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Unified T-S fuzzy-relaxed control barrier function framework for unicycle Mobile robot safe trajectory tracking.
Ali Rahmanian1, Mohammad Hassan Asemani1
1School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran.
ISA Transactions
|April 9, 2026
Summary
This study presents a unified control framework for autonomous mobile robots, ensuring safe trajectory tracking and obstacle avoidance using fuzzy logic and a safety filter. The method achieves accurate navigation with low computational cost.
Area of Science:
- Robotics
- Control Systems
- Artificial Intelligence
Background:
- Safe operation of autonomous mobile robots is crucial in uncertain environments.
- Trajectory tracking and obstacle avoidance are key challenges for mobile robots.
Purpose of the Study:
- To propose a unified control framework for trajectory tracking and obstacle avoidance in unicycle mobile robots.
- To ensure safe navigation in dynamic and obstacle-rich environments.
Main Methods:
- Utilized a Takagi-Sugeno (T-S) fuzzy controller for nonlinear dynamics representation.
- Employed a relaxed Control Barrier Function (rCBF)-based safety filter for collision avoidance.
- Synthesized a parallel distributed compensation (PDC) controller using linear matrix inequalities (LMIs).
Main Results:
- The proposed framework accurately tracks desired trajectories while effectively avoiding obstacles.
- An extended rCBF formulation provided a smooth, analytical safety assist input.
- The system demonstrated low computational complexity, suitable for real-time applications.
Conclusions:
- The unified control framework effectively integrates trajectory tracking and obstacle avoidance for unicycle mobile robots.
- The rCBF-based safety filter ensures collision avoidance without online optimization.
- The approach offers a computationally efficient solution for safe autonomous robot navigation.
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