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Quantifying the Trajectory Tracking Accuracy in UGVs: The Role of Traffic Scheduling in Wi-Fi-Enabled Time-Sensitive
Elena Ferrari1, Alberto Morato2, Federico Tramarin1,3
1Department of Information Engineering, University of Padova, 35131 Padova, Italy.
Sensors (Basel, Switzerland)
|February 13, 2026
Summary
Accurate trajectory tracking in unmanned ground vehicles relies on precise scheduling in wireless Time-Sensitive Networking (WTSN). This study shows proper configuration of traffic scheduling and time synchronization is crucial for reliable performance.
Area of Science:
- Robotics and Automation
- Wireless Networking
- Control Systems Engineering
Background:
- Accurate trajectory tracking is essential for unmanned ground vehicles (UGVs) in autonomous systems.
- Wireless Time-Sensitive Networking (WTSN) relies on deterministic packet delivery, traffic scheduling, and time synchronization for reliable operation.
- IEEE 802.1Qbv time-aware traffic scheduling impacts trajectory accuracy in Wi-Fi TSN networks.
Purpose of the Study:
- To quantify the effect of IEEE 802.1Qbv traffic scheduling on UGV trajectory tracking accuracy.
- To analyze how misconfigured real-time (RT) and best-effort (BE) windows and clock misalignment affect packet reception and control.
- To provide a framework for dimensioning RT and BE windows for reliable packet delivery.
Main Methods:
- Developed a mathematical framework to predict real-time packet reception based on network parameters and synchronization offsets.
- Validated the model through extensive simulations in an ROS-Gazebo environment.
- Utilized Linux-based traffic shaping and scheduling tools for realistic network emulation.
Main Results:
- Improper traffic scheduling and synchronization offsets significantly degrade UGV trajectory tracking accuracy.
- Correctly dimensioned scheduling windows ensure reliable packet delivery and stable control, even with imperfect synchronization.
- The study demonstrates the critical interplay between network configuration and robotic system performance.
Conclusions:
- Practical design guidelines for configuring wireless TSN networks for real-time trajectory tracking in mobile robotics.
- Highlights the importance of precise traffic scheduling and time synchronization for autonomous systems.
- Offers a method for a priori dimensioning of scheduling windows to ensure system reliability.
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