  The paper presents a path planning algorithm based on RRT* that addresses the
risk of grounding during evasive manoeuvres to avoid collision. The planner
achieves this objective by integrating a collective navigation experience with
the systematic use of water depth information from the electronic navigational
chart. Multivariate kernel density estimation is applied to historical AIS data
to generate a probabilistic model describing seafarer's best practices while
sailing in confined waters. This knowledge is then encoded into the RRT* cost
function to penalize path deviations that would lead own ship to sail in
shallow waters. Depth contours satisfying the own ship draught define the
actual navigable area, and triangulation of this non-convex region is adopted
to enable uniform sampling. This ensures the optimal path deviation.
