A Mobile Robot Visual Perception System based on Deep Learning Approach
Апстракт
In this paper, we present the novel mobile robot
perception system based on a deep learning framework. The
hardware subsystem consists of an Nvidia Jetson Nano
development board integrated with two parallelly positioned
Basler daA1600-60uc cameras, while the software subsystem is
based on the convolutional neural networks utilized for semantic
segmentation of the environment scene. A Fully Convolutional
neural Network (FCN) based on the ResNet18 backbone
architecture is utilized to provide accurate information about
machine tool models and background position in the image. FCN
model is trained on our custom-developed dataset of a laboratory
model of manufacturing environment and implemented on
mobile robot RAICO (Robot with Artificial Intelligence based
COgnition).
Кључне речи:
Deep learning / Perception System / Mobile robot / Semantic SegmentationИзвор:
Зборник радова ‐ 65. Конференција за електронику, телекомуникације, рачунарство, аутоматику и нуклеарну технику, Етно село Станишићи, 08‐10.09.2021. године / Proceedings of Papers – 8th International Conference on Electrical, Electronic and Computing Engineering, IcETRAN 2021, Ethno willage Stanišići, Republic of Srpska, Bosnia and Herzegovina, 2021, 2021, 568-572Издавач:
- Belgrade : Društvo za ETRAN
- Beograd : Akademska misao
Финансирање / пројекти:
- Министарство науке, технолошког развоја и иновација Републике Србије, институционално финансирање - 200105 (Универзитет у Београду, Машински факултет) (RS-MESTD-inst-2020-200105)
- MISSION4.0 - Deep Machine Learning and Swarm Intelligence-Based Optimization Algorithms for Control and Scheduling of Cyber-Physical Systems in Industry 4.0 (RS-ScienceFundRS-AI-6523109)
Колекције
Институција/група
Mašinski fakultetTY - CONF AU - Jokić, Aleksandar AU - Đokić, Lazar AU - Petrović, Milica AU - Miljković, Zoran PY - 2021 UR - https://machinery.mas.bg.ac.rs/handle/123456789/4233 AB - In this paper, we present the novel mobile robot perception system based on a deep learning framework. The hardware subsystem consists of an Nvidia Jetson Nano development board integrated with two parallelly positioned Basler daA1600-60uc cameras, while the software subsystem is based on the convolutional neural networks utilized for semantic segmentation of the environment scene. A Fully Convolutional neural Network (FCN) based on the ResNet18 backbone architecture is utilized to provide accurate information about machine tool models and background position in the image. FCN model is trained on our custom-developed dataset of a laboratory model of manufacturing environment and implemented on mobile robot RAICO (Robot with Artificial Intelligence based COgnition). PB - Belgrade : Društvo za ETRAN PB - Beograd : Akademska misao C3 - Зборник радова ‐ 65. Конференција за електронику, телекомуникације, рачунарство, аутоматику и нуклеарну технику, Етно село Станишићи, 08‐10.09.2021. године / Proceedings of Papers – 8th International Conference on Electrical, Electronic and Computing Engineering, IcETRAN 2021, Ethno willage Stanišići, Republic of Srpska, Bosnia and Herzegovina, 2021 T1 - A Mobile Robot Visual Perception System based on Deep Learning Approach EP - 572 SP - 568 UR - https://hdl.handle.net/21.15107/rcub_machinery_4233 ER -
@conference{ author = "Jokić, Aleksandar and Đokić, Lazar and Petrović, Milica and Miljković, Zoran", year = "2021", abstract = "In this paper, we present the novel mobile robot perception system based on a deep learning framework. The hardware subsystem consists of an Nvidia Jetson Nano development board integrated with two parallelly positioned Basler daA1600-60uc cameras, while the software subsystem is based on the convolutional neural networks utilized for semantic segmentation of the environment scene. A Fully Convolutional neural Network (FCN) based on the ResNet18 backbone architecture is utilized to provide accurate information about machine tool models and background position in the image. FCN model is trained on our custom-developed dataset of a laboratory model of manufacturing environment and implemented on mobile robot RAICO (Robot with Artificial Intelligence based COgnition).", publisher = "Belgrade : Društvo za ETRAN, Beograd : Akademska misao", journal = "Зборник радова ‐ 65. Конференција за електронику, телекомуникације, рачунарство, аутоматику и нуклеарну технику, Етно село Станишићи, 08‐10.09.2021. године / Proceedings of Papers – 8th International Conference on Electrical, Electronic and Computing Engineering, IcETRAN 2021, Ethno willage Stanišići, Republic of Srpska, Bosnia and Herzegovina, 2021", title = "A Mobile Robot Visual Perception System based on Deep Learning Approach", pages = "572-568", url = "https://hdl.handle.net/21.15107/rcub_machinery_4233" }
Jokić, A., Đokić, L., Petrović, M.,& Miljković, Z.. (2021). A Mobile Robot Visual Perception System based on Deep Learning Approach. in Зборник радова ‐ 65. Конференција за електронику, телекомуникације, рачунарство, аутоматику и нуклеарну технику, Етно село Станишићи, 08‐10.09.2021. године / Proceedings of Papers – 8th International Conference on Electrical, Electronic and Computing Engineering, IcETRAN 2021, Ethno willage Stanišići, Republic of Srpska, Bosnia and Herzegovina, 2021 Belgrade : Društvo za ETRAN., 568-572. https://hdl.handle.net/21.15107/rcub_machinery_4233
Jokić A, Đokić L, Petrović M, Miljković Z. A Mobile Robot Visual Perception System based on Deep Learning Approach. in Зборник радова ‐ 65. Конференција за електронику, телекомуникације, рачунарство, аутоматику и нуклеарну технику, Етно село Станишићи, 08‐10.09.2021. године / Proceedings of Papers – 8th International Conference on Electrical, Electronic and Computing Engineering, IcETRAN 2021, Ethno willage Stanišići, Republic of Srpska, Bosnia and Herzegovina, 2021. 2021;:568-572. https://hdl.handle.net/21.15107/rcub_machinery_4233 .
Jokić, Aleksandar, Đokić, Lazar, Petrović, Milica, Miljković, Zoran, "A Mobile Robot Visual Perception System based on Deep Learning Approach" in Зборник радова ‐ 65. Конференција за електронику, телекомуникације, рачунарство, аутоматику и нуклеарну технику, Етно село Станишићи, 08‐10.09.2021. године / Proceedings of Papers – 8th International Conference on Electrical, Electronic and Computing Engineering, IcETRAN 2021, Ethno willage Stanišići, Republic of Srpska, Bosnia and Herzegovina, 2021 (2021):568-572, https://hdl.handle.net/21.15107/rcub_machinery_4233 .