Skip to main content

An incremental sampling-based approach to inspection planning: the rapidly exploring random tree of trees

  • Andreas Bircher (a1), Kostas Alexis (a2), Ulrich Schwesinger (a1), Sammy Omari (a1), Michael Burri (a1) and Roland Siegwart (a1)...

A new algorithm, called rapidly exploring random tree of trees (RRTOT) is proposed, that aims to address the challenge of planning for autonomous structural inspection. Given a representation of a structure, a visibility model of an onboard sensor, an initial robot configuration and constraints, RRTOT computes inspection paths that provide full coverage. Sampling based techniques and a meta-tree structure consisting of multiple RRT* trees are employed to find admissible paths with decreasing cost. Using this approach, RRTOT does not suffer from the limitations of strategies that separate the inspection path planning problem into that of finding the minimum set of observation points and only afterwards compute the best possible path among them. Analysis is provided on the capability of RRTOT to find admissible solutions that, in the limit case, approach the optimal one. The algorithm is evaluated in both simulation and experimental studies. An unmanned rotorcraft equipped with a vision sensor was utilized as the experimental platform and validation of the achieved inspection properties was performed using 3D reconstruction techniques.

Corresponding author
*Corresponding author. E-mail:
Hide All
1. Stumm, E., Breitenmoser, A., Pomerleau, F., Pradalier, C. and Siegwart, R., “Tensor-voting-based navigation for robotic inspection of 3d surfaces using lidar point clouds,” 31 (12), 14651488 (2012).
2. Burri, M., Nikolic, J., Hurzeler, C., Caprari, G. and Siegwart, R., “Aerial Service Robots for Visual Inspection of Thermal Power Plant Boiler Systems,” Applied Robotics for the Power Industry, 2012 2nd International Conference on Zurich, Switzerland (2012) pp. 70–75.
3. Englot, B. and Hover, F. S., “Three-dimensional coverage planning for an underwater inspection robot,” 32 (9–10), 10481073 (2013).
4. Bircher, A., Alexis, K., Burri, M., Oettershagen, P., Omari, S., Mantel, T. and Siegwart, R., “Structural Inspection Path Planning Via Iterative Viewpoint Resampling with Application to Aerial Robotics,” IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA (May 2015) pp. 6423–6430. [Online]. Available:
5. Bircher, A., Kamel, M., Alexis, K., Burri, M., Oettershagen, P., Omari, S., Mantel, T. and Siegwart, R., “Three-dimensional coverage path planning via viewpoint resampling and tour optimization for aerial robots,” Autonomous Robots, Springer US, 1–25 (2015). DOI: 10.1007/s10514-015-9517-1, ISSN: 15737527.
6. Galceran, E. and Marc, M. Carreras, “A survey on coverage path planning for robotics,” Robot. Auton. Syst. 61 (12), 12581276 (2013).
7. Barraquand, J. and Latombe, J.-C., “Robot motion planning: A distributed representation approach,” Int. J. Robot. Res. 10, 628649 (1991).
8. Choset, H., “Coverage for robotics–a survey of recent results,” Ann. Math. Artif. Intell. 31 (1–4), 113126 (2001).
9. Zelinsky, A., Jarvis, R. A., Byrne, J. and Yuta, S., “Planning Paths of Complete Coverage of an Unstructured Environment by a Mobile Robot,” Proceedings of International Conference on Advanced Robotics vol. 13, Tsukuba (1993) pp. 533–538.
10. Urrutia, J., “Art Gallery and Illumination Problems,” In: Handbook of Computational Geometry, Instituto de Mathematicas, Universidad Nacional Autonoma de Mexico: Mexico (2000) pp. 9731027.
11. Shmoys, D., Lenstra, J., Kan, A. and Lawler, E., The Traveling Salesman Problem. Lenstra, J. K., Kan, A. R., Lawler, E. L., Shmoys, D. B., editors. The traveling salesman problem: a guided tour of combinatorial optimization. John Wiley & Sons (1985).
12. Englot, B. and Hover, F. S., “Sampling-Based Sweep Planning to Exploit Local Planarity in the Inspection of Complex 3d Structures,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, Vilamoura (2012) pp. 4456–4463.
13. Danner, T. and Kavraki, L. E., “Randomized planning for short inspection paths,” IEEE International Conference in Robotics and Automation, 2000, Apr 24, Vol. 2, pp. 971–976, San Francisco, CA, USA.
14. Blaer, P. S. and Allen, P. K., “View planning and automated data acquisition for three-dimensional modeling of complex sites,” J. Field Robot. 26 (11–12), 865891.
15. Papadopoulos, G., Kurniawati, H. and Patrikalakis, N., “Asymptotically Optimal Inspection Planning using Systems with Differential Constraints,” Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany (2013) pp. 4126–4133.
16. Karaman, S. and Frazzoli, E., “Sampling-based algorithms for optimal motion planning,” Int. J. Robot. Res. 30 (7), 846894 (2011).
17. Plaku, E., Bekris, K. E., Chen, B. Y., Ladd, A. M. and Kavraki, L., “Sampling-based roadmap of trees for parallel motion planning,” IEEE Trans. Robot. 21 (4), 597608 (2005).
18. Wang, W., Yan, L., Xu, X. and Yang, S. X., “An Adaptive Roadmap Guided Multi-RRTs Strategy for Single Query Path Planning,” Proceedings of the 2010 IEEE International Conference on Robotics and Automation (ICRA), IEEE, Anchorage, AK, USA (2010) pp. 2871–2876.
19. Devaurs, D., Simeon, T., Cortés, J. et al., “A Multi-Tree Extension of the Transition-Based RRT: Application to Ordering-and-Pathfinding Problems in Continuous Cost Spaces,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Chicago, IL, USA (2014) pp. 2991–2996.
20. Hsu, D., Kindel, R., Latombe, J. C. and Rock, S., “Randomized kinodynamic motion planning with moving obstacles,” The International Journal of Robotics Research, 21 (3), 233255 (2002 March). doi: 10.1177/027836402320556421.
21. Achtelik, M. W., Lynen, S., Chli, M. and Siegwart, R., “Inversion Based Direct Position Control and Trajectory Following for Micro Aerial Vehicles,” IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), Tokyo, JP (2013) pp. 2933–2939.
22. Nikolic, J., Rehder, J., Burri, M., Gohl, P., Leutenegger, S., Furgale, P. T. and Siegwart, R., “A Synchronized Visual-Inertial Sensor System with FPGA Pre-Processing for Accurate Real-Time Slam,” Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) IEEE, Hong Kong (2014) pp. 431–437.
23. Ascending Technologies GmbH, “”.
24. Autodesk Inc., “”.
25. Hornung, A., Wurm, K. M., Bennewitz, M., Stachniss, C. and Burgard, W., “OctoMap: An efficient probabilistic 3D mapping framework based on octrees,” Auton. Robots 34 (3), 189206 (2013).
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

  • ISSN: 0263-5747
  • EISSN: 1469-8668
  • URL: /core/journals/robotica
Please enter your name
Please enter a valid email address
Who would you like to send this to? *


Type Description Title
Supplementary materials

Bircher supplementary material
Bircher supplementary material 1

 Video (9.8 MB)
9.8 MB


Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed