IEEE Robotics & Automation Magazine - December 2023 - 87

Jelena Vuletic, Laboratory for Robotics and Intelligent
Control Systems, Faculty of Electrical and Computer Engineering,
University of Zagreb, 10000 Zagreb, Croatia. E-mail: jelena.
vuletic@fer.hr.
Matko Orsag, Laboratory for Robotics and Intelligent
Control Systems, Faculty of Electrical and Computer
Engineering, University of Zagreb, 10000 Zagreb, Croatia.
E-mail: matko.orsag@fer.hr.
REFERENCES
[1] J. C. Loudon, An Encyclopædia of Gardening. London, U.K.: Longman, Rees,
Orme, Brown and Green, 1826.
[2] I. Charania and X. Li, " Smart farming: Agriculture's shift from a labor intensive
to technology native industry, " Internet Things, vol. 9, Mar. 2020, Art. no.
100142, doi: 10.1016/j.iot.2019.100142.
[3] C. W. Bac, E. J. van Henten, J. Hemming, and Y. Edan, " Harvesting robots for
high-value crops: State-of-the-art review and challenges ahead, " J. Field Robot.,
vol. 31, no. 6, pp. 888-911, Nov./Dec. 2014, doi: 10.1002/rob.21525.
[4] C. Lehnert, I. Sa, C. McCool, B. Upcroft, and T. Perez, " Sweet pepper pose
detection and grasping for automated crop harvesting, " in Proc. IEEE Int. Conf.
Robot. Autom. (ICRA), 2016, pp. 2428-2434, doi: 10.1109/ICRA.2016.7487394.
[5] M. Polic, M. Car, F. Petric, and M. Orsag, " Compliant plant exploration for
agricultural procedures with a collaborative robot, " IEEE Robot. Autom. Lett.,
vol. 6, no. 2, pp. 2768-2774, Apr. 2021, doi: 10.1109/LRA.2021.3062301.
[6] J. Vuletic´, M. Polic´, and M. Orsag, " Robotic strawberry flower treatment based on
deep-learning vision, " in Proc. Int. Workshop Human-Friendly Robot., Cham,
Switzerland: Springer-Verlag, 2023, pp. 189-204, doi: 10.1007/978-3-031-22731-8_14.
[7] M. Polic, M. Car, J. Tabak, and M. Orsag, " Robotic irrigation water management:
Estimating soil moisture content by feel and appearance, " in Proc. 19th Int.
Conf. Ubiquitous Robots (UR), 2022, pp. 16-22, doi: 10.1109/UR55393.
2022.9826252.
[8] M. Polic, J. Tabak, and M. Orsag, " Pepper to fall: A perception method
for sweet pepper robotic harvesting, " Intell. Service Robot., vol. 15, no. 2,
pp. 193-201, 2022, doi: 10.1007/s11370-021-00401-7.
[9] J. Vuletic´, M. Polic´, and M. Orsag, " Procedural generation of synthetic dataset
for robotic applications in sweet pepper cultivation, " in Proc. Int. Conf. Smart
Syst. Technol. (SST), 2022, pp. 309-314, doi: 10.1109/SST55530.2022.9954643.
[10] D. Ball et al., " Farm workers of the future: Vision-based robotics for broadacre
agriculture, " IEEE Robot. Autom. Mag., vol. 24, no. 3, pp. 97-107, Sep. 2017,
doi: 10.1109/MRA.2016.2616541.
[11] A. Pretto et al., " Building an aerial-ground robotics system for precision
farming: An adaptable solution, " IEEE Robot. Autom. Mag., vol. 28, no. 3,
pp. 29-49, Sep. 2021, doi: 10.1109/MRA.2020.3012492.
[12] S. Patnaik, S. Sen, and M. S. Mahmoud, Smart Village Technology: Concepts
and Developments. New York, NY, USA: Springer-Verlag, 2020.
[13] R. Barth, J. Hemming, and E. J. van Henten, " Design of an eye-in-hand sensing
and servo control framework for harvesting robotics in dense vegetation, " Biosyst.
Eng., vol. 146, pp. 71-84, Jun. 2016, doi: 10.1016/j.biosystemseng.2015.12.001.
[14] C. Lehnert, A. English, C. McCool, A. W. Tow, and T. Perez, " Autonomous
sweet pepper harvesting for protected cropping systems, " IEEE Robot. Autom.
