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Pregled bibliografske jedinice broj: 1079602

Deep Semantic Image Segmentation for UAV-UGV Cooperative Path Planning: A Car Park Use Case


Kundid Vasić, Mirela; Drak, Ahmad; Bugarin, Nediljko; Kružić, Stanko; Musić, Josip; Pomrehn, Christoph; Schöbel, Maximilian; Johenneken, Maximilian; Stančić, Ivo; Papić, Vladan; Herpers, Rainer
Deep Semantic Image Segmentation for UAV-UGV Cooperative Path Planning: A Car Park Use Case // The 28th International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2020)
Split, 2020. 28, 6 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


CROSBI ID: 1079602 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Deep Semantic Image Segmentation for UAV-UGV Cooperative Path Planning: A Car Park Use Case

Autori
Kundid Vasić, Mirela ; Drak, Ahmad ; Bugarin, Nediljko ; Kružić, Stanko ; Musić, Josip ; Pomrehn, Christoph ; Schöbel, Maximilian ; Johenneken, Maximilian ; Stančić, Ivo ; Papić, Vladan ; Herpers, Rainer

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
The 28th International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2020) / - Split, 2020

Skup
The 28th International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2020)

Mjesto i datum
Split, Hrvatska, 17-19.09.2020

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
cooperative path planning, semantic image segmentation, neural networks, unmanned ground vehicle, unmanned aerial vehicle

Sažetak
Navigation of Unmanned Ground Vehicles (UGV) in unknown environments is an active area of research for mobile robotics. A main hindering factor for UGV navigation is the limited range of the on-board sensors that process only restricted areas of the environment at a time. In addition, most existing approaches process sensor information under the assumption of a static environment. This restrains the exploration capability of the UGV especially in time-critical applications such as search and rescue. The cooperation with an Unmanned Aerial Vehicle (UAV) can provide the UGV with an extended perspective of the environment which enables a better-suited path planning solution that can be adjusted on demand. In this work, we propose a UAV-UGV cooperative path planning approach for dynamic environments by performing semantic segmentation on images acquired from the UAV's view via a deep neural network. The approach is evaluated in a car park scenario, with the goal of providing a path plan to an empty parking space for a ground- based vehicle. The experiments were performed on a created dataset of real-world car park images located in Croatia and Germany, in addition to images from a simulated environment. The segmentation results demonstrate the viability of the proposed approach in producing maps of the dynamic environment on demand and accordingly generating path plans for ground-based vehicles.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo



POVEZANOST RADA


Ustanove:
Fakultet elektrotehnike, strojarstva i brodogradnje, Split

Profili:

Avatar Url Ivo Stančić (autor)

Avatar Url Stanko Kružić (autor)

Avatar Url Vladan Papić (autor)

Avatar Url Josip Musić (autor)

Avatar Url Nediljko Bugarin (autor)


Citiraj ovu publikaciju:

Kundid Vasić, Mirela; Drak, Ahmad; Bugarin, Nediljko; Kružić, Stanko; Musić, Josip; Pomrehn, Christoph; Schöbel, Maximilian; Johenneken, Maximilian; Stančić, Ivo; Papić, Vladan; Herpers, Rainer
Deep Semantic Image Segmentation for UAV-UGV Cooperative Path Planning: A Car Park Use Case // The 28th International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2020)
Split, 2020. 28, 6 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Kundid Vasić, M., Drak, A., Bugarin, N., Kružić, S., Musić, J., Pomrehn, C., Schöbel, M., Johenneken, M., Stančić, I., Papić, V. & Herpers, R. (2020) Deep Semantic Image Segmentation for UAV-UGV Cooperative Path Planning: A Car Park Use Case. U: The 28th International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2020).
@article{article, year = {2020}, pages = {6}, chapter = {28}, keywords = {cooperative path planning, semantic image segmentation, neural networks, unmanned ground vehicle, unmanned aerial vehicle}, title = {Deep Semantic Image Segmentation for UAV-UGV Cooperative Path Planning: A Car Park Use Case}, keyword = {cooperative path planning, semantic image segmentation, neural networks, unmanned ground vehicle, unmanned aerial vehicle}, publisherplace = {Split, Hrvatska}, chapternumber = {28} }
@article{article, year = {2020}, pages = {6}, chapter = {28}, keywords = {cooperative path planning, semantic image segmentation, neural networks, unmanned ground vehicle, unmanned aerial vehicle}, title = {Deep Semantic Image Segmentation for UAV-UGV Cooperative Path Planning: A Car Park Use Case}, keyword = {cooperative path planning, semantic image segmentation, neural networks, unmanned ground vehicle, unmanned aerial vehicle}, publisherplace = {Split, Hrvatska}, chapternumber = {28} }




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