The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Obstacle Detection and Collision Avoidance for a UAV With Complementary Low-Cost Sensors
Open accessAbstract
This paper demonstrates an innovative and simple solution for obstacle detection and collision avoidance of unmanned aerial vehicles (UAVs) optimized for and evaluated with quadrotors. The sensors exploited in this paper are low-cost ultrasonic and infrared range finders, which are much cheaper though noisier than more expensive sensors such as laser scanners. This needs to be taken into consideration for the design, implementation, and parametrization of the signal processing and control algorithm for such a system, which is the topic of this paper. For improved data fusion, inertial and optical flow sensors are used as a distance derivative for reference. As a result, a UAV is capable of distance controlled collision avoidance, which is more complex and powerful than comparable simple solutions. At the same time, the solution remains simple with a low computational burden. Thus, memory and time-consuming simultaneous localization and mapping is not required for collision avoidance.
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Citations
Cites
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Vision based MAV navigation in unknown and unstructured environments
Blösch, M., Weiss, S., Scaramuzza, D., & Siegwart, R. (2010) · 2010 IEEE International Conference on Robotics and Automation · doi:10.1109/robot.2010.5509920 · Cited by 428
Monocular‐SLAM–based navigation for autonomous micro helicopters in GPS‐denied environments
Weiss, S., Scaramuzza, D., & Siegwart, R. (2011) · Journal of Field Robotics · doi:10.1002/rob.20412 · Cited by 414
A Fully Autonomous Indoor Quadrotor
Grzonka, S., Grisetti, G., & Burgard, W. (2012) · IEEE Transactions on Robotics · doi:10.1109/tro.2011.2162999 · Cited by 386
Autonomous multi-floor indoor navigation with a computationally constrained MAV
Shen, S., Michael, N., & Kumar, V. (2011) · 2011 IEEE International Conference on Robotics and Automation · doi:10.1109/icra.2011.5980357 · Cited by 357
Camera-based navigation of a low-cost quadrocopter
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The Stanford testbed of autonomous rotorcraft for multi agent control (STARMAC)
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Flying Fast and Low Among Obstacles: Methodology and Experiments
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Quadrotor Using Minimal Sensing For Autonomous Indoor Flight
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Cited by
A survey on vision-based UAV navigation
Lu, Y., Xue, Z., Xia, G.-S., & Zhang, L. (2018) · Geo-spatial Information Science · doi:10.1080/10095020.2017.1420509 · Cited by 448
Unmanned Aerial Vehicles (UAVs): Collision Avoidance Systems and Approaches
Yasin, J. N., Mohamed, S. A. S., Haghbayan, M.-H., Heikkonen, J., Tenhunen, H., & Plosila, J. (2020) · IEEE Access · doi:10.1109/access.2020.3000064 · Cited by 329
Survey of computer vision algorithms and applications for unmanned aerial vehicles
Al-Kaff, A., Martín, D., García, F., Escalera, A. D. L., & María Armingol, J. (2018) · Expert Systems with Applications · doi:10.1016/j.eswa.2017.09.033 · Cited by 246
DroneTalk: An Internet-of-Things-Based Drone System for Last-Mile Drone Delivery
Chen, K.-W., Xie, M.-R., Chen, Y.-M., Chu, T.-T., & Lin, Y.-B. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2021.3138432 · Cited by 88
Metadata
- Authors
- Gageik, N., Benz, P., & Montenegro, S.
- Venue
- IEEE Access
- Published
- 2015
- Volume
- 3
- Pages
- 599-609
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W1493644597
- Cited by
- 265
- References
- 14
- FWCI
- 15.60
- Type
- journal article
- Language
- en
- Open access
- gold
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
