CBFs-Based Model Predictive Control for Obstacle Avoidance With Tilt Angle Limitation for Ball-Balancing Robots
This study investigates an automatic navigation method for one type of underactuated system, ball-balancing robot (ballbot), in complex environments with both dynamic obstacles and complex-shaped obstacles. To ensure safe operations, which means that ballbot has to avoid obstacles and maintain tilt...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10988790/ |
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| author | Minh Duc Pham Duc Cuong Vu Thi Thuy Hang Nguyen Thi-van-Anh Nguyen Minh Nhat Vu Tung Lam Nguyen |
| author_facet | Minh Duc Pham Duc Cuong Vu Thi Thuy Hang Nguyen Thi-van-Anh Nguyen Minh Nhat Vu Tung Lam Nguyen |
| author_sort | Minh Duc Pham |
| collection | DOAJ |
| description | This study investigates an automatic navigation method for one type of underactuated system, ball-balancing robot (ballbot), in complex environments with both dynamic obstacles and complex-shaped obstacles. To ensure safe operations, which means that ballbot has to avoid obstacles and maintain tilt angles in a desired range, Nonlinear Model Predictive Control (NMPC) is formulated to predict the position and behavior of the ballbot, followed by the optimization problem assisted by Control Barrier Function (CBF) constraints to drive the ballbot in the safe trajectory. Instead of directly implementing tilt angle limitations on the main NMPC, another Quadratic Programming Optimizer based on CBF is designed outside the main controller to reduce the constraint complexity of optimization. An elliptic-bounded generation method is used to simplify the object boundary, especially concave obstacles definition in NMPC constraints, while Extended State Observer is used for observing, compensating the uncertainty terms, and estimating the velocities of the ballbot. In general, by combining this CBF-based NMPC and Quadratic Programming, this research addresses simultaneously high-quality observer, tracking control, balancing control, complex motion planning and safe-angle constraints for the 3D-ballbot system. The effectiveness of our proposed method is determined by simulations in complicated tracking scenarios with static, dynamic and complex-shaped objects. |
| format | Article |
| id | doaj-art-c3069b68cbee4d4ebbf80441d145352c |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-c3069b68cbee4d4ebbf80441d145352c2025-08-20T02:31:02ZengIEEEIEEE Access2169-35362025-01-0113822118222810.1109/ACCESS.2025.356747410988790CBFs-Based Model Predictive Control for Obstacle Avoidance With Tilt Angle Limitation for Ball-Balancing RobotsMinh Duc Pham0https://orcid.org/0009-0007-4509-2155Duc Cuong Vu1https://orcid.org/0009-0002-3190-1875Thi Thuy Hang Nguyen2Thi-van-Anh Nguyen3https://orcid.org/0000-0002-5290-5296Minh Nhat Vu4https://orcid.org/0000-0003-0692-8830Tung Lam Nguyen5https://orcid.org/0000-0003-4108-8275Motion Control and Applied Robotics Laboratory (MoCAR), School of Electrical and Electronic Engineering, Hanoi University of Science and Technology, Hanoi, VietnamMotion Control and Applied Robotics Laboratory (MoCAR), School of Electrical and Electronic Engineering, Hanoi University of Science and Technology, Hanoi, VietnamMotion Control and Applied Robotics Laboratory (MoCAR), School of Electrical and Electronic Engineering, Hanoi University of Science and Technology, Hanoi, VietnamMotion Control and Applied Robotics Laboratory (MoCAR), School of Electrical and Electronic Engineering, Hanoi University of Science and Technology, Hanoi, VietnamAutomation and Control Institute (ACIN), TU Wien, Vienna, AustriaMotion Control and Applied Robotics Laboratory (MoCAR), School of Electrical and Electronic Engineering, Hanoi University of Science and Technology, Hanoi, VietnamThis study investigates an automatic navigation method for one type of underactuated system, ball-balancing robot (ballbot), in complex environments with both dynamic obstacles and complex-shaped obstacles. To ensure safe operations, which means that ballbot has to avoid obstacles and maintain tilt angles in a desired range, Nonlinear Model Predictive Control (NMPC) is formulated to predict the position and behavior of the ballbot, followed by the optimization problem assisted by Control Barrier Function (CBF) constraints to drive the ballbot in the safe trajectory. Instead of directly implementing tilt angle limitations on the main NMPC, another Quadratic Programming Optimizer based on CBF is designed outside the main controller to reduce the constraint complexity of optimization. An elliptic-bounded generation method is used to simplify the object boundary, especially concave obstacles definition in NMPC constraints, while Extended State Observer is used for observing, compensating the uncertainty terms, and estimating the velocities of the ballbot. In general, by combining this CBF-based NMPC and Quadratic Programming, this research addresses simultaneously high-quality observer, tracking control, balancing control, complex motion planning and safe-angle constraints for the 3D-ballbot system. The effectiveness of our proposed method is determined by simulations in complicated tracking scenarios with static, dynamic and complex-shaped objects.https://ieeexplore.ieee.org/document/10988790/Ball-balancing robotmoving obstacle avoidancemodel predictive controlcontrol barrier functionoutput constraintsimulation technique |
| spellingShingle | Minh Duc Pham Duc Cuong Vu Thi Thuy Hang Nguyen Thi-van-Anh Nguyen Minh Nhat Vu Tung Lam Nguyen CBFs-Based Model Predictive Control for Obstacle Avoidance With Tilt Angle Limitation for Ball-Balancing Robots IEEE Access Ball-balancing robot moving obstacle avoidance model predictive control control barrier function output constraint simulation technique |
| title | CBFs-Based Model Predictive Control for Obstacle Avoidance With Tilt Angle Limitation for Ball-Balancing Robots |
| title_full | CBFs-Based Model Predictive Control for Obstacle Avoidance With Tilt Angle Limitation for Ball-Balancing Robots |
| title_fullStr | CBFs-Based Model Predictive Control for Obstacle Avoidance With Tilt Angle Limitation for Ball-Balancing Robots |
| title_full_unstemmed | CBFs-Based Model Predictive Control for Obstacle Avoidance With Tilt Angle Limitation for Ball-Balancing Robots |
| title_short | CBFs-Based Model Predictive Control for Obstacle Avoidance With Tilt Angle Limitation for Ball-Balancing Robots |
| title_sort | cbfs based model predictive control for obstacle avoidance with tilt angle limitation for ball balancing robots |
| topic | Ball-balancing robot moving obstacle avoidance model predictive control control barrier function output constraint simulation technique |
| url | https://ieeexplore.ieee.org/document/10988790/ |
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