Universal Low-Complexity Safe Tracking Control and Its Application to Time-Independent Path Following of Nonholonomic Mobile Robots

The existing shared control schemes and automatic control schemes are almost designed separately. Based on the designed constrained function and shared-constrained function, this paper proposes a universal control framework for high-order strict-feedback systems that can achieve safe tracking control with very low algorithm complexity regardless of whether the reference signal exceeds safety constraints, combining the flexibility of manual operating with the persistence and security of automatic control. A universal safe tracking control theorem is presented to prove the security of system operation. Furthermore, based on the proposed universal safe tracking control method, a novel time-independent path following control method with lane constraints is proposed for nonholonomic mobile robots by converting lane constraints into heading angle constraints, thus achieving automatic/auxiliary adaptive cruise control and lane keeping. Simulation and experimental results are provided to demonstrate the practical applicability of this method. Note to Practitioners—This work addresses the issue of the reference signal exceeding the safety constraint due to planner errors (in autonomous control) or human operator mistakes (in shared control). Compared to existing control methods, the proposed architecture is not only applicable to safe tracking control in both autonomous and shared control scenarios, but also features extremely low algorithmic complexity, making it highly suitable for practical deployment. Unlike traditional shared control systems, where human operators directly manipulate system inputs, the proposed method allows operators to control the system by adjusting the reference signal. This ensures that feedback control is always present, thereby reducing the difficulty of manipulation. Moreover, in contrast to common trajectory tracking methods, the proposed time-independent path following approach holds greater practical value, ultimately achieving adaptive cruise control and lane-keeping for mobile robots. To ensure repeatability, our codes are open sourced on github: <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/Mudianrui/USC-and-app-in-NMRs.git</uri>. Experimental videos can be accessed through <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://youtu.be/VrsISKkJOCA</uri>