Abstract
The most critical process in the inspection is the structure coverage which is a time and resource intensive task. In this paper, Search Space Coverage Path Planning (SSCPP) algorithm for inspecting complex structure using a vehicular system consisting of Unmanned Aerial Vehicle (UAV) is proposed. The proposed algorithm exploits our knowledge of the structure model, and the UAV’s onboard sensors to generate coverage paths that maximizes coverage and accuracy. The algorithm supports the integration of multiple sensors to increase the coverage at each viewpoint and reduce the mission time. A weighted heuristic reward function is developed in the algorithm to target coverage, accuracy, travelled distance and turning angle at each viewpoint. The iterative processes of the proposed algorithm were accelerated exploiting the parallel architecture of the Graphics Processing Unit (GPU). A set of experiments using models of different shapes were conducted in simulated and real environments. The simulation and experimental results show the validity and effectiveness of the proposed algorithm.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Open source implementation of the presented algorithm as a ROS package. https://github.com/kucars/sspp
Gazebo (2015). http://gazebosim.org/
Alexis, K., Papachristos, C., Siegwart, R., Tzes, A.: Uniform coverage structural inspection path-planning for micro aerial vehicles. In: IEEE International Symposium on Intelligent Control - Proceedings, October 2015, pp. 59–64 (2015). https://doi.org/10.1109/ISIC.2015.7307280
Almadhoun, R., Taha, T., Seneviratne, L., Dias, J., Cai, G.: Aircraft inspection using unmanned aerial vehicles. In: International Micro Air Vehicle Competition and Conference, pp. 43–49 (2016). http://www.imavs.org/papers/2016/43_IMAV2016_Proceedings.pdf
Almadhoun, R., Taha, T., Seneviratne, L., Dias, J., Cai, G.: GPU accelerated coverage path planning optimized for accuracy in robotic inspection applications. In: 2016 IEEE 59th International Midwest Symposium on Circuits and Systems (MWSCAS), pp. 1–4 (2016). https://doi.org/10.1109/MWSCAS.2016.7869968
Atkar, P.N., Conner, D.C., Greenfield, A., Choset, H.: Hierarchical segmentation of surfaces embedded in R3 for auto-body painting. Algorithmic Found. Robot. VI 1, 27–42 (2005)
Bircher, A., et al.: Structural inspection path planning via iterative viewpoint resampling with application to aerial robotics, pp. 6423–6430 (2015)
Bircher, A., et al.: Three-dimensional coverage path planning via viewpoint resampling and tour optimization for aerial robots. Auton. Robots (2015). https://doi.org/10.1007/s10514-015-9517-1
Cheng, P., Keller, J., Kumar, V.: Time-optimal UAV trajectory planning for 3D urban structure coverage. In: 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS, pp. 2750–2757 (2008). https://doi.org/10.1109/IROS.2008.4650988
Christofides, N.: Worst-Case Analysis of a New Heuristic Prepared for the Travelling Salesman Problem, February 1976
Dornhege, C., Kleiner, A., Kolling, A.: Coverage search in 3D. In: 2013 IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2013 (2013). https://doi.org/10.1109/SSRR.2013.6719340
Englot, B., Hover, F.: Inspection planning for sensor coverage of 3D marine structures. In: IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings, pp. 4412–4417 (2010). https://doi.org/10.1109/IROS.2010.5648908
Englot, B., Hover, F.: Sampling-based coverage path planning for inspection of complex structures. In: ICAPS, pp. 29–37 (2012)
Englot, B., Hover, F.S.: Sampling-based sweep planning to exploit local planarity in the inspection of complex 3D structures. In: IEEE International Conference on Intelligent Robots and Systems, pp. 4456–4463 (2012). https://doi.org/10.1109/IROS.2012.6386126
Furrer, F., Burri, M., Achtelik, M., Siegwart, R.: RotorS—a modular Gazebo MAV simulator framework. In: Koubaa, A. (ed.) Robot Operating System (ROS): The Complete Reference (Volume 1). SCI, vol. 625, pp. 595–625. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-26054-9_23
Galceran, E., Carreras, M.: A survey on coverage path planning for robotics. Robot. Auton. Syst. 61(12), 1258–1276 (2013). https://doi.org/10.1016/j.robot.2013.09.004
Ground, A., Uav, V.: A hybrid path planning method in unmanned. IEEE Trans. Veh. Technol. 65(12), 9585–9596 (2016). https://doi.org/10.1109/TVT.2016.2623666
Haner, S., Heyden, A.: Discrete Optimal View Path Planning (2011)
