Abstract
Automatic robotic inspection of arbitrary free-form shapes is relevant for many quality control applications in different industries. We propose a method for planning the motion of an industrial robot to perform ultrasonic inspection of varying 3D shapes. Our method starts with the calculation of a set of sub-paths. These sub-paths are derived from streamlines. The underlying vector field is deduced from local curvature of the inspected geometry. Intermediate robot motions are planned to connect individual sub-paths to obtain a single complete inspection path. Coverage is calculated via ray tracing to simulate the propagation of ultrasound signals. This simulation enables the algorithm to proceed adaptively and to find a good trade-off between path length and coverage. We report experiments for four different geometries. The results indicate that shorter paths are achieved by using ray tracing for adaptive adjustment of streamline density. Our algorithm is tailored to ultrasonic inspection. However, the main concept of exploiting local surface curvature and streamlines for coverage path planning generalizes to other robotic inspection problems.
Highlights
Coverage path planning (CPP) deals with the problem of finding a path for a robot to cover some region of interest
This approach is compared to a baseline algorithm that does not consider the volumetric inspection, but considers surface points in a certain proximity d to the streamline as inspected
Local curvature is taken as the measure to evolve individual streamlines
Summary
Coverage path planning (CPP) deals with the problem of finding a path for a robot to cover some region of interest. With the growing number of applications related to mobile robotics, CPP is a highly relevant problem to study. This is especially true as robotic applications cover more and more areas of everyday human life. The definition of what region is covered by which robot configuration or position strongly depends on the application. While the ray tracing approach is very specific to UT, the heuristic of using streamlines is applicable to other coverage planning problems.
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