ROS-based Controller for a Two-Wheeled Self-Balancing Robot

Juan Díaz-Téllez, Ruben Senen García-Ramírez, Jairo Pérez-Pérez, Jaime Estevez-Carreón, Miguel Angel Carreón-Rosales

Abstract


In this article, a controller based on a Robot Operating System (ROS) for a two-wheeled self-balancing robot is designed. The proposed ROS architecture is open, allowing the integration of different sensors, actuators, and processing units. The low-cost robot was designed for educational purposes. It used an ESP32 microcontroller as the central unit, an MPU6050 Inertial Measurement Unit sensor, DC motors with encoders, and an L298N integrated circuit as a power stage. The mathematical model is analyzed through Newton-Euler and linearized around an equilibrium point. The control objective is to self-balance the robot to the vertical axis in the presence of disturbances. The proposed control is based on a bounded saturation, which is lightweight and easy to implement in embedded systems with low computational resources. Experimental results are performed in real-time under regulation, conditions far from the equilibrium point, and rejection of external disturbances. The results show a good performance, thus validating the mechanical design, the embedded system, and the control scheme. The proposed ROS architecture allows the incorporation of different modules, such as mapping, autonomous navigation, and manipulation, which contribute to studying robotics, control, and embedded systems.


Keywords


Real-Time; ROS; Two-Wheel Self-Balancing; ESP32; Segway; PID

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References


A. Stefek, T. V. Pham, V. Krivanek and K. L. Pham, “Energy Comparison of Controllers Used for a Differential Drive Wheeled Mobile Robot,” in IEEE Access, vol. 8, pp. 170915-170927, 2020, doi: 10.1109/AC- CESS.2020.3023345.

Y. Maddahi and K. Zareinia, “Nonparametric Bootstrap Technique to Improve Positional Accuracy in Mobile Robots with Differential Drive Mechanism,” in IEEE Access, vol. 8, pp. 158502-158511, 2020, doi: 10.1109/ACCESS.2020.3020864.

U. Ruiz, “Capturing a Dubins Car with a Differential Drive Robot,” in IEEE Access, vol. 10, pp. 81805-81815, 2022, doi: 10.1109/AC- CESS.2022.3196342.

Q. Lu, Z. Li, H. Song and C. Y. Su, “Visual Regulation of Differential- Drive Mobile Robots: A Nonadaptive Switching Approach,” in IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 51, no. 11, pp. 6874-6884, Nov. 2021, doi: 10.1109/TSMC.2020.2963889.

F. Ke, Z. Li and C. Yang, “Robust Tube-Based Predictive Control for Visual Servoing of Constrained Differential-Drive Mobile Robots,” in IEEE Transactions on Industrial Electronics, vol. 65, no. 4, pp. 3437- 3446, April 2018, doi: 10.1109/TIE.2017.2756595.

R. Mao and H. Dai, “Distributed Non-Convex Model Predictive Control for Non-Cooperative Collision Avoidance of Networked Differential Drive Mobile Robots,” in IEEE Access, vol. 10, pp. 52674-52685, 2022, doi: 10.1109/ACCESS.2021.3134696.

R. F. Carpio et al., “A Navigation Architecture for Ackermann Vehicles in Precision Farming,” in IEEE Robotics and Automation Letters, vol. 5, no. 2, pp. 1103-1110, April 2020, doi: 10.1109/LRA.2020.2967306.

Y. Gao, Y. Shen, T. Xu, W. Zhang and L. Gu¨venc, “Oscillatory Yaw Motion Control for Hydraulic Power Steering Articulated Vehicles Con- sidering the Influence of Varying Bulk Modulus,” in IEEE Transactions on Control Systems Technology, vol. 27, no. 3, pp. 1284-1292, May 2019, doi: 10.1109/TCST.2018.2803746.

L. Bascetta, D. A. Cucci, and M. Matteucci “Kinematic trajectory tracking controller for an all-terrain Ackermann steering vehicle,” IFAC- PapersOnLine, vol. 49, no. 15, pp. 13-18, 2016.

S. Upadhyay and A. Ratnoo, “A Point-to-Ray Framework for Gen- erating Smooth Parallel Parking Maneuvers,” in IEEE Robotics and Automation Letters, vol. 3, no. 2, pp. 1268-1275, April 2018, doi: 10.1109/LRA.2018.2795655.

M. T. Watson, D. T. Gladwin and T. J. Prescott, “Collinear Mecanum Drive: Modeling, Analysis, Partial Feedback Linearization, and Non- linear Control,” in IEEE Transactions on Robotics, vol. 37, no. 2, pp. 642-658, April 2021, doi: 10.1109/TRO.2020.2977878.

D. U. Rijalusalam and I. Iswanto, “Implementation Kinematics Modeling and Odometry of Four Omni Wheel Mobile Robot on The Trajec- tory Planning and Motion Control Based Microcontroller,” Journal of Robotics and Control (JRC), vol. 2, no. 5, pp. 448-455, 2021.

R. T. Yunardi, D. Arifianto, F. Bachtiar, and J. I. Prananingrum, “Holo- nomic Implementation of Three Wheels Omnidirectional Mobile Robot using DC Motors,” Journal of Robotics and Control (JRC), vol. 2, no. 2, 2021, doi: 10.18196/jrc.2254.

A. Neaz, S. Lee, and K. Nam, “Design and Implementation of an Integrated Control System for Omnidirectional Mobile Robots in Industrial Logistics,” Sensors, vol. 23, no. 6, p. 3184, 2023, doi: 10.3390/s23063184

T. Terakawa, M. Komori, K. Matsuda and S. Mikami, “A Novel Om- nidirectional Mobile Robot with Wheels Connected by Passive Sliding Joints,” in IEEE/ASME Transactions on Mechatronics, vol. 23, no. 4, pp. 1716-1727, Aug. 2018, doi: 10.1109/TMECH.2018.2842259.

S. Lee and D. Chwa, “Dynamic Image-Based Visual Servoing of Monocular Camera Mounted Omnidirectional Mobile Robots Consid- ering Actuators and Target Motion via Fuzzy Integral Sliding Mode Control,” in IEEE Transactions on Fuzzy Systems, vol. 29, no. 7, pp. 2068-2076, July 2021, doi: 10.1109/TFUZZ.2020.2985931.

K. Albert, K. S. Phogat, F. Anhalt, R. N. Banavar, D. Chatterjee and B. Lohmann, “Structure-Preserving Constrained Optimal Trajec- tory Planning of a Wheeled Inverted Pendulum,” in IEEE Trans- actions on Robotics, vol. 36, no. 3, pp. 910-923, June 2020, doi: 10.1109/TRO.2020.2985579.

W. Zhao, X. Wang, B. Qi and T. Runge, “Ground-Level Mapping and Navigating for Agriculture Based on IoT and Computer Vision,” in IEEE Access, vol. 8, pp. 221975-221985, 2020, doi: 10.1109/AC- CESS.2020.3043662.

X. Gao et al., “Review of Wheeled Mobile Robots’ Navigation Problems and Application Prospects in Agriculture,” in IEEE Access, vol. 6, pp. 49248-49268, 2018, doi: 10.1109/ACCESS.2018.2868848.

J. Pak, J. Kim, Y. Park and H. I. Son, “Field Evaluation of Path- Planning Algorithms for Autonomous Mobile Robot in Smart Farms,” in IEEE Access, vol. 10, pp. 60253-60266, 2022, doi: 10.1109/AC- CESS.2022.3181131.

W. Wan, B. Shi, Z. Wang and R. Fukui, “Multirobot Object Transport via Robust Caging,” in IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 50, no. 1, pp. 270-280, Jan. 2020, doi: 10.1109/TSMC.2017.2733552.

J. Alonso-Mora, S. Baker, and D. Rus, “Multi-robot formation control and object transport in dynamic environments via constrained optimiza- tion,” The International Journal of Robotics Research, vol. 36, no. 9, pp. 1000-1021, 2017, doi:10.1177/0278364917719333

H. M. Pe´rez-Villeda, G. Arechavaleta, A. Morales-D´ıaz, “Multi-vehicle coordination based on hierarchical quadratic programming,” Control Engineering Practice, vol. 94, p. 104206, 2020.

D. Koung, O. Kermorgant, I. Fantoni and L. Belouaer, “Coopera- tive Multi-Robot Object Transportation System Based on Hierarchical Quadratic Programming,” in IEEE Robotics and Automation Letters, vol. 6, no. 4, pp. 6466-6472, Oct. 2021, doi: 10.1109/LRA.2021.3092305.

C. L. Shih and L. C. Lin, “Trajectory Planning and Tracking Control of a Differential-Drive Mobile Robot in a Picture Drawing Application,” Robotics, vol. 6, no. 3, p. 17, 2017, doi: 10.3390/robotics6030017.

X. Hou et al., “A Novel Mobile Robot Navigation Method Based on Hand-Drawn Paths,” in IEEE Sensors Journal, vol. 20, no. 19, pp. 11660- 11673, 1 Oct.1, 2020, doi: 10.1109/JSEN.2020.2997055.

Kaneko, R., Nakamura, Y., Morita, R. et al. Point cloud data map creation from factory design drawing for LiDAR localiza- tion of an autonomous mobile robot. Artif Life Robotics, vol. 28, no. 2, pp. 314-322, 2022, doi: 10.1007/s10015-022-00834-y

D. Lee, G. Kang, B. Kim and D. H. Shim, “Assistive Delivery Robot Application for Real-World Postal Services,” in IEEE Access, vol. 9, pp. 141981-141998, 2021, doi: 10.1109/ACCESS.2021.3120618.

V. P. Bacheti, A. S. Branda˜o and M. Sarcinelli-Filho, “A Path-Following Controller for a UAV-UGV Formation Performing the Final Step of Last- Mile-Delivery,” in IEEE Access, vol. 9, pp. 142218-142231, 2021, doi: 10.1109/ACCESS.2021.3120347.

J. G. Parada-Salado, L. E. Ortega-Garcia, L. F. Ayala-Ramirez, F. J. Perez-Pinal, C. A. Herrera-Ramirez and J. A. Padilla-Medina, “A Low- Cost Land Wheeled Autonomous Mini-robot for In-door Surveillance,” in IEEE Latin America Transactions, vol. 16, no. 5, pp. 1298-1305, May 2018, doi: 10.1109/TLA.2018.8407100.

T. Wang, P. Huang and G. Dong, “Cooperative Persistent Surveillance on a Road Network by Multi-UGVs With Detection Ability,” in IEEE Transactions on Industrial Electronics, vol. 69, no. 11, pp. 11468-11478, Nov. 2022, doi: 10.1109/TIE.2021.3121729.

C. Li, C. Fang, F. Wang, B Xia, and Y Song, “Complete coverage path planning for an Arnold system based mobile robot to perform specific types of missions,” Front Inform Technol Electron Eng, vol. 20, pp. 1530–1542, 2019, doi: 10.1631/FITEE.1800616.

A. H. Tan and G. Nejat, “Enhancing Robot Task Completion Through Environment and Task Inference: A Survey from the Mobile Robot Perspective,” J. Intell. Robot. Syst., vol. 106, no. 73, 2022, doi: 10.1007/s10846-022-01776-0

F. Niroui, K. Zhang, Z. Kashino and G. Nejat, “Deep Reinforce- ment Learning Robot for Search and Rescue Applications: Explo- ration in Unknown Cluttered Environments,” in IEEE Robotics and Automation Letters, vol. 4, no. 2, pp. 610-617, April 2019, doi: 10.1109/LRA.2019.2891991.

C. Wang, J. Cheng, J. Wang, X. Li and M. Q. H. Meng, “Efficient Object Search with Belief Road Map Using Mobile Robot,” in IEEE Robotics and Automation Letters, vol. 3, no. 4, pp. 3081-3088, Oct. 2018, doi: 10.1109/LRA.2018.2849610.

G. Curiel-Olivares, J. Linares-Flores, A. Herna´ndez-Me´ndez, J. F. Guerrero-Castellanos, G. Mino-Aguilar and C. Garc´ıa-Rodr´ıguez, “Two- In-Wheeled Self-Balancing Electric Vehicle Based on Active Dis- turbance Rejection Controller,” 2019 IEEE International Conference on Mechatronics (ICM), Ilmenau, Germany, 2019, pp. 608-613, doi: 10.1109/ICMECH.2019.8722948.

G. Curiel-Olivares, J. Linares Flores, J. F. Guerrero-Castellanos, and A. Herna´ndez-Me´ndez, “Self-balancing based on Active Disturbance Rejection Controller for the Two-In-Wheeled Electric Vehicle, Ex- perimental results,” Mechatronics, vol. 76, p. 102552, 2021, doi: 10.1016/j.mechatronics.2021.102552.

Y. Zhang, K. Song, J. Yi, P. Huang, Z. Duan and Q. Zhao, “Absolute Attitude Estimation of Rigid Body on Moving Platform Using Only Two Gyroscopes and Relative Measurements,” in IEEE/ASME Transactions on Mechatronics, vol. 23, no. 3, pp. 1350-1361, June 2018, doi: 10.1109/TMECH.2018.2811730.

