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We address the challenge of generating a visibility graph for 3D path planning for a small- scale helicopter through an environment with geometric obstacles. The visibility graph is based on approximating a number of continuous dierentiable conguration space obstacles that are generated from the convex hull of their work space obstacles. An approximation to the optimal path can subsequently be found using an existing graph search algorithm. The presented approach is suitable for fully known environments with a large number of truly 3D (not merely "raised" 2D) obstacles. A test scenario for a small-scale helicopter inspecting a wind turbine is shown. We consider methods for path planning that can be used to operating a small-scale helicopter near the surface of obstacles. We distinguish the term "trajectory" from "path" in that a path is without time and trajectory includes time. In this paper we are mainly concerned with the geometric problem of path planning. We consider the general trajectory planning problem for a UAS as having two levels; 1) a path that avoids larger static obstacles, such as buildings, mountains, etc., and 2) a trajectory along the path that also avoids smaller, possibly mobile object and at the same time takes the dynamics of the vehicle into account by generating a feasible state trajectory and possibly a related control trajectory. The present work is a method for generating and optimal solution to the rst level. And because that level is static the method presented also prioritize the ability to easily do multi-query searches and replanning. We look at feasibility of the path from a qualitative perspective by preferring path with higher order of dierentiable. This means that we do not consider the structural and dynamical capabilities of the vehicle in greater details at this level. This and dynamic obstacles should be handled at a lower trajectory planning level, that generates full state and control trajectories, and typically also does single query searches because of the dynamic obstacles. Although we only look at top level path planning, we still employ a stepwise strategy, that more eciently can handle isolated changes in the environment as well as re-planning where only changes to via points change. This work is focused on path planning using visibility graphs that is based on the conguration

Configuration Space and Visibility Graph Generation from Geometric Workspaces for UAVs