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Design of a Formation Control System to Assist Human Operators in Flying a Swarm of Robotic Blimps

Tianfu Wu, Jiaqi Fu, Wugang Meng, Sungjin Cho, Huanzhe Zhan, Fumin Zhang

TL;DR

The paper tackles indoor swarm formation control for a trio of blimps under payload and sensing constraints, introducing a dynamic leader-switching framework operated via a human-in-the-loop UI. It combines monocular vision and laser altimetry for follower perception, with an external Ground PC handling perception and coordination while enabling any blimp to assume leadership. A novel leader-switch algorithm distributes maneuvering demands during sharp turns and a two-tier follower controller leverages outer distance and inner velocity loops, plus separate altitude and yaw control. Experimental results show that leader switching improves formation stability and success rates during dynamic indoor maneuvers, while highlighting occlusion challenges that motivate scalable, hierarchical coordination for larger swarms.

Abstract

Formation control is essential for swarm robotics, enabling coordinated behavior in complex environments. In this paper, we introduce a novel formation control system for an indoor blimp swarm using a specialized leader-follower approach enhanced with a dynamic leader-switching mechanism. This strategy allows any blimp to take on the leader role, distributing maneuvering demands across the swarm and enhancing overall formation stability. Only the leader blimp is manually controlled by a human operator, while follower blimps use onboard monocular cameras and a laser altimeter for relative position and altitude estimation. A leader-switching scheme is proposed to assist the human operator to maintain stability of the swarm, especially when a sharp turn is performed. Experimental results confirm that the leader-switching mechanism effectively maintains stable formations and adapts to dynamic indoor environments while assisting human operator.

Design of a Formation Control System to Assist Human Operators in Flying a Swarm of Robotic Blimps

TL;DR

The paper tackles indoor swarm formation control for a trio of blimps under payload and sensing constraints, introducing a dynamic leader-switching framework operated via a human-in-the-loop UI. It combines monocular vision and laser altimetry for follower perception, with an external Ground PC handling perception and coordination while enabling any blimp to assume leadership. A novel leader-switch algorithm distributes maneuvering demands during sharp turns and a two-tier follower controller leverages outer distance and inner velocity loops, plus separate altitude and yaw control. Experimental results show that leader switching improves formation stability and success rates during dynamic indoor maneuvers, while highlighting occlusion challenges that motivate scalable, hierarchical coordination for larger swarms.

Abstract

Formation control is essential for swarm robotics, enabling coordinated behavior in complex environments. In this paper, we introduce a novel formation control system for an indoor blimp swarm using a specialized leader-follower approach enhanced with a dynamic leader-switching mechanism. This strategy allows any blimp to take on the leader role, distributing maneuvering demands across the swarm and enhancing overall formation stability. Only the leader blimp is manually controlled by a human operator, while follower blimps use onboard monocular cameras and a laser altimeter for relative position and altitude estimation. A leader-switching scheme is proposed to assist the human operator to maintain stability of the swarm, especially when a sharp turn is performed. Experimental results confirm that the leader-switching mechanism effectively maintains stable formations and adapts to dynamic indoor environments while assisting human operator.
Paper Structure (19 sections, 8 equations, 9 figures, 1 table)

This paper contains 19 sections, 8 equations, 9 figures, 1 table.

Table of Contents

  1. INTRODUCTION
  2. RELATED WORK
  3. Traditional Leader Follower Strategy
  4. Dynamic Leader Selection
  5. Problem Formulation
  6. METHODOLOGY
  7. System Overview
  8. Leader Switch Algorithm
  9. Monocular Camera Relative Position Estimation
  10. Follower Controller Design
  11. Distance Controller
  12. Height Controller
  13. Yaw Controller
  14. EXPERIMENT
  15. Experimental Setup
  16. ...and 4 more sections

Figures (9)

  • Figure 1: Indoor blimp swarm and the blimp design.
  • Figure 2: Illustration of operator-controlled leader-switching during sharp turns.
  • Figure 3: Block diagram of indoor aerial swarm formation flight with three blimps.
  • Figure 4: Blimp swarm control UI with leader selection error alert.
  • Figure 5: Flow Charts of Leader Switch Algorithm
  • ...and 4 more figures