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Decentralized CBF-based Safety Filters for Collision Avoidance of Cooperative Missile Systems with Input Constraints

Johannes Autenrieb, Mark Spiller

TL;DR

This work addresses collision avoidance in multi-agent cooperative missile engagements under input constraints by developing a decentralized, event-triggered safety filter grounded in robust control barrier functions (RCBFs). Each agent solves a local quadratic program (QP) to minimally modify its nominal PNG-based acceleration, enforcing pairwise RCBF constraints for nearby neighbors, with a cooperative assumption a_j = -a_i when connected. To handle simultaneous constraint conflicts, a slack-variable prioritization scheme is introduced, weighted by distance and time-to-ZEM, yielding a Pareto-optimal trade-off that preserves critical safety while maintaining nominal performance when possible. Simulations on many-on-many interception scenarios demonstrate collision-free operation and minimal deviation from nominal guidance, highlighting scalability and practicality for safety-critical multi-agent aerospace systems.

Abstract

This paper presents a decentralized safety filter for collision avoidance in multi-agent aerospace interception scenarios. The approach leverages robust control barrier functions (RCBFs) to guarantee forward invariance of safety sets under bounded inputs and high-relative-degree dynamics. Each effector executes its nominal cooperative guidance command, while a local quadratic program (QP) modifies the input only when necessary. Event-triggered activation based on range and zero-effort miss (ZEM) criteria ensures scalability by restricting active constraints to relevant neighbors. To resolve feasibility issues from simultaneous constraints, a slack-variable relaxation scheme is introduced that prioritizes critical agents in a Pareto-optimal manner. Simulation results in many-on-many interception scenarios demonstrate that the proposed framework maintains collision-free operation with minimal deviation from nominal guidance, providing a computationally efficient and scalable solution for safety-critical multi-agent aerospace systems.

Decentralized CBF-based Safety Filters for Collision Avoidance of Cooperative Missile Systems with Input Constraints

TL;DR

This work addresses collision avoidance in multi-agent cooperative missile engagements under input constraints by developing a decentralized, event-triggered safety filter grounded in robust control barrier functions (RCBFs). Each agent solves a local quadratic program (QP) to minimally modify its nominal PNG-based acceleration, enforcing pairwise RCBF constraints for nearby neighbors, with a cooperative assumption a_j = -a_i when connected. To handle simultaneous constraint conflicts, a slack-variable prioritization scheme is introduced, weighted by distance and time-to-ZEM, yielding a Pareto-optimal trade-off that preserves critical safety while maintaining nominal performance when possible. Simulations on many-on-many interception scenarios demonstrate collision-free operation and minimal deviation from nominal guidance, highlighting scalability and practicality for safety-critical multi-agent aerospace systems.

Abstract

This paper presents a decentralized safety filter for collision avoidance in multi-agent aerospace interception scenarios. The approach leverages robust control barrier functions (RCBFs) to guarantee forward invariance of safety sets under bounded inputs and high-relative-degree dynamics. Each effector executes its nominal cooperative guidance command, while a local quadratic program (QP) modifies the input only when necessary. Event-triggered activation based on range and zero-effort miss (ZEM) criteria ensures scalability by restricting active constraints to relevant neighbors. To resolve feasibility issues from simultaneous constraints, a slack-variable relaxation scheme is introduced that prioritizes critical agents in a Pareto-optimal manner. Simulation results in many-on-many interception scenarios demonstrate that the proposed framework maintains collision-free operation with minimal deviation from nominal guidance, providing a computationally efficient and scalable solution for safety-critical multi-agent aerospace systems.

Paper Structure

This paper contains 7 sections, 1 theorem, 43 equations, 5 figures, 1 table.

Table of Contents

  1. Introduction
  2. Preliminaries
  3. Problem Formulation
  4. Decentralized Robust CBF-based QP Formulation for Collision Avoidance
  5. Criticality-Based Prioritization under Conflicting Constraints
  6. Simulation Results
  7. Conclusion

Key Result

Theorem 1

Suppose $h\in\mathcal{G}^2$ and there exists $a_{\max}>0$ such that for all $(t,\mathbf{x})\in [t_0,\infty)\times \mathcal{S}(t)$, Then the function is a RCBF on the set i.e., for any class-$\mathcal{K}$ function $\alpha$ and all $t\in[t_0,\infty)$, $\mathbf{x}\in\mathcal{S}^{res}_H(t)$. The set is non-empty for any class-$\mathcal{K}$ function $\alpha$ and any $(t,\mathbf{x})\in[t_0,\infty)\

Figures (5)

  • Figure 1: Illustration of decentralized, event-triggered safety filtering in a many-on-many interception mission with cooperative effectors.
  • Figure 2: 3D trajectories with PNG only. Missiles 1 and 2 collide at $t=6.43\,$s.
  • Figure 3: Position histories with PNG only. Collision occurs between Missiles 1 and 2.
  • Figure 4: 3D trajectories with PNG + safety filter. All missiles intercept safely.
  • Figure 5: Position histories with PNG + safety filter. Separation maintained.

Theorems & Definitions (3)

  • Definition 1
  • Definition 2
  • Theorem 1: breeden2023robust