Swarm Trajectories Generation for Target Capturing With Uncertain Information

Fedele G., D'Alfonso L., Bono A., GAZİ V.

IEEE Transactions on Control of Network Systems, 2023 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Publication Date: 2023
  • Doi Number: 10.1109/tcns.2023.3258620
  • Journal Name: IEEE Transactions on Control of Network Systems
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, MathSciNet, zbMATH
  • Keywords: Aerospace electronics, distributed control law, Estimation, multi-agent system, Robot sensing systems, Sensors, Space vehicles, Target capturing, target enclosing, target surrounding, Target tracking, Uncertainty
  • Yıldız Technical University Affiliated: Yes


This work describes a methodology to generate trajectories for a swarm of agents, modeled as single integrators, for achieving target capturing/enclosing and containment. The discussed method proposes a robust solution which relaxes the strong assumptions about the exact knowledge of the target information. In particular, each agent requires a rough estimation of the reference, with an a-priori known bounded error both on the position and the velocity. It is shown that the swarm can be properly guided to enter a given capturing region while remaining outside a defined distancing region around the target. Steady-state analysis for velocity consensus is also provided for the case in which the reference information is exactly known by the agents.