimisation objectives
title_full_unstemmed Online parameter adaptive control of mobile robots based on deep reinforcement learning under multiple optimisation objectives
title_short Online parameter adaptive control of mobile robots based on deep reinforcement learning under multiple optimisation objectives
title_sort online parameter adaptive control of mobile robots based on deep reinforcement learning under multiple optimisation objectives
topic learning (artificial intelligence)
mobile robots
url https://doi.org/10.1049/ccs2.12105
work_keys_str_mv AT xiulisui onlineparameteradaptivecontrolofmobilerobotsbasedondeepreinforcementlearningundermultipleoptimisationobjectives
AT haiyongchen onlineparameteradaptivecontrolofmobilerobotsbasedondeepreinforcementlearningundermultipleoptimisationobjectives