K. M. Goher and S. O. Fadlallah, “Control of a Two-wheeled Machine with Two-directions Handling Mechanism Using PID and PD-FLC Algorithms,” Int. J. Autom. Comput., vol. 16, pp. 511–533, 2019, doi: 10.1007/s11633-019-1172-0.

H. Ren and C. Zhou, “Control System of Two-Wheel Self-Balancing Vehicle,” J. Shanghai Jiaotong Univ. (Sci.), vol. 26, pp. 713–721, 2021, doi: 10.1007/s12204-021-2361-x.

C. Iwendi, M. A. Alqarni, J. H. Anajemba, A. S. Alfakeeh, Z. Zhang and A. K. Bashir, “Robust Navigational Control of a Two-Wheeled Self- Balancing Robot in a Sensed Environment,” in IEEE Access, vol. 7, pp. 82337-82348, 2019, doi: 10.1109/ACCESS.2019.2923916.

J. Diaz-Tellez, V. Gutierrez-Vicente, J. Estevez-Carreon, O. D. Ramirez- Cardenas, and R. S. Garcia-Ramirez, “Nonlinear Control of a Two- Wheeled Self-balancing Autonomous Mobile Robot,” Advances in Soft Computing: 20th Mexican International Conference on Artificial Intel- ligence, pp. 348-359, 2021, doi: 10.1007/978-3-030-89820-5 28.

A. Lima-Pe´rez et al., “Robust Control of a Two-Wheeled Self-Balancing Mobile Robot,” 2021 International Conference on Mechatronics, Elec- tronics and Automotive Engineering (ICMEAE), Cuernavaca, Mexico, 2021, pp. 196-201, doi: 10.1109/ICMEAE55138.2021.00038.

R. Xiong, L. Li, C. Zhang, K. Ma, X. Yi and H. Zeng, “Path Tracking of a Four-Wheel Independently Driven Skid Steer Robotic Vehicle Through a Cascaded NTSM-PID Control Method,” in IEEE Transactions on Instrumentation and Measurement, vol. 71, pp. 1-11, 2022, doi: 10.1109/TIM.2022.3160549.

S. Kim and S. Kwon, “Nonlinear Optimal Control Design for Underactu- ated Two-Wheeled Inverted Pendulum Mobile Platform,” in IEEE/ASME Transactions on Mechatronics, vol. 22, no. 6, pp. 2803-2808, Dec. 2017, doi: 10.1109/TMECH.2017.2767085.

F. A Jime´nez, I. Ruge, and A. A Jime´nez, “Modeling and Control of a Two Wheeled Self-Balancing Robot: a didactic platform for control engineering education,” Proceedings of the 18th LACCEI International Multi-Conference for Engineering, Education and Technology, 2020, doi: 10.18687/LACCEI2020.1.1.556.

S. M. H. Rostami, A. K. Sangaiah, J. Wang, and H. Kim, “Real- time obstacle avoidance of mobile robots using state-dependent Riccati equation approach,” J. Image Video Proc., 2018, doi: 10.1186/s13640- 018-0319-1.

H. Tourajizadeh, M. Rezaei, and A. H. Sedigh, “Optimal Control of Screw In-pipe Inspection Robot with Controllable Pitch Rate,” J. Intell. Robot. Syst., vol. 90, pp. 269–286, 2018, doi: 10.1007/s10846-017-06587.

T. Johnson, S. Zhou, W. Cheah, W. Mansell, R. Young, and S Watson “Implementation of a Perceptual Controller for an Inverted Pendu- lum Robot,” J. Intell. Robot. Syst., vol. 99, pp. 683–692, 2020, doi: 10.1007/s10846-020-01158-4.

S. Jeong and T. Takahashi, “Wheeled inverted pendulum type assistant robot: design concept and mobile control,” Intel. Serv. Robotics, vol. 1, no. 4, pp. 313–320, 2008, doi: 10.1007/s11370-008-0024-5

X. Zhang, R. Wang, Y. Fang, B. Li and B. Ma, “Acceleration-Level Pseudo-Dynamic Visual Servoing of Mobile Robots with Backstepping and Dynamic Surface Control,” in IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 49, no. 10, pp. 2071-2081, Oct. 2019, doi: 10.1109/TSMC.2017.2777897.

Y. Chen, N. Li, W. Zeng, S. Zhang and G. Ma, “Curved Path Following Controller for 4W Skid-Steering Mobile Robots Using Backstepping,” in IEEE Access, vol. 10, pp. 66072-66082, 2022, doi: 10.1109/AC- CESS.2022.3185062.

