Multi-Objective Path-Based D* Lite

Incrementalgraph search algorithms such as D* Lite reuse previous, and perhaps partial, searches to expedite subsequent path planning tasks. In this article, we are interested in developing incremental graph for finding problems simultaneously optimize multiple objectives travel risk, arrival time, etc. This is challenging because a multi-objective setting, the number of “Pareto-optimal” solutions can grow exponentially with respect size graph. article presents new algorithm called Multi-Objective Path-Based (MOPBD*) which leverages path-based expansion strategy prune dominated solutions. Additionally, introduce sub-optimal variant MOPBD* improve efficiency while approximating Pareto-optimal front. We numerically evaluate performance its variants various maps two three objectives. Results show that our approach more efficient than from scratch, runs up an order magnitude faster existing method planning.