Where to Fly, What to Send: Communication-Aware Aerial Support for Ground Robots

TL;DR

The paper tackles coordinated exploration and communication in a multi-robot system where a single UAV assists multiple UGVs in an unknown, bandwidth-limited environment. It introduces a Value-of-Information (VoI) framework to select task-relevant map data for transmission, coupled with a MILP-based bandwidth allocation to distribute limited communication resources among seekers. A utility-driven exploration strategy guides the UAV's data gathering, balancing information value with exploration costs. Simulation results demonstrate substantial reductions in data transmission while maintaining or improving navigation performance, highlighting the framework's practical potential for communication-aware aerial support in real-world missions.

Abstract

In this work we consider a multi-robot team operating in an unknown environment where one aerial agent is tasked to map the environment and transmit (a portion of) the mapped environment to a group of ground agents that are trying to reach their goals. The entire operation takes place over a bandwidth-limited communication channel, which motivates the problem of determining what and how much information the assisting agent should transmit and when while simultaneously performing exploration/mapping. The proposed framework enables the assisting aerial agent to decide what information to transmit based on the Value-of-Information (VoI), how much to transmit using a Mixed-Integer Linear Programming (MILP), and how to acquire additional information through an utility score-based environment exploration strategy. We perform a communication-motion trade-off analysis between the total amount of map data communicated by the aerial agent and the navigation cost incurred by the ground agents.

Figures (9)

• Figure 1: Overview of a helper/UAV assisting the $\mathbf{r}^{th}$ receiver/UGV agent by sending remote map observations based on the receiver's need. The UAV selects cells to send from the set of informative cells. Brighter the cell color the higher its value-of-information. UGV sends its estimated path way-points shown by yellow cells and path-uncertainty fraction.
• Figure 2: (a) Full Environment ($\mathcal{M}$). (b) Partially Explored Map ($\mathcal{M}_e$). (c) A representative Data Transfer Map ($X_\mathcal{T}$). (d) Corresponding Information Map ( $X_{\mathcal{I}}$).
• Figure 3: Flowchart illustrating the operation at time $t$. Active seekers send their path information to the supporter. Based on the received path data ( $\rho(\hat{\pi}^\textbf{r}_*(\textit{t}),m)$), the supporter updates their corresponding information map to select relevant data for transmission and determines the exploration path to gather additional information.
• Figure 4: (a) Supporter Exploration Map $\mathcal{M}^\textbf{h}(\textit{t})$: the slate-gray region represents the unexplored area $\mathcal{M}^\textbf{h}_u(t)$. The yellow cells correspond to the $\textbf{r}^{th}$ seeker’s path data $\rho(\hat{\pi}^\textbf{r}_*(\textit{t}), m)$, sampled at $m = 3$. (b–d) Maps corresponding to the $\textbf{r}^{\text{th}}$ seeker agent: (b) Supporter Difference Map $(\mathcal{T}^\textbf{r}_{\textbf{p}}(\textit{t}) - o_\textbf{p})$: red indicates a positive difference, blue a negative one, and white no difference. (c) Region of Interest Map $\Dot{\iota}^\textbf{r}_\textbf{p}(\textit{t})$: darker shades represent higher interest values. (d) Weighted Information Map $\mathrm{VoI}^\textbf{r}_{\textbf{p}}(\textit{t})$: cells with magenta boundaries denote the top $10$ cells with most value-of-information.
• Figure 5: Bandwidth allocation for a single-supporter and three-seeker team. The allocated bandwidths for each agent are shown by the red, green, and blue sections, representing $\boldsymbol{b}^1$, $\boldsymbol{b}^2$, and $\boldsymbol{b}^3$, respectively.