R. Parween, M. V. Heredia, M. M. Rayguru, R. E. Abdulkader and M. R. Elara, “Autonomous Self-Reconfigurable Floor Cleaning Robot,” in IEEE Access, vol. 8, pp. 114433-114442, 2020, doi: 10.1109/AC- CESS.2020.2999202.

C. -H. Chiu and C. -Y. Wu, “Bicycle Robot Balance Control Based on a Robust Intelligent Controller,” in IEEE Access, vol. 8, pp. 84837-84849, 2020, doi: 10.1109/ACCESS.2020.2992792.

X. Yang, P. Wei, Y. Zhang, X. Liu and L. Yang, “Disturbance Observer Based on Biologically Inspired Integral Sliding Mode Control for Trajectory Tracking of Mobile Robots,” in IEEE Access, vol. 7, pp. 48382-48391, 2019, doi: 10.1109/ACCESS.2019.2907126.

I. Reguii, I. Hassani, and C. Rekik, “Mobile Robot Navigation Using Planning Algorithm and Sliding Mode Control in a Cluttered Environ- ment,” Journal of Robotics and Control (JRC), vol. 3, no. 2, pp. 166-175, 2022.

N. Esmaeili, A. Alfi, and H. Khosravi, “Balancing and Trajectory Tracking of Two-Wheeled Mobile Robot Using Backstepping Sliding Mode Control: Design and Experiments,” J Intell Robot Syst, vol. 87, pp. 601–613, 2017, doi: 10.1007/s10846-017-0486-9.

H. Xie, J. Zheng, Z. Sun, H. Wang, and R. Chai, “Finite-time track- ing control for nonholonomic wheeled mobile robot using adaptive fast nonsingular terminal sliding mode,” Nonlinear Dyn, vol. 110, pp. 1437–1453, 2022 doi: 10.1007/s11071-022-07682-2.

M. Cui, “Observer-Based Adaptive Tracking Control of Wheeled Mobile Robots With Unknown Slipping Parameters,” in IEEE Access, vol. 7, pp. 169646-169655, 2019, doi: 10.1109/ACCESS.2019.2955887

J. Meng, H. Xiao, L. Jiang, Z. Hu, L. Jiang, and N. Jiang, “Adap- tive Model Predictive Control for Mobile Robots with Localization Fluctuation Estimation” Sensors, vol. 23, no. 5, p. 2501, 2023, doi: 10.3390/s23052501.

J. Lin, Z. Miao, H. Zhong, W. Peng, Y. Wang and R. Fierro, “Adaptive Image-Based Leader–Follower Formation Control of Mo- bile Robots with Visibility Constraints,” in IEEE Transactions on Industrial Electronics, vol. 68, no. 7, pp. 6010-6019, July 2021, doi: 10.1109/TIE.2020.2994861.

D. Chwa and J. Boo, “Adaptive Fuzzy Output Feedback Simultaneous Posture Stabilization and Tracking Control of Wheeled Mobile Robots with Kinematic and Dynamic Disturbances,” in IEEE Access, vol. 8, pp. 228863-228878, 2020, doi: 10.1109/ACCESS.2020.3046282

M. Cui, “Observer-Based Adaptive Tracking Control of Wheeled Mobile Robots with Unknown Slipping Parameters,” in IEEE Access, vol. 7, pp. 169646-169655, 2019, doi: 10.1109/ACCESS.2019.2955887.

M. Cui, W. Liu, H. Liu, H. Jiang, and Z. Wang, “Extended state observer- based adaptive sliding mode control of differential-driving mobile robot with uncertainties,” Nonlinear Dyn, vol. 83, pp. 667–683, 2016, doi: 10.1007/s11071-015-2355-z.

K. Liu, H. Gao, H. Ji, and Z. Hao, “Adaptive Sliding Mode Based Disturbance Attenuation Tracking Control for Wheeled Mobile Robots,” Int. J. Control Autom. Syst., vol. 18, pp. 1288–1298, 2020, doi: 10.1007/s12555-019-0262-7

C. F. Hsu and W. F. Kao, “Double-loop fuzzy motion control with CoG supervisor for two-wheeled self-balancing assistant robots,” Int. J. Dynam. Control, vol. 8, pp. 851–866, 2020, doi: 10.1007/s40435-020- 00617-y.

