Transformed Stereo Vision and Structure Sensor for Development 3D Mapping on "FLoW" Humanoid Robot in Real Time

Ardiansyah Al Farouq, Raden Sanggar Dewanto, Dadet Pramadihanto

Abstract


In this paper, we proposed a method for building 3D Mapping environment in real time. The purpose of this model is to be able to approach the human ability to quickly know the environment. The problem of building a 3D mapping in real time is dependent on the efficiency of the algorithm to transform 2D images into depth data forms, which then transformed into a 3D model. This paper shows a method of transformation which has built an efficient algorithm because it can complete the entire sequential algorithm in real time. The algorithm has successfully run the whole system that only has a depth pixel error average of 18,10% and an average error of the system running in real time.

Keywords


3D Mapping; Stereo Matching; Robot Automation; Real Time System;

Full Text:

PDF

References


G. Dissanayake, P. Newman, S. Clark, H.F. Durrant-Whyte, and M. Csorba.,” A solution to the simultaneous localization and map building (SLAM) problem”, IEEE Transactions of Robotics and Automation, (2001).

M. Michael, T. Sebastian, K. Daphne, W. Ben., “FastSLAM: A Factored Solution to the Simultaneous Localization and Mapping Problem”, In Proceedings of the AAAI National Conference on Artificial Intelligence, (2002).

Bayu Setiawan, Oxsy Giandi, Dadet Pramadihanto, Raden Sanggar, Dewanto, Sritrusta Sukaridhoto, and Ahmad Subhan Khaillulah., “Flow head: 7 dof mechanism for flow humanoid”, In Control, Electronics, Renewable Energy and Communications (ICCEREC),International Conference on, pages 98–102. IEEE, (2015).

Hermann Von Helmholtz. Handbuch der physiologischen Optik,volume 9. Voss, 1867.

Jaesik Park, Hyeongwoo Kim, Yu-Wing Tai, Michael S Brown, and In So Kweon. “High-quality depth map upsampling and completion for rgb-d cameras”. IEEE Transactions on Image Processing, 23(12):5559–5572, (2014).

Jaesik Park, Hyeongwoo Kim, Yu-Wing Tai, Michael S Brown, and Inso Kweon. “High quality depth map upsampling for 3d-tof cameras”. In 2011 International Conference on Computer Vision, pages 1623–1630. IEEE, (2011).

Jing Liu, Chunpeng Li, Xuefeng Fan, and Zhaoqi Wang. “Reliable fusion of stereo matching and depth sensor for high quality dense depth maps”. Sensors, 15(8):20894–20924, (2015).

Zhu, J.; Wang, L.; Yang, R.; Davis, J.E.; Pan, Z. “Reliability fusion of time-of-flight depth and stereo geometry for high quality depth maps”. IEEE Trans. Pattern Anal. Mach. Intell. (2011), 33, 1400–1414.

Zhang, S.; Wang, C.; Chan, S. A “New High Resolution Depth Map Estimation System Using Stereo Vision and Depth Sensing Device”. In Proceedings of the IEEE 9th International Colloquium on Signal Processing and its Applications, Kuala Lumpur, Malaysia, (8–10 March 2013); pp. 49–53.

Wang, Y.; Jia, Y. A “fusion framework of stereo vision and Kinect for high-quality dense depth maps”. Comput. Vis. (2013), 7729, 109-120.

Yang, Q.; Yang, R.; Davis, J.; Nistér, D. “Spatial-depth super resolution for range images”. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Minneapolis, MN, USA, (17–22 June 2007).


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

ISSN: 2180-1843

eISSN: 2289-8131