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Distance-based Multiple Non-cooperative Ground Target Encirclement for Complex Environments

Fen Liu, Shenghai Yuan, Kun Cao, Wei Meng, Lihua Xie

Abstract

This paper proposes a comprehensive strategy for complex multi-target-multi-drone encirclement in an obstacle-rich and GPS-denied environment, motivated by practical scenarios such as pursuing vehicles or humans in urban canyons. The drones have omnidirectional range sensors that can robustly detect ground targets and obtain noisy relative distances. After each drone task is assigned, a novel distance-based target state estimator (DTSE) is proposed by estimating the measurement output noise variance and utilizing the Kalman filter. By integrating anti-synchronization techniques and pseudo-force functions, an acceleration controller enables two tasking drones to cooperatively encircle a target from opposing positions while navigating obstacles. The algorithms effectiveness for the discrete-time double-integrator system is established theoretically, particularly regarding observability. Moreover, the versatility of the algorithm is showcased in aerial-to-ground scenarios, supported by compelling simulation results. Experimental validation demonstrates the effectiveness of the proposed approach.

Distance-based Multiple Non-cooperative Ground Target Encirclement for Complex Environments

Abstract

This paper proposes a comprehensive strategy for complex multi-target-multi-drone encirclement in an obstacle-rich and GPS-denied environment, motivated by practical scenarios such as pursuing vehicles or humans in urban canyons. The drones have omnidirectional range sensors that can robustly detect ground targets and obtain noisy relative distances. After each drone task is assigned, a novel distance-based target state estimator (DTSE) is proposed by estimating the measurement output noise variance and utilizing the Kalman filter. By integrating anti-synchronization techniques and pseudo-force functions, an acceleration controller enables two tasking drones to cooperatively encircle a target from opposing positions while navigating obstacles. The algorithms effectiveness for the discrete-time double-integrator system is established theoretically, particularly regarding observability. Moreover, the versatility of the algorithm is showcased in aerial-to-ground scenarios, supported by compelling simulation results. Experimental validation demonstrates the effectiveness of the proposed approach.
Paper Structure (13 sections, 6 theorems, 53 equations, 14 figures, 1 algorithm)

This paper contains 13 sections, 6 theorems, 53 equations, 14 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. Preliminaries and Problem Formulation
  3. System Model
  4. Perception Measurements
  5. Task Assignment
  6. Problem Formulation
  7. Position estimation and control law
  8. Target State Estimator
  9. Encirclement Accelerate Controller
  10. Convergence analysis
  11. Simulation Results
  12. Experimental Results
  13. conclusion

Key Result

Lemma 1

(Uniform observability) Under Assumption limit and Assumption without_repulsive_force, the state model of target $j$ in eq3 with output equation eq5 is uniformly observable, implying that the observability Gramin matrix $\mathcal{O}_1$ satisfies $\Lambda_1I_{4\times4}\leq \mathcal{O}_1\leq\Lambda_2I

Figures (14)

  • Figure 1: Two drones “encircle” a moving target.
  • Figure 2: The onboard sensors configuration of drone.
  • Figure 3: Architecture of multiple non-cooperative ground target encirclement strategy.
  • Figure 4: Snapshots: The real-time position points where six drones encircle three targets.
  • Figure 5: The error trajectories of DTSE.
  • ...and 9 more figures

Theorems & Definitions (13)

  • Remark 1
  • Remark 2
  • Remark 3
  • Remark 4
  • Remark 5
  • Remark 6
  • Lemma 1
  • Lemma 2
  • Lemma 3
  • Theorem 1
  • ...and 3 more