[en] Object detection and tracking is a challenging task, especially for unmanned aerial robots in complex environments where both static and dynamic objects are present. It is, however, essential for ensuring safety of the robot during navigation in such environments. In this work we present a practical online approach which is based on a 2D LIDAR. Unlike common approaches in the literature of modeling the environment as 2D or 3D occupancy grids, our approach offers a fast and robust method to represent the objects in the environment in a compact form, which is significantly more efficient in terms of both memory and computation in comparison with the former. Our approach is also capable of classifying objects into categories such as static and dynamic, and tracking dynamic objects as well as estimating their velocities with reasonable accuracy.
Wang, Min ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Voos, Holger ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Su, Daobilige; University of Sydney > Australian Center for Field Robotics (ACFR)
External co-authors :
yes
Language :
English
Title :
Robust Online Obstacle Detection and Tracking for Collision-free Navigation of Multirotor UAVs in Complex Environments
Publication date :
2018
Event name :
The 15th International Conference on Control, Automation, Robotics and Vision
Event place :
Singapore, Singapore
Event date :
from 18-11-2018 to 21-11-2018
Audience :
International
Main work title :
15th International Conference on Control, Automation, Robotics and Vision (ICARCV), Singapore 18-21 November 2018
Pages :
1228 - 1234
Peer reviewed :
Peer reviewed
FnR Project :
FNR10484117 - Robust Emergency Sense-and-avoid Capability For Small Remotely Piloted Aerial Systems, 2015 (01/02/2016-31/01/2019) - Holger Voos
B. Albaker and N. Rahim, "A survey of collision avoidance approaches for unmanned aerial vehicles, " in 2009 International Conference for Technical Postgraduates (TECHPOS), 2009, pp. 1-7.
Y. Wu, Y. Sui, and G. Wang, "Vision-based real-time aerial object localization and tracking for uav sensing system, " IEEE Access, vol. 5, pp. 23 969-23 978, 2017.
A. Al-Kaff, F. Garca, D. Martn, A. De La Escalera, and J. M. Armingol, "Obstacle detection and avoidance system based on monocular camera and size expansion algorithm for uavs, " Sensors, vol. 17, no. 5, p. 1061, 2017.
T. Toda, G. Masuyama, and K. Umeda, "Detecting moving objects using optical flow with a moving stereo camera, " in Adjunct Proceedings of the 13th International Conference on Mobile and Ubiquitous Systems: Computing Networking and Services, 2016, pp. 35-40.
A. Ess, B. Leibe, K. Schindler, and L. van Gool, "Moving obstacle detection in highly dynamic scenes, " in 2009 IEEE International Conference on Robotics and Automation (ICRA), 2009, pp. 56-63.
M. Odelga, P. Stegagno, and H. H. Bülthoff, "Obstacle detection, tracking and avoidance for a teleoperated uav, " in 2016 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2016, pp. 2984-2990.
F. S. Leira, "Object detection and tracking with uavs: A framework for uav object detection and tracking using a thermal imaging camera, " 2017.
A. Azim and O. Aycard, "Detection, classification and tracking of moving objects in a 3d environment, " in 2012 IEEE Intelligent Vehicles Symposium, 2012, pp. 802-807.
G. Gate and F. Nashashibi, "An approach for robust mapping, detection, tracking and classification in dynamic environments, " in 2009 International Conference on Advanced Robotics, 2009, pp. 1-6.
M. Becker, R. Hall, S. Kolski, K. Macek, R. Siegwart, and B. Jensen, "2d laser-based probabilistic motion tracking in urban-like environments, " Journal of the Brazilian Society of Mechanical Sciences and Engineering, vol. 31, no. 2, pp. 83-96, 2009.
L. Garca-Pérez, M. C. Garca-Alegre, Á. Ribeiro, D. Guinea, and J. M. Cañas, "Perception and tracking of dynamic objects for optimization of avoidance strategies in autonomous piloting of vehicles, " in International Conference on Spatial Cognition, 2004, pp. 500-517.
C.-C. Wang, C. Thorpe, and S. Thrun, "Online simultaneous localization and mapping with detection and tracking of moving objects: Theory and results from a ground vehicle in crowded urban areas, " in 2003 IEEE International Conference on Robotics and Automation (ICRA), vol. 1, 2003, pp. 842-849.
C.-C. Wang and C. Thorpe, "Simultaneous localization and mapping with detection and tracking of moving objects, " in 2002 IEEE International Conference on Robotics and Automation (ICRA), vol. 3, 2002, pp. 2918-2924.
M. Dekan, D. Frantisek, B. Andrej, R. Jozef, R. Dávid, and M. Josip, "Moving obstacles detection based on laser range finder measurements, " International Journal of Advanced Robotic Systems, vol. 15, no. 1, p. 1729881417748132, 2018.
C. Mertz, L. E. Navarro-Serment, R. MacLachlan, P. Rybski, A. Steinfeld, A. Suppe, C. Urmson, N. Vandapel, M. Hebert, C. Thorpe, et al., "Moving object detection with laser scanners, " Journal of Field Robotics, vol. 30, no. 1, pp. 17-43, 2013.
K. Rebai, A. Benabderrahmane, O. Azouaoui, and N. Ouadah, "Moving obstacles detection and tracking with laser range finder, " in 2009 International Conference on Advanced Robotics, 2009, pp. 1-6.
M. Przybya, "Detection and tracking of 2d geometric obstacles from lrf data, " in 2017 11th International Workshop on Robot Motion and Control (RoMoCo), 2017, pp. 135-141.
A. Mendes, L. C. Bento, and U. Nunes, "Multi-target detection and tracking with a laser scanner, " in Intelligent Vehicles Symposium, 2004 IEEE. IEEE, 2004, pp. 796-801.
M. Lakrouf, S. Larnier, M. Devy, and N. Achour, "Moving obstacles detection and camera pointing for mobile robot applications, " in Proceedings of the 3rd International Conference on Mechatronics and Robotics Engineering, 2017, pp. 57-62.
H. Cho, Y.-W. Seo, B. V. Kumar, and R. R. Rajkumar, "A multisensor fusion system for moving object detection and tracking in urban driving environments, " in 2014 IEEE International Conference on Robotics and Automation (ICRA), 2014, pp. 1836-1843.
M. S. Darms, P. E. Rybski, C. Baker, and C. Urmson, "Obstacle detection and tracking for the urban challenge, " IEEE Transactions on intelligent transportation systems, vol. 10, no. 3, pp. 475-485, 2009.
G. Monteiro, C. Premebida, P. Peixoto, and U. Nunes, "Tracking and classification of dynamic obstacles using laser range finder and vision, " in Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2006, pp. 1-7.
C. Premebida and U. Nunes, "Segmentation and geometric primitives extraction from 2d laser range data for mobile robot applications, " Robotica, vol. 2005, pp. 17-25, 2005.