Helsgaun, K.: Effective implementation of the Lin-Kernighan traveling salesman heuristic. Eur. J. Oper. Res. 126(1), 106–130 (2000). https://doi.org/10.1016/S0377-2217(99)00284-2
Heng, L., Gotovos, A., Krause, A., Pollefeys, M.: Efficient visual exploration and coverage with a micro aerial vehicle in unknown environments. In: IEEE International Conference on Robotics and Automation (2015)
Hong, S.: Accelerating CUDA graph algorithms at maximum warp. ACM SIGPLAN Not. 46, 267–276 (2011)
Hornung, A., Wurm, K.M., Bennewitz, M., Stachniss, C., Burgard, W.: OctoMap: an efficient probabilistic 3D mapping framework based on octrees. Auton. Robots 34(3), 189–206 (2013). https://doi.org/10.1007/s10514-012-9321-0
Hover, F.S., et al.: Advanced perception, navigation and planning for autonomous in-water ship hull inspection. Int. J. Robot. Res. 31(12), 1445–1464 (2012). https://doi.org/10.1177/0278364912461059
Janousek, P., Faigl, J.: Speeding up coverage queries in 3D multi-goal path planning. In: Proceedings - IEEE International Conference on Robotics and Automation, vol. 1, pp. 5082–5087 (2013). https://doi.org/10.1109/ICRA.2013.6631303
Karaman, S., Frazzoli, E.: Sampling-based algorithms for optimal motion planning. Int. J. Robot. Res. 30(7), 846–894 (2011). https://doi.org/10.1177/0278364911406761
Khoshelham, K., Elberink, S.O.: Accuracy and resolution of kinect depth data for indoor mapping applications. Sensors 12(12), 1437–1454 (2012). https://doi.org/10.3390/s120201437
Krainin, M., Curless, B., Fox, D.: Autonomous generation of complete 3D object models using next best view manipulation planning. In: Proceedings - IEEE International Conference on Robotics and Automation, pp. 5031–5037 (2011). https://doi.org/10.1109/ICRA.2011.5980429
Labbe, M., Michaud, F.: Online global loop closure detection for large-scale multi-session graph-based SLAM. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2661–2666 (2014)
Luo, C., Mcclean, S.I., Parr, G., Teacy, L., Nardi, R.D.: UAV position estimation and collision avoidance using the extended Kalman filter. IEEE Trans. Veh. Technol. 62(6), 2749–2762 (2013). https://doi.org/10.1109/TVT.2013.2243480
Optitrack, 25 March 2017. http://www.optitrack.com/
Papadopoulos, G., Kurniawati, H., Patrikalakis, N.M.: Asymptotically optimal inspection planning using systems with differential constraints, pp. 4111–4118 (2013)
PX4, 16 July 2015. http://px4.io/
Qin, H., et al.: Autonomous exploration and mapping system using heterogeneous UAVs and UGVs in GPS-denied environments. IEEE Trans. Veh. Technol. PP(c), 1 (2018). https://doi.org/10.1109/TVT.2018.2890416
ROS, 16 July 2015. http://www.ros.org/
Scott, W.R.: Model-based view planning. Mach. Vis. Appl. 20(1), 47–69 (2009). https://doi.org/10.1007/s00138-007-0110-2
Scott, W.R., Roth, G., Rivest, J.F.: View planning for automated three-dimensional object reconstruction and inspection. ACM Comput. Surv. 35(1), 64–96 (2003). https://doi.org/10.1145/641865.641868
Sehestedt, S., Paul, G., Rushton-smith, D., Liu, D.: Prior-knowledge assisted fast 3D map building of structured environments for steel bridge maintenance, pp. 1040–1046 (2013)
Trummer, M., Munkelt, C., Denzler, J.: Online next-best-view planning for accuracy optimization using an extended E-criterion. In: Proceedings - International Conference on Pattern Recognition, pp. 1642–1645 (2010). https://doi.org/10.1109/ICPR.2010.406
Valente, J., Barrientos, A., Cerro, J.D.: Coverage path planning to survey large outdoor areas with aerial robots: a comprehensive analysis. In: Introduction to Modern Robotics (2011)
Wallar, A., Plaku, E., Sofge, D.A.: A planner for autonomous risk-sensitive coverage (PARC OV ) by a team of unmanned aerial vehicles. In: IEEE Symposium on Swarm Intelligence (SIS) (2014). https://doi.org/10.1109/SIS.2014.7011807
Acknowledgements
This publication is based upon work supported by the Khalifa University of Science and Technology under Award No. RC1-2018-KUCARS.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Almadhoun, R., Taha, T., Dias, J., Seneviratne, L., Zweiri, Y. (2019). Coverage Path Planning for Complex Structures Inspection Using Unmanned Aerial Vehicle (UAV). In: Yu, H., Liu, J., Liu, L., Ju, Z., Liu, Y., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2019. Lecture Notes in Computer Science(), vol 11744. Springer, Cham. https://doi.org/10.1007/978-3-030-27541-9_21
Download citation
DOI: https://doi.org/10.1007/978-3-030-27541-9_21
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-27540-2
Online ISBN: 978-3-030-27541-9
eBook Packages: Computer ScienceComputer Science (R0)