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Dokumenttyp:
Konferenzbeitrag 
Autor(en):
Kaldestad, K.B.; Haddadin, S.; Belder, R.; Hovland, G.; Anisi, D.A. 
Titel:
Collision avoidance with potential fields based on parallel processing of 3D-point cloud data on the GPU 
Abstract:
In this paper we present an experimental study on real-time collision avoidance with potential fields that are based on 3D point cloud data and processed on the Graphics Processing Unit (GPU). The virtual forces from the potential fields serve two purposes. First, they are used for changing the reference trajectory. Second they are projected to and applied on torque control level for generating according nullspace behavior together with a Cartesian impedance main control loop. The GPU algorithm...    »
 
Stichworte:
collision avoidance; control engineering computing; graphics processing units; industrial robots; mobile robots; parallel processing; torque control; trajectory control; 3D-point cloud data; Cartesian impedance main control loop; GPU; KUKA/DLR lightweight robot; collision avoidance; graphics processing unit; industrial manufacturing; parallel processing; potential fields; reference trajectory planning; torque control level; Collision avoidance; Force; Graphics processing units; Robot sensing sys...    »
 
Kongress- / Buchtitel:
Robotics and Automation (ICRA), 2014 IEEE International Conference on 
Jahr:
2014 
Monat:
May 
Seiten:
3250-3257