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Welcome to the StructuralInspectionPlanner wiki!

Beta version

This toolbox implements the algorithm described in our ICRA 2015 paper contribution [1]

The algorithms iteraitvely samples viewpoints for every triangle of a mesh representing the structure and in a second step connects them by finding the best tour. In every iteration, the viewpoints are chosen such that the connections to the neighbouring viewpoints on the tour are minimized. The viewpoint sampling is formulated as a quadratic programming problem as described in [1] and solved with a fast solver [2]. The traveling salesman problem (finding the best tour) is solved using the Lin-Kernighan heuristic. Specifically, use is made of the implementation described in [3]. Local planning is achieved by means of the RRT* planner using the original implementation described in [4].

Two types of vehicles are supported: Rotorcraft and fixed-wing systems. For both, simplified models are employed. Conservative parameter choices allow the real system to track the computed path.

In order to find high quality paths, specific properties are required for meshes used to represent the structures to be inspected. Size and shape of the triangles must be such, that it can be inspected from a single pose, without too strict constraints on the choice. Namely, small size and similar lengths of their sides favour flexibility of choice for the viewpoints.

A good way to resample your mesh is the ACVD application for surface mesh coarsening and resampling.

Contents:

• Installation Instructions
• Visualization
• Demo Scenarios
• Interface
• Parameters
• Writing a Client
• Error Description
• Example Results
• Utilities

References:

1. A. Bircher, K. Alexis, M. Burri, P. Oettershagen, S. Omari, T. Mantel and R. Siegwart, “Structural inspection path planning via iterative viewpoint resampling with application to aerial robotics,” in Robotics and Automation (ICRA), 2015 IEEE International Conference on, May 2015, pp. 6423-6430
2. K. Helsguan, "An effective implementation of the lin-kernighan traveling salesman heuristic", European Journal of Operational Research, vol. 126, no. 1, pp. 106-130, 2000.
3. H.J. Ferreau and A. Potschka and C. Kirches, "qpOASES"
4. S. Karaman and E. Frazzoli, "Sampling-based algorithms for optimal motion planning", International Journal of Robotics Research", vol. 30, no. 7, pp. 846-894, 2011

If you use this software in a scientific publication, please cite the following paper:

@INPROCEEDINGS{BABOOMS_ICRA_15, 
author = "{A. Bircher, K. Alexis, M. Burri, P. Oettershagen, S. Omari, T. Mantel and R. Siegwart}",
booktitle = {Robotics and Automation (ICRA), 2015 IEEE International Conference on}, 
title={Structural Inspection Path Planning via Iterative Viewpoint Resampling with Application to Aerial Robotics}, 
year={2015}, 
month={May}, 
pages={6423-6430}, 
}

Credits:

This algorithm was developed by Andreas Bircher with the help and support of the members of the Autonomous Systems Lab. The work was supported by the European Commission-funded projects AEROWORKS and ICARUS.

Contact:

You can contact us for any question or remark:

• Andreas Bircher
• Kostas Alexis