Abstract
In this paper we present our approaches for solving this year’s virtual RoboCup @Home tasks with special focus on object detection and manipulation in the simulation environment Gazebo, which lead to our successful participation in the Open Platform League. There, we deployed the model of robot TIAGo Steel Edition, which is publicly provided by PAL Robotics. For object detection and pose estimation, we use a custom pixel-based clustering approach for segmenting potentially object supporting planes first. Instances of arbitrary and unknown objects can thus be detected and suitable grasping poses can be deduced. We perform object recognition by training our YOLO v3 network on a synthetic dataset of rendered YCB object images with Blender. A generalized grasping pipeline, which integrates extent and orientation information from our general object detection, performs planning and execution of combined arm and torso trajectory using MoveIt.
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Notes
- 1.
ROS wiki entry of robot TIAGo: http://wiki.ros.org/Robots/TIAGo.
- 2.
Blender website: https://www.blender.org/.
- 3.
MoveIt website: https://moveit.ros.org/.
- 4.
Public homer code repositories: https://gitlab.uni-koblenz.de/robbie/homer_navigation/, https://gitlab.uni-koblenz.de/robbie/homer_mapping.
References
Calli, B., Singh, A., Walsman, A., Srinivasa, S., Abbeel, P., Dollar, A.M.: The YCB object and model set: towards common benchmarks for manipulation research. In: 2015 International Conference on Advanced Robotics (ICAR), pp. 510–517. IEEE (2015)
Contreras, L., Matsusaka, Y., Yamamoto, T., Okada, H.: sDSPL - towards a benchmark for general-purpose task evaluation in domestic service robots. In: The 39th Annual Conference of the Robotics Society of Japan (2021)
Hornung, A., Wurm, K.M., Bennewitz, M., Stachniss, C., Burgard, W.: OctoMap: an efficient probabilistic 3D mapping framework based on octrees. Auton. Robot. 34(3), 189–206 (2013)
Koenig, N., Howard, A.: Design and use paradigms for gazebo, an open-source multi-robot simulator. In: 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No. 04CH37566), vol. 3, pp. 2149–2154. IEEE (2014)
Lima, P.U., Nardi, D., Kraetzschmar, G., Berghofer, J., Matteucci, M., Buchanan, G.: Rockin innovation through robot competitions [competitions]. IEEE Robot. Autom. Mag. 21(2), 8–12 (2014)
Lima, P.U., Nardi, D., Kraetzschmar, G.K., Bischoff, R., Matteucci, M.: RoCKIn and the European robotics league: building on RoboCup best practices to promote robot competitions in Europe. In: Behnke, S., Sheh, R., Sarıel, S., Lee, D.D. (eds.) RoboCup 2016. LNCS (LNAI), vol. 9776, pp. 181–192. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-68792-6_15
Memmesheimer, R., Mykhalchyshyna, I., Seib, V., Evers, T., Paulus, D.: homer@UniKoblenz: winning team of the RoboCup@Home open platform league 2018. In: Holz, D., Genter, K., Saad, M., von Stryk, O. (eds.) RoboCup 2018. LNCS (LNAI), vol. 11374, pp. 512–523. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-27544-0_42
Memmesheimer, R., Seib, V., Paulus, D.: homer@UniKoblenz: winning team of the RoboCup@Home open platform league 2017. In: Akiyama, H., Obst, O., Sammut, C., Tonidandel, F. (eds.) RoboCup 2017. LNCS (LNAI), vol. 11175, pp. 509–520. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00308-1_42
Pages, J., Marchionni, L., Ferro, F.: Tiago: the modular robot that adapts to different research needs. In: International Workshop on Robot Modularity, IROS (2016)
Redmon, J., Farhadi, A.: Yolov3: an incremental improvement. arXiv preprint arXiv:1804.02767 (2018)
Schneider, S., et al.: The rockin@ home challenge. In: ISR/Robotik 2014; 41st International Symposium on Robotics, pp. 1–7. VDE (2014)
Wisspeintner, T., Van Der Zant, T., Iocchi, L., Schiffer, S.: Robocup@ home: scientific competition and benchmarking for domestic service robots. Interact. Stud. 10(3), 392–426 (2009)
Acknowledgements
We want to thank the participating students Niklas Yann Wettengel, Robin Bartsch, Janine Buchholz, Maximilian Grothe and Kevin Fischer Rios. Also thanks to everybody in the RoboCup committees who have made RoboCup @Home in this pandemic possible despite all the obstacles and long working hours.
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Müller, D., Wettengel, N.Y., Paulus, D. (2022). homer@UniKoblenz: Winning Team of the RoboCup Virtual @Home Open Platform League 2021. In: Alami, R., Biswas, J., Cakmak, M., Obst, O. (eds) RoboCup 2021: Robot World Cup XXIV. RoboCup 2021. Lecture Notes in Computer Science(), vol 13132. Springer, Cham. https://doi.org/10.1007/978-3-030-98682-7_23
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