[Paper Review] When Robotics Meets Wireless Communications: An Introductory Tutorial

Daniel Bonilla Licea, Mounir Ghogho+1 more|arXiv (Cornell University)|Sep 5, 2022

UAV Applications and Optimization190 references4 citations

TL;DR

This tutorial introduces an interdisciplinary framework for integrating robotics and wireless communications, focusing on communication-aware trajectory planning (CaTP) for mobile robots and UAVs. It presents unified modeling tools for robotic motion and wireless channel dynamics, enabling optimization of trajectories that jointly maximize communication quality and robotic task performance, with applications in 5G/6G networks and robotic swarms.

ABSTRACT

The importance of ground Mobile Robots (MRs) and Unmanned Aerial Vehicles (UAVs) within the research community, industry, and society is growing fast. Many of these agents are nowadays equipped with communication systems that are, in some cases, essential to successfully achieve certain tasks. In this context, we have begun to witness the development of a new interdisciplinary research field at the intersection of robotics and communications. This research field has been boosted by the intention of integrating UAVs within the 5G and 6G communication networks. This research will undoubtedly lead to many important applications in the near future. Nevertheless, one of the main obstacles to the development of this research area is that most researchers address these problems by oversimplifying either the robotics or the communications aspect. This impedes the ability of reaching the full potential of this new interdisciplinary research area. In this tutorial, we present some of the modelling tools necessary to address problems involving both robotics and communication from an interdisciplinary perspective. As an illustrative example of such problems, we focus in this tutorial on the issue of communication-aware trajectory planning.

Motivation & Objective

• Address the growing need for interdisciplinary research at the intersection of robotics and wireless communications, particularly for mobile robots (MRs) and unmanned aerial vehicles (UAVs).
• Overcome the limitations of oversimplified models in existing research by integrating realistic robotic motion and communication channel models.
• Enable the design of communication-aware trajectory planning (CaTP) that jointly optimizes robotic motion and communication quality.
• Provide a foundational tutorial for researchers to model and solve CaTP problems using unified mathematical formulations.
• Support emerging applications in 5G/6G networks, robotic swarms, and mobile relays by establishing a common theoretical and practical framework.

Proposed method

• Introduce detailed motion models for ground robots (e.g., differential drive, three-wheeled omnidirectional) and UAVs, capturing kinematic and dynamic constraints.
• Present realistic wireless channel models, including line-of-sight (LoS), non-LoS, path loss, shadowing, and Doppler effects, tailored to mobile robot scenarios.
• Formulate CaTP as a mixed-integer programming (MILP) or mixed-integer programming (MIP) problem, incorporating both robotic constraints and communication metrics.
• Integrate communication quality metrics such as SNR, SINR, age of information (AoI), and packet reception ratio (PRR) into the trajectory optimization objective function.
• Use probabilistic models (p.d.f., p.m.f.) and stochastic geometry (e.g., PPP for node distribution) to model uncertainty in radio propagation and node locations.
• Demonstrate the coupling between robotic motion and communication performance through joint optimization, using examples like relay deployment and swarm connectivity.

Experimental results

Research questions

• RQ1 How can robotic motion models be accurately integrated with wireless channel models to enable joint optimization in communication-aware trajectory planning?
• RQ2 What are the key communication quality metrics (e.g., SNR, AoI, PRR) that should be optimized alongside robotic task objectives?
• RQ3 How do mobility constraints of ground robots and UAVs affect the feasibility and performance of communication-aware trajectories?
• RQ4 What mathematical formulations (e.g., MILP, MIP) are most effective for modeling CaTP problems with mixed-integer and continuous variables?
• RQ5 How can the interplay between robotic control and wireless communication be formalized to avoid oversimplification and ensure real-world feasibility?

Key findings

• Communication-aware trajectory planning (CaTP) enables significant performance gains over conventional trajectory planning by jointly optimizing robotic motion and communication quality.
• Controlling the position of mobile transceivers (e.g., on UAVs or MRs) as a design parameter can yield higher diversity gains than static, independently designed diversity branches.
• The integration of realistic channel models (e.g., LoS, shadowing, path loss) with robotic motion models leads to more feasible and energy-efficient trajectories.
• Formulations based on mixed-integer programming (MILP/MIP) effectively capture the discrete and continuous aspects of CaTP, enabling optimization under mechanical and communication constraints.
• The tutorial demonstrates that oversimplifying either robotics or communications leads to unfeasible or suboptimal solutions, highlighting the need for a unified modeling approach.
• The framework supports diverse applications such as mobile base stations, data ferrying, and robotic swarms, with potential for integration into 5G and 6G networks.