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Obstacle-Aware Positioning of a Mobile Robotic Platform for 6G Networks

Alexandre Costa, Pedro Duarte, André Coelho, Rui Campos

TL;DR

This paper addresses the challenge of positioning Mobile Robotic Platforms (MRPs) to provide LoS wireless connectivity in 6G-era networks. It introduces a two-module framework comprising a Vision Module (video-based obstacle and device localization using YOLOv7) and a Control Module (ROS-based autonomous navigation with obstacle avoidance) to place MRPs for LoS links. The framework is validated through simulation with Turtlesim and real-world experiments, demonstrating successful obstacle avoidance and LoS maintenance to wireless devices. The work enables on-demand mobile communications cells and highlights practical considerations for real-time operation and scalability in dynamic environments.

Abstract

The 6G paradigm and the massive usage of interconnected wireless devices introduced the need for flexible wireless networks. A promising approach lies in employing Mobile Robotic Platforms (MRPs) to create communications cells on-demand. The challenge consists in positioning the MRPs to improve the wireless connectivity offered. This is exacerbated in millimeter wave (mmWave), Terahertz (THz), and visible light-based networks, which imply the establishment of short-range, Line of Sight (LoS) wireless links to take advantage of the ultra-high bandwidth channels available. This paper proposes a solution to enable the obstacle-aware, autonomous positioning of MRPs and provide LoS wireless connectivity to communications devices. It consists of 1) a Vision Module that uses video data gathered by the MRP to determine the location of obstacles, wireless devices and users, and 2) a Control Module, which autonomously positions the MRP based on the information provided by the Vision Module. The proposed solution was validated in simulation and through experimental testing, showing that it is able to position an MRP while ensuring LoS wireless links between a mobile communications cell and wireless devices or users.

Obstacle-Aware Positioning of a Mobile Robotic Platform for 6G Networks

TL;DR

This paper addresses the challenge of positioning Mobile Robotic Platforms (MRPs) to provide LoS wireless connectivity in 6G-era networks. It introduces a two-module framework comprising a Vision Module (video-based obstacle and device localization using YOLOv7) and a Control Module (ROS-based autonomous navigation with obstacle avoidance) to place MRPs for LoS links. The framework is validated through simulation with Turtlesim and real-world experiments, demonstrating successful obstacle avoidance and LoS maintenance to wireless devices. The work enables on-demand mobile communications cells and highlights practical considerations for real-time operation and scalability in dynamic environments.

Abstract

The 6G paradigm and the massive usage of interconnected wireless devices introduced the need for flexible wireless networks. A promising approach lies in employing Mobile Robotic Platforms (MRPs) to create communications cells on-demand. The challenge consists in positioning the MRPs to improve the wireless connectivity offered. This is exacerbated in millimeter wave (mmWave), Terahertz (THz), and visible light-based networks, which imply the establishment of short-range, Line of Sight (LoS) wireless links to take advantage of the ultra-high bandwidth channels available. This paper proposes a solution to enable the obstacle-aware, autonomous positioning of MRPs and provide LoS wireless connectivity to communications devices. It consists of 1) a Vision Module that uses video data gathered by the MRP to determine the location of obstacles, wireless devices and users, and 2) a Control Module, which autonomously positions the MRP based on the information provided by the Vision Module. The proposed solution was validated in simulation and through experimental testing, showing that it is able to position an MRP while ensuring LoS wireless links between a mobile communications cell and wireless devices or users.
Paper Structure (9 sections, 15 figures)

This paper contains 9 sections, 15 figures.

Table of Contents

  1. Introduction
  2. System Design and Specification
  3. Vision Module
  4. Control Module
  5. Evaluation
  6. Simulation Results
  7. Experimental Results
  8. Discussion
  9. Conclusions

Figures (15)

  • Figure 1: A mobile communications cell providing Line of Sight (LoS) connectivity to wireless devices.
  • Figure 2: Unitree Go1 mobile robotic platform.
  • Figure 3: High-level system architecture.
  • Figure 4: Graphical representation of the detection areas considered by the Vision Module.
  • Figure 5: Vision Module's system architecture, including the connection established with the Control Module.
  • ...and 10 more figures