Lett., vol. 2, no. 2, pp. 872-879, Apr. 2017, doi: 10.1109/LRA.2017.2655622.
[15] Y. Xiong, Y. Ge, L. Grimstad, and P. J. From, " An autonomous strawberryharvesting
robot: Design, development, integration, and field evaluation, " J. Field
Robot., vol. 37, no. 2, pp. 202-224, 2020, doi: 10.1002/rob.21889.
[16] S. Abondance, C. B. Teeple, and R. J. Wood, " A dexterous soft robotic hand
for delicate in-hand manipulation, " IEEE Robot. Autom. Lett., vol. 5, no. 4, pp.
5502-5509, Oct. 2020, doi: 10.1109/LRA.2020.3007411.
[17] E. Navas, R. Fernandez, D. Sepulveda, M. Armada, and P. Gonzalez-DeSantos,
" Soft gripper for robotic harvesting in precision agriculture applications, "
in Proc. IEEE Int. Conf. Auton. Robot Syst. Competitions (ICARSC), 2021,
pp. 167-172, doi: 10.1109/ICARSC52212.2021.9429797.
[18] A. Gunderman, J. Collins, A. Myers, R. Threlfall, and Y. Chen, " Tendondriven
soft robotic gripper for blackberry harvesting, " IEEE Robot. Autom. Lett.,
vol. 7, no. 2, pp. 2652-2659, Apr. 2022, doi: 10.1109/LRA.2022.3143891.
[19] L. Fu, F. Gao, J. Wu, R. Li, M. Karkee, and Q. Zhang, " Application of consumer
RGB-D cameras for fruit detection and localization in field: A critical review, "
Comput. Electron. Agriculture, vol. 177, 2020, Art. no. 105687, doi: 10.1016/j.compag.2020.105687.
[20]
S. Hinterstoisser, O. Pauly, H. Heibel, M. Martina, and M. Bokeloh, " An
annotation saved is an annotation earned: Using fully synthetic training for object
detection, " in Proc. IEEE/CVF Int. Conf. Comput. Vision Workshops, 2019,
pp. 2787-2796, doi: 10.1109/ICCVW.2019.00340.
[21] S. Khan, B. Phan, R. Salay, and K. Czarnecki, " ProcSy: Procedural synthetic
dataset generation towards influence factor studies of semantic segmentation networks, "
in Proc. IEEE/CVF Conf. Comput. Vision Pattern Recognit. (CVPR)
Workshops, 2019, pp. 88-96.
[22] M. Di Cicco, C. Potena, G. Grisetti, and A. Pretto, " Automatic model based dataset
generation for fast and accurate crop and weeds detection, " in Proc. IEEE/RSJ Int. Conf.
Intell. Robots Syst. (IROS), 2017, pp. 5188-5195, doi: 10.1109/IROS.2017.8206408.
[23] J. Olatunji, G. Redding, C. Rowe, and A. East, " Reconstruction of kiwifruit
fruit geometry using a CGAN trained on a synthetic dataset, " Comput. Electron.
Agriculture, vol. 177, 2020, Art. no. 105699, doi: 10.1016/j.compag.2020.105699.
[24] K. Zhang, Q. Wu, and Y. Chen, " Detecting soybean leaf disease from synthetic
image using multi-feature fusion faster R-CNN, " Comput. Electron. Agriculture,
vol. 183, Apr. 2021, Art. no. 106064, doi: 10.1016/j.compag.2021.106064.
[25] R. Barth, J. IJsselmuiden, J. Hemming, and E. J. Van Henten, " Data synthesis
methods for semantic segmentation in agriculture: A capsicum annuum dataset, "
Comput. Electron. Agriculture, vol. 144, pp. 284-296, Jan. 2018, doi: 10.1016/j.
compag.2017.12.001.
[26] C. Doersch and A. Zisserman, " Sim2real transfer learning for 3D human
pose estimation: Motion to the rescue, " in Proc. Adv. Neural Inf. Process. Syst., H.
Wallach, H. Larochelle, A. Beygelzimer, F. d'Alché-Buc, E. Fox, and R. Garnett,
Eds. Red Hook, NY, USA: Curran Associates, 2019, vol. 32, pp. 1-13.
[27] A. Pashevich, R. Strudel, I. Kalevatykh, I. Laptev, and C. Schmid,
" Learning to augment synthetic images for sim2real policy transfer, " in Proc.
