Cognitive Maps and Path Planning in Minkowski Spacetime: An Image‐Dilation Approach

We present a computationally simple yet efficient method for planning global trajectories in deterministic dynamic environments of arbitrary dimensions and complexity. The method leverages morphological operations on a discrete Minkowski spacetime and constructs cognitive maps that encode the earliest arrival time at each point. We established a solid theoretical foundation, ensuring the approach's applicability in risk‐critical missions. The method is illustrated using simulations of terrestrial robots and flying drones, resulting in efficient yet conservative solutions that closely mimic the behavior of biological agents.