Literature by the same author
plus at Google Scholar

Bibliografische Daten exportieren
 

A Fast, GPU-based Geometrical Placement Planner For Unknown Sensor-Modelled Objects And Placement Areas

Title data

Baumgartl, Johannes ; Werner, Tim ; Kaminsky, Per ; Henrich, Dominik:
A Fast, GPU-based Geometrical Placement Planner For Unknown Sensor-Modelled Objects And Placement Areas.
In: IEEE International Conference on Robotics and Automation. - Hongkong , 2014 . - pp. 1552-1559
DOI: https://doi.org/10.1109/ICRA.2014.6907058

Project information

Project title:
Project's official title
Project's id
PAP
No information

Abstract in another language

A Personal Robot should be able to handle unknown objects in unknown environments. For a manipulation task the question what to do with an object once it had been grasped is one of the most essential ones beside the grasping task itself. Moreover, the planning time should be at least as fast as the time the robot needs for its motions. We propose a fast placement planner for sensor-modelled objects in complex environments. The planner computes a stable position and orientation for the object in the environment. The algorithm uses only geometric information, most notably no force or torque sensor is required. In particular, we introduce a novel approach regarding the pose computation. By means of experiments with various household objects the robustness and performance are validated. Further on, we compare our approach with a pose computation using a physics simulation framework.

Further data

Item Type: Article in a book
Refereed: Yes
Keywords: Robotik; manipulation skills; on-line algorithms; parallel processing; Simulation; vision
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science III > Chair Applied Computer Science III - Univ.-Prof. Dr. Dominik Henrich
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 19 Feb 2025 15:36
Last Modified: 19 Feb 2025 15:36
URI: https://eref.uni-bayreuth.de/id/eprint/92478