A real-time Plan-and-Avoid framework resolves predicted well-clear violations by generating minimally intrusive unilateral advisories to surrounding cooperative traffic while preserving a declared priority trajectory.
A fault-tolerant multi-agent reinforcement learning framework for unmanned aerial vehicles–unmanned ground vehicle coverage path planning,
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Plan-and-Avoid: Real-Time Aircraft Trajectory Coordination in a Multi-Agent Environment
A real-time Plan-and-Avoid framework resolves predicted well-clear violations by generating minimally intrusive unilateral advisories to surrounding cooperative traffic while preserving a declared priority trajectory.