LiDAR Based Trajectory-Tracking of an Autonomous Differential Drive Mobile Robot Using Fuzzy Sliding Mode Controller
This study aims to achieve the trajectory-tracking of an autonomous differential drive mobile robot (ADDMR) in the presence of friction torques using the proposed Fuzzy Sliding-Mode Control (FSMC). First, the complete model of the ADDMR is established including kinematic, dynamic and actuator models...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2022-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9741783/ |
| _version_ | 1818367176976891904 |
|---|---|
| author | Hsiu-Ming Wu Muhammad Qomaruz Zaman |
| author_facet | Hsiu-Ming Wu Muhammad Qomaruz Zaman |
| author_sort | Hsiu-Ming Wu |
| collection | DOAJ |
| description | This study aims to achieve the trajectory-tracking of an autonomous differential drive mobile robot (ADDMR) in the presence of friction torques using the proposed Fuzzy Sliding-Mode Control (FSMC). First, the complete model of the ADDMR is established including kinematic, dynamic and actuator models. Then, the desired trajectory is planned and generated via Bézier curve combined with cubic time mapping. The localization of the ADDMR is performed using the Monte Carlo Localization (MCL) technique and LiDAR point cloud data. Subsequently, the proposed FSMC utilizes nonlinear sliding surfaces inferred based on fuzzy logic to asymptotically attain the pose convergence. To investigate the feasibility and robustness of the proposed FSMC, simulations and experiments are conducted under different operation conditions. The results show that the proposed FSMC using LiDAR data in the feedback leads to excellent control performance even in the presence of friction torques. It was also shown through simulations and experiments that the established ADDMR model fits the actual ADDMR model very well. |
| first_indexed | 2024-12-13T22:47:54Z |
| format | Article |
| id | doaj.art-8839a51728644f339501c015ac87c542 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-13T22:47:54Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-8839a51728644f339501c015ac87c5422022-12-21T23:28:41ZengIEEEIEEE Access2169-35362022-01-0110337133372210.1109/ACCESS.2022.31622449741783LiDAR Based Trajectory-Tracking of an Autonomous Differential Drive Mobile Robot Using Fuzzy Sliding Mode ControllerHsiu-Ming Wu0https://orcid.org/0000-0001-5708-6114Muhammad Qomaruz Zaman1https://orcid.org/0000-0003-4637-3016Department of Intelligent Automation Engineering, National Taipei University of Technology, Taipei, TaiwanGraduate Institute of Manufacturing Technology, National Taipei University of Technology, Taipei, TaiwanThis study aims to achieve the trajectory-tracking of an autonomous differential drive mobile robot (ADDMR) in the presence of friction torques using the proposed Fuzzy Sliding-Mode Control (FSMC). First, the complete model of the ADDMR is established including kinematic, dynamic and actuator models. Then, the desired trajectory is planned and generated via Bézier curve combined with cubic time mapping. The localization of the ADDMR is performed using the Monte Carlo Localization (MCL) technique and LiDAR point cloud data. Subsequently, the proposed FSMC utilizes nonlinear sliding surfaces inferred based on fuzzy logic to asymptotically attain the pose convergence. To investigate the feasibility and robustness of the proposed FSMC, simulations and experiments are conducted under different operation conditions. The results show that the proposed FSMC using LiDAR data in the feedback leads to excellent control performance even in the presence of friction torques. It was also shown through simulations and experiments that the established ADDMR model fits the actual ADDMR model very well.https://ieeexplore.ieee.org/document/9741783/Autonomous differential drive mobile robotfuzzy sliding-mode controlMonte Carlo localizationnonlinear sliding surfaceBézier curve |
| spellingShingle | Hsiu-Ming Wu Muhammad Qomaruz Zaman LiDAR Based Trajectory-Tracking of an Autonomous Differential Drive Mobile Robot Using Fuzzy Sliding Mode Controller IEEE Access Autonomous differential drive mobile robot fuzzy sliding-mode control Monte Carlo localization nonlinear sliding surface Bézier curve |
| title | LiDAR Based Trajectory-Tracking of an Autonomous Differential Drive Mobile Robot Using Fuzzy Sliding Mode Controller |
| title_full | LiDAR Based Trajectory-Tracking of an Autonomous Differential Drive Mobile Robot Using Fuzzy Sliding Mode Controller |
| title_fullStr | LiDAR Based Trajectory-Tracking of an Autonomous Differential Drive Mobile Robot Using Fuzzy Sliding Mode Controller |
| title_full_unstemmed | LiDAR Based Trajectory-Tracking of an Autonomous Differential Drive Mobile Robot Using Fuzzy Sliding Mode Controller |
| title_short | LiDAR Based Trajectory-Tracking of an Autonomous Differential Drive Mobile Robot Using Fuzzy Sliding Mode Controller |
| title_sort | lidar based trajectory tracking of an autonomous differential drive mobile robot using fuzzy sliding mode controller |
| topic | Autonomous differential drive mobile robot fuzzy sliding-mode control Monte Carlo localization nonlinear sliding surface Bézier curve |
| url | https://ieeexplore.ieee.org/document/9741783/ |
| work_keys_str_mv | AT hsiumingwu lidarbasedtrajectorytrackingofanautonomousdifferentialdrivemobilerobotusingfuzzyslidingmodecontroller AT muhammadqomaruzzaman lidarbasedtrajectorytrackingofanautonomousdifferentialdrivemobilerobotusingfuzzyslidingmodecontroller |