SYGTMARODec 22, 2021

IDCAIS: Inter-Defender Collision-Aware Interception Strategy against Multiple Attackers

arXiv:2112.12098v3
Originality Incremental advance
AI Analysis

This addresses the challenge of coordinating defenders in dynamic environments to protect areas, but it is incremental as it builds on prior work by adding collision awareness.

The paper tackles the problem of multi-agent area defense by introducing an interception strategy that accounts for potential collisions among defenders, using a mixed-integer quadratic program to minimize capture times and manage collisions, with simulations demonstrating its effectiveness.

In the prior literature on multi-agent area defense games, the assignments of the defenders to the attackers are done based on a cost metric associated only with the interception of the attackers. In contrast to that, this paper presents an Inter-Defender Collision-Aware Interception Strategy (IDCAIS) for defenders to intercept attackers in order to defend a protected area, such that the defender-to-attacker assignment protocol not only takes into account an interception-related cost but also takes into account any possible future collisions among the defenders on their optimal interception trajectories. In particular, in this paper, the defenders are assigned to intercept attackers using a mixed-integer quadratic program (MIQP) that: 1) minimizes the sum of times taken by defenders to capture the attackers under time-optimal control, as well as 2) helps eliminate or delay possible future collisions among the defenders on the optimal trajectories. To prevent inevitable collisions on optimal trajectories or collisions arising due to time-sub-optimal behavior by the attackers, a minimally augmented control using exponential control barrier function (ECBF) is also provided. Simulations show the efficacy of the approach.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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