Smooth Control Strategies for Path-Following on Computationally Constrained Mobile Robots with Discontinuous Localization

In diverse applications such as large industrial settings, automated guided vehicles (AGVs) deal with discontinuous localization feedback from optical sensors or QR code readers. These discontinuities may induce aggressive behavior in reactive controllers, which is dangerous in practical operations. Additionally, many AGVs are chosen for their low power consumption, to be used for longer operation times, which commonly reduces the computational resources of the system. This work proposes a real-time path-following algorithm based on Bézier curves to address these challenges. The proposed strategy selects third-order Bézier curve control points in a logical and structured manner to create smooth recovery trajectories as discontinuities appear. Numerical simulations and practical experiments were carried out to validate the performance of the proposed approach. A comparison with model predictive control (MPC) showcased that the Bézier-based approach achieves a similar performance in terms of control smoothness, while the computational complexity is reduced.