Path planning has become a predominant issue for unmanned aerial vehicles (UAVs),
especially in complex indoor environments. Existing solutions for UAV indoor path planning …

In the multi-objective shortest-path problem we are interested in computing a path, or a set of
paths that simultaneously balance multiple cost functions. This problem is important for a …

Heuristic search algorithms, eg A*, are the commonly used tools for pathfinding on grids, ie
graphs of regular structure that are widely employed to represent environments in robotics …

The occurrence of large-magnitude disasters has significantly aroused public attention
regarding diversified site selection of emergency facilities. In particular, emergency airport …

Multi-UAV cooperative trajectory planning (MUCTP) refers to the planning of multiple flyable
trajectories based on the location of each UAV and mission point in a complex environment …

Multi-agent reinforcement learning (MARL) has recently excelled in solving challenging
cooperative and competitive multi-agent problems in various environments with, mostly, few …

Counting the number of shortest paths on a grid is a simple procedure with close ties to
Pascal's triangle. We show how path counting can be used to select relatively direct grid …

Path finding is a well-studied problem in AI, which is often framed as graph search. Any-
angle path finding is a technique that augments the initial graph with additional edges to …

Environment modeling serves as the foundation for path planning in unmanned systems.
Single-scale maps have many nodes and impose large memory requirements; tree-based …

Path planning is a critical task in automated navigation and seeks to identify optimal collision-
free routes for autonomous systems such as unmanned vehicles, aircrafts, and surface ships …