Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Bearing-based Autonomous Communication Relay Positioning under Field-of-View Constraints

Marco Fabris, Daniel Zelazo

TL;DR

This work develops a bearing-based formation-control framework for an autonomous relay vehicle (RV) to position itself for relay establishment while keeping multiple agents within its Field-of-View (FoV). The approach derives a bearing-only control law applicable to single and multi-agent scenarios, complemented by a collision-avoidance term that preserves FoV coverage. Key theoretical results yield explicit gain thresholds, including $K_r^{\star} = v_M / \mathrm{s}_{\gamma}$ for a single agent and $K_r^{q}$ for $n>1$ agents, ensuring FoV containment under bearing measurements only and with low risk of collisions. The framework is validated through numerical simulations, a switching mechanism that avoids chattering, and a surveillance-style application demonstrating dynamic patrolling and coverage. The proposed method offers a scalable, decentralized solution for maintaining connectivity and relay functionality in MAS deployments, with potential extensions to 3D environments and more general connectivity constraints.

Abstract

This paper investigates the problem of communication relay establishment for multiple agent-based mobile units using a relay vehicle. The objective is to drive autonomously the relay vehicle to attain a position for communication relay establishment while maintaining the other vehicles inside of its field-of-view. A bearing-based control law is proposed for the relay drone and designed for both single and multiple agents. We also provide a collision avoidance scheme that ensures no collisions between the relay and other agents. Numerical simulations and experimental results are reported as well to show the efficacy of the proposed approach.

Bearing-based Autonomous Communication Relay Positioning under Field-of-View Constraints

TL;DR

This work develops a bearing-based formation-control framework for an autonomous relay vehicle (RV) to position itself for relay establishment while keeping multiple agents within its Field-of-View (FoV). The approach derives a bearing-only control law applicable to single and multi-agent scenarios, complemented by a collision-avoidance term that preserves FoV coverage. Key theoretical results yield explicit gain thresholds, including for a single agent and for agents, ensuring FoV containment under bearing measurements only and with low risk of collisions. The framework is validated through numerical simulations, a switching mechanism that avoids chattering, and a surveillance-style application demonstrating dynamic patrolling and coverage. The proposed method offers a scalable, decentralized solution for maintaining connectivity and relay functionality in MAS deployments, with potential extensions to 3D environments and more general connectivity constraints.

Abstract

This paper investigates the problem of communication relay establishment for multiple agent-based mobile units using a relay vehicle. The objective is to drive autonomously the relay vehicle to attain a position for communication relay establishment while maintaining the other vehicles inside of its field-of-view. A bearing-based control law is proposed for the relay drone and designed for both single and multiple agents. We also provide a collision avoidance scheme that ensures no collisions between the relay and other agents. Numerical simulations and experimental results are reported as well to show the efficacy of the proposed approach.
Paper Structure (19 sections, 7 theorems, 50 equations, 11 figures)

This paper contains 19 sections, 7 theorems, 50 equations, 11 figures.

Table of Contents

  1. Introduction
  2. Preliminaries
  3. Autonomous Relay Tracking
  4. System model and problem statement
  5. Control strategy
  6. The Single Agent Case
  7. The 2-agent Case
  8. Generalization for $n>2$ agents
  9. Collision avoidance implementation
  10. Numerical simulations
  11. Validation of the control gain selection and limitations
  12. Single agent case
  13. Two agent case
  14. Validation of the switching mechanism
  15. Two agent case
  16. ...and 4 more sections

Key Result

proposition 1

Under Asm. asm:max_speed, Asm. asm:tracking_at_t0, Asm. asm:coll_avoid_relay and the presence of a single agent, the adoption of control law eq:ctrl_law_1 with $K_{r} \geq K_{r}^{\star} = v_{M}/\mathrm{s}_{\gamma}$ implies that $\mathbf{g}_{r1}(t) \in \mathcal{C}$, $\forall t\geq 0$.

Figures (11)

  • Figure 1: Top view illustration of the control problem.
  • Figure 2: Single agent case scenario: geometric construction employed in Prop. \ref{['prop:oneagent']}.
  • Figure 3: (a): Two agents belonging to the same side of the FoV (yellow). (b): Two agents laying on the different sides of the FoV (yellow and pink).
  • Figure 4: Two-agent case scenario: geometric construction employed in Lem. \ref{['lemma:twoagents']}. Unit vectors $\mathbf{g}_{\scaleto{FoVj}{4pt}}^{\perp} = \mathbf{R}_{z}((-1)^{j}\pi/2) \mathbf{g}_{\scaleto{FoVj}{4pt}}$, with $j=1,2$, are also defined to help the visualization.
  • Figure 5: Illustration of the collision avoidance strategy under analysis: possible scenarios. Here $\mathcal{V}_{r}^{*} = \mathcal{V}_{r} = \{1,2\}$ holds.
  • ...and 6 more figures

Theorems & Definitions (16)

  • remark 1
  • proposition 1
  • proof
  • lemma 1
  • proof
  • proposition 2
  • proof
  • theorem 1
  • proof
  • remark 2
  • ...and 6 more