Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Robot Conga: A Leader-Follower Walking Approach to Sequential Path Following in Multi-Agent Systems

Pranav Tiwari, Soumyodipta Nath

TL;DR

The paper tackles sequential path following in multi-agent systems by introducing Robot Conga, a centralized leader-follower scheme that propagates followers' references based on the leader’s spatial displacement along a shared trajectory, leveraging a global position reference from indoor localization. It develops a unicycle-based model with tracking error $e$ and a Lyapunov-based controller, yielding inputs $u(t)$ and $\omega(t)$ that guarantee asymptotic (and locally exponential) stability. The approach decouples progression from time, enabling robust, scalable performance across heterogeneous platforms (TurtleBot3 and Laikago) and real-time path updates via joystick-driven steering and B-spline interpolation, with proven convergence in simulation and demonstrations. This yields a practical formation-control framework for indoor applications like logistics, inspection, and surveillance, where precise spacing and synchronized traversal are essential while low-level actuation differences are abstracted away.

Abstract

Coordinated path following in multi-agent systems is a key challenge in robotics, with applications in automated logistics, surveillance, and collaborative exploration. Traditional formation control techniques often rely on time-parameterized trajectories and path integrals, which can result in synchronization issues and rigid behavior. In this work, we address the problem of sequential path following, where agents maintain fixed spatial separation along a common trajectory, guided by a leader under centralized control. We introduce Robot Conga, a leader-follower control strategy that updates each agent's desired state based on the leader's spatial displacement rather than time, assuming access to a global position reference, an assumption valid in indoor environments equipped with motion capture, vision-based tracking, or UWB localization systems. The algorithm was validated in simulation using both TurtleBot3 and quadruped (Laikago) robots. Results demonstrate accurate trajectory tracking, stable inter-agent spacing, and fast convergence, with all agents aligning within 250 time steps (approx. 0.25 seconds) in the quadruped case, and almost instantaneously in the TurtleBot3 implementation.

Robot Conga: A Leader-Follower Walking Approach to Sequential Path Following in Multi-Agent Systems

TL;DR

The paper tackles sequential path following in multi-agent systems by introducing Robot Conga, a centralized leader-follower scheme that propagates followers' references based on the leader’s spatial displacement along a shared trajectory, leveraging a global position reference from indoor localization. It develops a unicycle-based model with tracking error and a Lyapunov-based controller, yielding inputs and that guarantee asymptotic (and locally exponential) stability. The approach decouples progression from time, enabling robust, scalable performance across heterogeneous platforms (TurtleBot3 and Laikago) and real-time path updates via joystick-driven steering and B-spline interpolation, with proven convergence in simulation and demonstrations. This yields a practical formation-control framework for indoor applications like logistics, inspection, and surveillance, where precise spacing and synchronized traversal are essential while low-level actuation differences are abstracted away.

Abstract

Coordinated path following in multi-agent systems is a key challenge in robotics, with applications in automated logistics, surveillance, and collaborative exploration. Traditional formation control techniques often rely on time-parameterized trajectories and path integrals, which can result in synchronization issues and rigid behavior. In this work, we address the problem of sequential path following, where agents maintain fixed spatial separation along a common trajectory, guided by a leader under centralized control. We introduce Robot Conga, a leader-follower control strategy that updates each agent's desired state based on the leader's spatial displacement rather than time, assuming access to a global position reference, an assumption valid in indoor environments equipped with motion capture, vision-based tracking, or UWB localization systems. The algorithm was validated in simulation using both TurtleBot3 and quadruped (Laikago) robots. Results demonstrate accurate trajectory tracking, stable inter-agent spacing, and fast convergence, with all agents aligning within 250 time steps (approx. 0.25 seconds) in the quadruped case, and almost instantaneously in the TurtleBot3 implementation.

Paper Structure

This paper contains 18 sections, 16 equations, 8 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Preliminaries
  3. Unicycle Dynamics
  4. Error Dynamics and Control Law
  5. Lyapunov Functions and Asymptotic Stability
  6. Stability of the System
  7. Time Derivative of the Lyapunov Function
  8. Control Law
  9. Trajectory Propagation and Real-Time Adaptation in Leader-Follower Systems
  10. Spatial Propagation of Reference States
  11. Dynamic Path Adaptation Using Joystick Steering
  12. Trajectory Correction on Steep Ascent
  13. Results
  14. TurtleBot3 Implementation
  15. Laikago Quadruped Implementation
  16. ...and 3 more sections

Figures (8)

  • Figure 1: Displacement-based State Update
  • Figure 2: Leader-Follower Initialization
  • Figure 3: Key-Controlled Dynamic Trajectory
  • Figure 4: Interpolation Method Comparison
  • Figure 5: Tracking Performance on TurtleBot3: Positional and angular errors converge despite dynamic path changes. [Multiple spikes represent individual direction and velocity commands]
  • ...and 3 more figures