Extracting Objects for Aerial Manipulation on UAVs Using Low Cost Stereo Sensors

Sensors

卷:16

Robert Bevec¹  Aleš Ude¹  Begoña C. Arrue²  Pablo Ramon Soria²  Aníbal Ollero² 

[1] Humanoid and Cognitive Robotics Lab, Department of Automatics, Biocybernetics and Robotics, Jožef Stefan Institute, Jamova cesta 39, Ljubljana 1000, Slovenia;

[2] Robotics, Vision and Control Group, University of Seville, Camino de los Descubrimientos, s/n, Seville 41092, Spain;

关键词: UAV;    object detection;    object recognition;    SVM;    manipulation;   

DOI  :  10.3390/s16050700

来源: DOAJ

【 摘 要 】

Giving unmanned aerial vehicles (UAVs) the possibility to manipulate objects vastly extends the range of possible applications. This applies to rotary wing UAVs in particular, where their capability of hovering enables a suitable position for in-flight manipulation. Their manipulation skills must be suitable for primarily natural, partially known environments, where UAVs mostly operate. We have developed an on-board object extraction method that calculates information necessary for autonomous grasping of objects, without the need to provide the model of the object’s shape. A local map of the work-zone is generated using depth information, where object candidates are extracted by detecting areas different to our floor model. Their image projections are then evaluated using support vector machine (SVM) classification to recognize specific objects or reject bad candidates. Our method builds a sparse cloud representation of each object and calculates the object’s centroid and the dominant axis. This information is then passed to a grasping module. Our method works under the assumption that objects are static and not clustered, have visual features and the floor shape of the work-zone area is known. We used low cost cameras for creating depth information that cause noisy point clouds, but our method has proved robust enough to process this data and return accurate results.

【 授权许可】

Unknown