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2019 | OriginalPaper | Buchkapitel

Object Grasping of Humanoid Robot Based on YOLO

verfasst von : Li Tian, Nadia Magnenat Thalmann, Daniel Thalmann, Zhiwen Fang, Jianmin Zheng

Erschienen in: Advances in Computer Graphics

Verlag: Springer International Publishing

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Abstract

This paper presents a system that aims to achieve autonomous grasping for micro-controller based humanoid robots such as the Inmoov robot [1]. The system consists of a visual sensor, a central controller and a manipulator. We modify the open sourced objection detection software YOLO (You Only Look Once) v2 [2] and associate it with the visual sensor to make the sensor be able to detect not only the category of the target object but also the location with the help of a depth camera. We also estimate the dimensions (i.e., the height and width) of the target based on the bounding box technique (Fig. 1). After that, we send the information to the central controller (a humanoid robot), which controls the manipulator (customised robotic hand) to grasp the object with the help of inverse kinematics theory. We conduct experiments to test our method with the Inmoov robot. The experiments show that our method is capable of detecting the object and driving the robotic hands to grasp the target object.

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Literatur
1.
Zurück zum Zitat Langevin, G.: Hand robot InMoov (2016) Langevin, G.: Hand robot InMoov (2016)
2.
Zurück zum Zitat Redmon, J., Farhadi, A.: YOLO9000: better, faster, stronger. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2017) Redmon, J., Farhadi, A.: YOLO9000: better, faster, stronger. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2017)
3.
Zurück zum Zitat Han, J., et al.: Advanced deep-learning techniques for salient and category-specific object detection: a survey. IEEE Signal Process. Mag. 35(1), 84–100 (2018)CrossRef Han, J., et al.: Advanced deep-learning techniques for salient and category-specific object detection: a survey. IEEE Signal Process. Mag. 35(1), 84–100 (2018)CrossRef
4.
Zurück zum Zitat Girshick, R.: Fast R-CNN. In: Proceedings of the IEEE International Conference on Computer Vision (2015) Girshick, R.: Fast R-CNN. In: Proceedings of the IEEE International Conference on Computer Vision (2015)
5.
Zurück zum Zitat Girshick, R., et al.: Rich feature hierarchies for accurate object detection and semantic segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2014) Girshick, R., et al.: Rich feature hierarchies for accurate object detection and semantic segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2014)
6.
Zurück zum Zitat Redmon, J., et al.: You only look once: unified, real-time object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2016) Redmon, J., et al.: You only look once: unified, real-time object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2016)
7.
Zurück zum Zitat Roa, M.A., Suárez, R.: Grasp quality measures: review and performance. Auton. Robots 38(1), 65–88 (2015)CrossRef Roa, M.A., Suárez, R.: Grasp quality measures: review and performance. Auton. Robots 38(1), 65–88 (2015)CrossRef
8.
Zurück zum Zitat Tikhanoff, V., et al.: Exploring affordances and tool use on the iCub. In: 2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids). IEEE (2013) Tikhanoff, V., et al.: Exploring affordances and tool use on the iCub. In: 2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids). IEEE (2013)
9.
Zurück zum Zitat Kurban, R., Skuka, F., Bozpolat, H.: Plane segmentation of kinect point clouds using RANSAC. In: The 7th International Conference on Information Technology (2015) Kurban, R., Skuka, F., Bozpolat, H.: Plane segmentation of kinect point clouds using RANSAC. In: The 7th International Conference on Information Technology (2015)
10.
Zurück zum Zitat Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381–395 (1981)MathSciNetCrossRef Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381–395 (1981)MathSciNetCrossRef
11.
Zurück zum Zitat Dakarimov, S., et al.: Study on the development and control of humanoid robot arm using MatLab/Arduino. 유공압건설기계학회 학술대회논문집, pp. 88–90 (2018) Dakarimov, S., et al.: Study on the development and control of humanoid robot arm using MatLab/Arduino. 유공압건설기계학회 학술대회논문집, pp. 88–90 (2018)
12.
Zurück zum Zitat Thalmann, N.M., Tian, L., Yao, F.: Nadine: a social robot that can localize objects and grasp them in a human way. In: Prabaharan, S.R.S., Thalmann, N.M., Kanchana Bhaaskaran, V.S. (eds.) Frontiers in Electronic Technologies. LNEE, vol. 433, pp. 1–23. Springer, Singapore (2017). https://doi.org/10.1007/978-981-10-4235-5_1CrossRef Thalmann, N.M., Tian, L., Yao, F.: Nadine: a social robot that can localize objects and grasp them in a human way. In: Prabaharan, S.R.S., Thalmann, N.M., Kanchana Bhaaskaran, V.S. (eds.) Frontiers in Electronic Technologies. LNEE, vol. 433, pp. 1–23. Springer, Singapore (2017). https://​doi.​org/​10.​1007/​978-981-10-4235-5_​1CrossRef
13.
Zurück zum Zitat Tian, L., et al.: The making of a 3D-printed, cable-driven, single-model, lightweight humanoid robotic hand. Front. Robot. AI 4, 65 (2017)CrossRef Tian, L., et al.: The making of a 3D-printed, cable-driven, single-model, lightweight humanoid robotic hand. Front. Robot. AI 4, 65 (2017)CrossRef
14.
Zurück zum Zitat Tian, L., et al.: A methodology to model and simulate customized realistic anthropomorphic robotic hands. In: Proceedings of Computer Graphics International 2018. ACM (2018) Tian, L., et al.: A methodology to model and simulate customized realistic anthropomorphic robotic hands. In: Proceedings of Computer Graphics International 2018. ACM (2018)
15.
Zurück zum Zitat Tian, L., et al.: Nature grasping by a cable-driven under-actuated anthropomorphic robotic hand. TELKOMNIKA 17(1), 1–7 (2019)CrossRef Tian, L., et al.: Nature grasping by a cable-driven under-actuated anthropomorphic robotic hand. TELKOMNIKA 17(1), 1–7 (2019)CrossRef
Metadaten
Titel
Object Grasping of Humanoid Robot Based on YOLO
verfasst von
Li Tian
Nadia Magnenat Thalmann
Daniel Thalmann
Zhiwen Fang
Jianmin Zheng
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-22514-8_47