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January 14, 2026SensorsOpen Access

Robust Model Predictive Control with a Dynamic Look-Ahead Re-Entry Strategy for Trajectory Tracking of Differential-Drive Robots

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Authors

DGDiego GuffantiMMMoisés Filiberto Mora MurilloSSSantiago Bustamante Sanchez

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Overview

Experimental validation demonstrates improved stability and accuracy in trajectory tracking of differential-drive robots using a novel control strategy.

Key Points

  • This work aims to enhance trajectory tracking accuracy in differential-drive mobile robots using a robust model predictive control strategy.
  • Experimental validation on a four-wheel differential-drive mobile robot.
  • Utilized a Model Predictive Control framework with quadratic programming for trajectory tracking.
  • Incorporated a SLAM algorithm for odometry correction in ROS 2.
  • Developed a dynamic look-ahead re-entry strategy to smooth reconnection after deviations.
  • Quantitative evaluation using RMSE, MAE, P95, and in-band percentage metrics.
  • Achieved lateral RMSE of 0.05 m and heading RMSE of 0.06 rad under nominal conditions.
  • Maintained 68.8% of the trajectory within the validation band in optimal configurations.
  • Demonstrated improved robustness with a lateral RMSE of 0.12 m and 51.4% in-band preservation under perturbations.
  • Outperformed traditional MPC without re-entry strategy, showing quicker recovery from deviations.

Cite This Study

Guffanti et al. (2026) studied this question.

synapsesocial.com/papers/696719c1c0d1e3cfbfce92c4https://doi.org/10.3390/s26020520
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