Items where Author is "Portugal, D"

Journal article

CARVALHO, A.E., FERREIRA, J.F. and PORTUGAL, D., 2024. 3D traversability analysis and path planning based on mechanical effort for UGVs in forest environments. Robotics and Autonomous Systems: 104560. ISSN 0921-8890

FERREIRA, J.F., PORTUGAL, D., ANDRADA, M.E., MACHADO, P., ROCHA, R.P. and PEIXOTO, P., 2023. Sensing and artificial perception for robots in precision forestry: a survey. Robotics, 12 (5): 139. ISSN 2218-6581

CRISTÓVÃO, M.P., PORTUGAL, D., CARVALHO, A.E. and FERREIRA, J.F., 2023. A LiDAR-Camera-Inertial-GNSS apparatus for 3D multimodal dataset collection in woodland scenarios. Sensors, 23 (15): 6676. ISSN 1424-8220

Chapter in book

CARVALHO, A.E., FERREIRA, J.F. and PORTUGAL, D., 2023. 3D traversability analysis in forest environments based on mechanical effort. In: I. PETROVIC, E. MENEGATTI and I. MARKOVIĆ, eds., Intelligent Autonomous Systems 17: proceedings of the 17th International Conference IAS-17. Lecture Notes in Networks and Systems (577). Cham: Springer. ISBN 9783031222153

ANDRADA, M.E., FERREIRA, J.F., PORTUGAL, D. and COUCEIRO, M.S., 2022. Integration of an artificial perception system for identification of live flammable material in forestry robotics. In: Proceedings of the 2022 IEEE/SICE International Symposium on System Integration (SII). Institute of Electrical and Electronics Engineers (IEEE), pp. 103-108. ISBN 9781665445399

MACHADO, P., BONNELL, J., BRANDENBURGH, S., FERREIRA, J.F., PORTUGAL, D. and COUCEIRO, M., 2021. Robotics use case scenarios. In: M. JAHRE, D. GÖHRINGER and P. MILLET, eds., Towards ubiquitous low-power image processing platforms. Cham, Switzerland: Springer, pp. 151-172. ISBN 9783030535315 (Forthcoming)

PORTUGAL, D., FERREIRA, J.F. and COUCEIRO, M.S., 2020. Requirements specification and integration architecture for perception in a cooperative team of forestry robots. In: M. RUSSO, X. DONG and A. MOHAMMAD, eds., Towards Autonomous Robotic Systems: 21st Annual Conference, TAROS 2020, Nottingham, UK, September 16, 2020, Proceedings. Lecture notes in computer science (12228). Cham: Springer, pp. 329-344. ISBN 9783030634858

MARTINS, G.S., FERREIRA, J.F., PORTUGAL, D. and COUCEIRO, M.S., 2019. MoDSeM: towards semantic mapping with distributed robots. In: K. ALTHOEFER, J. KONSTANTINOVA and K. ZHANG, eds., Towards autonomous robotic systems. Proceedings of the 20th Annual Conference, TAROS 2019, London, 3-5 July 2019. Part II. Lecture notes in computer science (11650). Cham: Springer, pp. 131-142. ISBN 9783030253318

Conference contribution

BITTNER, D., FERREIRA, J.F., ANDRADA, M.E., BIRD, J.J. and PORTUGAL, D., 2022. Generating synthetic multispectral images for semantic segmentation in forestry applications. In: Innovation in Forestry Robotics: Research and Industry Adoption Workshop - IEEE Conference on Robotics and Automation (ICRA 2022), Philadelphia (PA), USA, 23-27 May 2022.

ANDRADA, M.E., FERREIRA, J.F., KANTOR, G., PORTUGAL, D. and ANTUNES, C.H., 2022. Model pruning in depth completion CNNs for forestry robotics with simulated annealing. In: Innovation in Forestry Robotics: Research and Industry Adoption Workshop - IEEE Conference on Robotics and Automation (ICRA 2022), Philadelphia (PA), USA, 23-27 May 2022.

LOURENÇO, D., DE CASTRO CARDOSO FERREIRA, J. and PORTUGAL, D., 2020. 3D local planning for a forestry UGV based on terrain gradient and mechanical effort. In: IROS 2020 Workshop on Perception, Planning and Mobility in Forestry Robotics (WPPMFR 2020), Las Vegas, NV, USA (virtual workshop), 29 October 2020.

ANDRADA, M.E., DE CASTRO CARDOSO FERREIRA, J., PORTUGAL, D. and COUCEIRO, M., 2020. Testing different CNN architectures for semantic segmentation for landscaping with forestry robotics. In: IROS 2020 Workshop on Perception, Planning and Mobility in Forestry Robotics (WPPMFR 2020), Las Vegas, NV, USA (virtual workshop), 29 October 2020.

MARTINS, S., FERREIRA, J.F., PORTUGAL, D. and COUCEIRO, M.S., 2019. MoDSeM: modular framework for distributed semantic mapping. 'Embedded intelligence: enabling & supporting RAS technologies'. In: 2nd UK-RAS Robotics and Autonomous Systems Conference, Loughborough, 2019.

Research datasets and databases

BITTNER, D., ANDRADA, M.E., PORTUGAL, D. and FERREIRA, J.F., 2021. SEMFIRE forest dataset for semantic segmentation and data augmentation. [Dataset]