M. Moness, D. Mahmoud, and A. Hussein, “Real-time Mamdani-like fuzzy and fusion-based fuzzy controllers for balancing two-wheeled inverted pendulum,” J Ambient Intell Human Comput, vol. 13, pp. 3577–3593, 2022, doi: 10.1007/s12652-020-01991-3

T. Zhao, Q. Yu, S. Dian, R. Guo and S. Li, “Non-singleton General Type-2 Fuzzy Control for a Two-Wheeled Self-Balancing Robot,” Int. J. Fuzzy Syst., vol. 21, pp. 1724–1737, 2019, doi: 10.1007/s40815-019- 00664-4.

T. A. Mai, D. N. Anisimov, T. S. Dang, V. N. Dinh, “Development of a microcontroller-based adaptive fuzzy controller for a two-wheeled self-balancing robot,” Microsystem Technologies, vol. 24, 2018, doi: 10.1007/s00542-018-3825-2.

L. Gentilini, S. Rossi, D. Mengoli, A. Eusebi and L. Marconi, “Tra- jectory Planning ROS Service for an Autonomous Agricultural Robot,” 2021 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor), Trento-Bolzano, Italy, 2021, pp. 384-389, doi: 10.1109/MetroAgriFor52389.2021.9628620.

J. Martin et al., “A Generic ROS-Based Control Architecture for Pest Inspection and Treatment in Greenhouses Using a Mobile Manipulator,” in IEEE Access, vol. 9, pp. 94981-94995, 2021, doi: 10.1109/AC- CESS.2021.3093978.

M. S. Miah and J. Knoll, “Area Coverage Optimization Using Heteroge- neous Robots: Algorithm and Implementation,” in IEEE Transactions on Instrumentation and Measurement, vol. 67, no. 6, pp. 1380-1388, June 2018, doi: 10.1109/TIM.2018.2800178.

W. Guan, S. Chen, S. Wen, Z. Tan, H. Song and W. Hou, “High- Accuracy Robot Indoor Localization Scheme Based on Robot Op- erating System Using Visible Light Positioning,” in IEEE Photonics Journal, vol. 12, no. 2, pp. 1-16, April 2020, Art no. 7901716, doi: 10.1109/JPHOT.2020.2981485.

R. Valner, V. Vunder, A. Aabloo, M. Pryor and K. Kruusama¨e, “TeMoto: A Software Framework for Adaptive and Dependable Robotic Autonomy with Dynamic Resource Management,” in IEEE Access, vol. 10, pp. 51889-51907, 2022, doi: 10.1109/ACCESS.2022.3173647.

R. F. Carpio et al., “A Navigation Architecture for Ackermann Vehicles in Precision Farming,” in IEEE Robotics and Automation Letters, vol. 5, no. 2, pp. 1103-1110, April 2020, doi: 10.1109/LRA.2020.2967306.

M. Pei, H. An, B. Liu and C. Wang, “An Improved Dyna-Q Algorithm for Mobile Robot Path Planning in Unknown Dynamic Environment,” in IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 52, no. 7, pp. 4415-4425, July 2022, doi: 10.1109/TSMC.2021.3096935.

F. Ugalde Pereira, P. Medeiros de Assis Brasil, M. A. de Souza Leite Cuadros, A. R. Cukla, P. Drews Junior and D. F. Tello Gamarra, “Analysis of Local Trajectory Planners for Mobile Robot with Robot Operating System,” in IEEE Latin America Transactions, vol. 20, no. 1, pp. 92-99, Jan. 2022, doi: 10.1109/TLA.2022.9662177.

J. Misˇeikis et al., “Lio-A Personal Robot Assistant for Human- Robot Interaction and Care Applications,” in IEEE Robotics and Automation Letters, vol. 5, no. 4, pp. 5339-5346, Oct. 2020, doi: 10.1109/LRA.2020.3007462.

J. Li, M. Liu, W. Wang and C. Hu, “Inspection Robot Based on Offline Digital Twin Synchronization Architecture,” in IEEE Journal of Radio Frequency Identification, vol. 6, pp. 943-947, 2022, doi: 10.1109/JRFID.2022.3207047.

M. A. Chung and C. W. Lin, “An Improved Localization of Mo- bile Robotic System Based on AMCL Algorithm,” in IEEE Sen- sors Journal, vol. 22, no. 1, pp. 900-908, no. 1, 2022, doi: 10.1109/JSEN.2021.3126605.

A. Bihlmaier and H. Wo¨rn, “Hands-on learning of ros using common hardware,” Robot Operating System (ROS) The Complete Reference, vol. 1, pp. 29-50, 2016.




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