# Quantifying the Trajectory Tracking Accuracy in UGVs: The Role of Traffic Scheduling in Wi-Fi-Enabled Time-Sensitive Networking

## TL;DR

This paper studies how traffic scheduling in Wi-Fi-enabled networks affects the accuracy of robot movement tracking.

## Contribution

A mathematical framework is introduced to predict packet delivery and optimize traffic scheduling for trajectory tracking.

## Key findings

- Improper traffic scheduling and synchronization can degrade trajectory tracking accuracy significantly.
- Correctly configured scheduling windows ensure reliable packet delivery and stable control.
- The model provides practical guidelines for wireless TSN network design in robotics.

## Abstract

Accurate trajectory tracking is a key requirement in unmanned ground vehicles (UGVs) operating in autonomous driving, mobile robotics, and industrial automation. In wireless Time-Sensitive Networking (WTSN) scenarios, trajectory accuracy strongly depends on deterministic packet delivery, precise traffic scheduling, and time synchronization among distributed devices. This paper quantifies the impact of IEEE 802.1Qbv time-aware traffic scheduling on trajectory tracking accuracy in UGVs operating over Wi-Fi-enabled TSN networks. The analysis focuses on how misconfigured real-time (RT) and best-effort (BE) transmission windows, as well as clock misalignment between devices, affect packet reception and control performance. A mathematical framework is introduced to predict the number of correctly received RT packets based on cycle time, packet periodicity, scheduling window lengths, and synchronization offsets, enabling the a priori dimensioning of RT and BE windows. The proposed model is validated through extensive simulations conducted in an ROS–Gazebo environment, utilising Linux-based traffic shaping and scheduling tools. Results show that improper traffic scheduling and synchronization offsets can significantly degrade trajectory tracking accuracy, while correctly dimensioned scheduling windows ensure reliable packet delivery and stable control, even under imperfect synchronization. The proposed approach provides practical design guidelines for configuring wireless TSN networks supporting real-time trajectory tracking in mobile robotic systems.