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Autonomous Robots
Erschienen in: Autonomous Robots 7/2017

25.01.2017

On-board model-based automatic collision avoidance: application in remotely-piloted unmanned aerial vehicles

verfasst von: Daman Bareiss, Joseph R. Bourne, Kam K. Leang

Erschienen in: Autonomous Robots | Ausgabe 7/2017

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Abstract

This paper focuses on real-world implementation and verification of a local, model-based stochastic automatic collision avoidance algorithm, with application in remotely-piloted (tele-operated) unmanned aerial vehicles (UAVs). Automatic collision detection and avoidance for tele-operated UAVs can reduce the workload of pilots to allow them to focus on the task at hand, such as searching for victims in a search and rescue scenario following a natural disaster. The proposed algorithm takes the pilot’s input and exploits the robot’s dynamics to predict the robot’s trajectory for determining whether a collision will occur. Using on-board sensors for obstacle detection, if a collision is imminent, the algorithm modifies the pilot’s input to avoid the collision while attempting to maintain the pilot’s intent. The algorithm is implemented using a low-cost on-board computer, flight-control system, and a two-dimensional laser illuminated detection and ranging sensor for obstacle detection along the trajectory of the robot. The sensor data is processed using a split-and-merge segmentation algorithm and an approximate Minkowski difference. Results from flight tests demonstrate the algorithm’s capabilities for tele-operated collision-free control of an experimental UAV.
Vorheriger Artikel Autonomous exploration of motor skills by skill babbling

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Metadaten
Titel
On-board model-based automatic collision avoidance: application in remotely-piloted unmanned aerial vehicles
verfasst von
Daman Bareiss
Joseph R. Bourne
Kam K. Leang
Publikationsdatum
25.01.2017
Verlag
Springer US
Erschienen in
Autonomous Robots / Ausgabe 7/2017
Print ISSN: 0929-5593
Elektronische ISSN: 1573-7527
DOI
https://doi.org/10.1007/s10514-017-9614-4

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