Abstract
Warehouse robots rely on navigation algorithm to maneuver in the warehouse. One of the available navigation algorithm includes the use of vision technology. Yet, the technology requires depth cameras to act as “eyes” of the robot. It is known that cameras depend on lighting factor to operate. A sole example includes failure of vision-powered warehouse robots in extreme lighting conditions. Thus, this paper discusses the approach to enable warehouse robot in in-tense lighting conditions with implementation of two vision technology. In this paper, two depth cameras that function on different technology were used. The cameras chosen are stereoscopic camera and infrared based time-of-flight camera. This paper first studies the lighting factor that affects the performance of both cameras. Next, both camera were simulated in extreme lighting condition. The results obtained are further analyzed and constructed into a selective algorithm. This exploratory study is an important fundamental contribution to complete robot functioning warehouse in future.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bhattacharya, A.: Amazon is just beginning to use robots in its warehouses and they’re already making a huge difference (2016). https://qz.com/709541/amazon-is-just-beginning-to-use-robots-in-its-warehouses-and-theyre-already-making-a-huge-difference/. Accessed 27 Apr 2017
Tracy: Meet ‘Little Orange’, the cutest warehouse worker: self-charging robots can sort 20,000 parcels an hour at a Chinese courier firm (2017). http://www.dailymail.co.uk/news/article-4401108/Meet-Little-Orange-robot-warehouse-worker-China.html. Accessed 4 Sept 2017
Banker, S.: Robots in the Warehouse: It’s Not Just Amazon (2016). https://www.forbes.com/sites/stevebanker/2016/01/11/robots-in-the-warehouse-its-not-just-amazon/#790cd3be40b8. Accessed 27 Apr 2017
Bélanger-Barrette, M.: Robotic vision systems: what is doable? (2016). http://www.controleng.com/single-article/robotic-vision-systems-what-is-doable/dd4e2be762802d6dce70384b5a0cf257.html. Accessed 17 May 2017
Elberink, S.O., Khoshelham, K.: Accuracy and resolution of kinect depth data for indoor mapping applications. Sensors 12(2), 1437–1454 (2012). doi:10.3390/s120201437
Arafa, O., Amer, A.I., Zaki, A.M.: Microcontroller-based mobile robot positioning and obstacle avoidance. JESIT 1(1), 58–71 (2014). doi:10.1016/j.jesit.2014.03.009
Lorente, M.T., Villarroel, J.L., Montano, L., et al.: Seamless robot localization and navigation in indoors-outdoors for logistics in warehouses (2015)
Akupati, C.R.: Intelligent outdoor navigation of a mobile robot platform using a low cost high precision RTK-GPS and obstacle avoidance system (2015)
Endres, F., Hess, J., Sturm, J., et al.: Real-time 3D visual SLAM with a hand-held RGB-D camera (2011)
Chang, H.Y., Sarkar, S., Chen, M.N., et al.: An integrated system for 3D pose estimation in cluttered environments. In: 29th Conference on Neural Information Processing Systems (2016)
Zhang, J., Tai, L., Boedecker, J., et al.: Neural SLAM. In: 1st Conference on Robot Learning (2016)
Lee, S., Choi, O., Horaud, R., et al.: An overview of depth cameras and range scanners based on time-of-flight technologies. MVA 27(7), 1005–1020 (2016)
Acknowledgement
This work was supported by the Small Grant Scheme – Sunway Lancaster (Grant No: SGSSL-FST-DCIS-0115-08) at Sunway University, Malaysia.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Tan, W.C., Yap, K.M. (2017). Exploratory Research on Application of Different Vision System on Warehouse Robot Using Selective Algorithm. In: Badioze Zaman, H., et al. Advances in Visual Informatics. IVIC 2017. Lecture Notes in Computer Science(), vol 10645. Springer, Cham. https://doi.org/10.1007/978-3-319-70010-6_27
Download citation
DOI: https://doi.org/10.1007/978-3-319-70010-6_27
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-70009-0
Online ISBN: 978-3-319-70010-6
eBook Packages: Computer ScienceComputer Science (R0)