IEEE/RSJ Int. Conf. Intell. Robots Syst. (IROS), 2019, pp. 2651-2657, doi:
10.1109/IROS40897.2019.8967622.
[28] T. Kiyokawa, K. Tomochika, J. Takamatsu, and T. Ogasawara, " Fully automated
annotation with noise-masked visual markers for deep-learning-based
object detection, " IEEE Robot. Autom. Lett., vol. 4, no. 2, pp. 1972-1977, Apr.
2019, doi: 10.1109/LRA.2019.2899153.
[29] V. Ilin, I. Kalinov, P. A. Karpyshev, and D. Tsetserukou, " DeepScanner: A
robotic system for automated 2D object dataset collection with annotations, " in
Proc. 26th IEEE Int. Conf. Emerg. Technol. Factory Autom. (ETFA), 2021,
pp. 1-8, doi: 10.1109/ETFA45728.2021.9613396.
[30] M. Otte, M. Kuhlman, and D. Sofge, " Multi-robot task allocation with auctions
in harsh communication environments, " in Proc. Int. Symp. Multi-Robot
Multi-Agent Syst. (MRS), 2017, pp. 32-39, doi: 10.1109/MRS.2017.8250928.
[31] H. Mitiche, D. Boughaci, and M. Gini, " Iterated local search for time-extended
multi-robot task allocation with spatio-temporal and capacity constraints, "
J. Intell. Syst., vol. 28, no. 2, pp. 347-360, 2019, doi: 10.1515/jisys-2018-0267.
[32] G. A. Korsah, " Exploring bounded optimal coordination for heterogeneous
teams with cross-schedule dependencies, " M.S. thesis, Carnegie Mellon Univ.,
Pittsburgh, PA, USA, Jan. 2011.
[33] J. G. Martin, J. R. D. Frejo, R. A. García, and E. F. Camacho, " Multi-robot
task allocation problem with multiple nonlinear criteria using branch and bound
and genetic algorithms, " Intell. Service Robot., vol. 14, no. 5, pp. 707-727, 2021,
doi: 10.1007/s11370-021-00393-4.
[34] W. Hess, D. Kohler, H. Rapp, and D. Andor, " Real-time loop closure in 2D
LIDAR SLAM, " in Proc. IEEE Int. Conf. Robot. Autom. (ICRA), 2016, pp. 1271-
1278, doi: 10.1109/ICRA.2016.7487258.
[35] M. Kokot, D. Miklic´, and T. Petrovic´, " Path continuity for multi-wheeled
AGVs, " IEEE Robot. Autom. Lett., vol. 6, no. 4, pp. 7437-7444, Oct. 2021, doi:
10.1109/LRA.2021.3099086.
[36] M. Polic, I. Krajacic, N. Lepora, and M. Orsag, " Convolutional autoencoder
for feature extraction in tactile sensing, " IEEE Robot. Autom. Lett., vol. 4, no. 4,
pp. 3671-3678, Oct. 2019, doi: 10.1109/LRA.2019.2927950.
[37] D. Stuhne, J. Tabak, M. Polic´, and M. Orsag, " Design and prototyping of soft
finger AI-enabled hand (SofIA), " in Proc. IEEE/ASME Int. Conf. Adv. Intell.
Mechatronics (AIM), 2022, pp. 1581-1586, doi: 10.1109/AIM52237.2022.9863338.
[38] J. Vuletic´, M. Car, and M. Orsag, " Close-range multispectral imaging with
Multispectral-Depth (MS-D) system, " Biosyst. Eng., vol. 231, pp. 178-194, Jul.
2023, doi: 10.1016/j.biosystemseng.2023.06.002.
[39] A. Ivanovic, M. Polic, J. Tabak, and M. Orsag, " Render-in-the-loop aerial
robotics simulator: Case study on yield estimation in indoor agriculture, " in Proc.
Int. Conf. Unmanned Aircraft Syst. (ICUAS), 2022, pp. 787-793, doi: 10.1109/
ICUAS54217.2022.9836121.
[40] G. A. Korsah, A. Stentz, and M. B. Dias, " A comprehensive taxonomy for
multi-robot task allocation, " Int. J. Robot. Res., vol. 32, no. 12, pp. 1495-1512,
2013, doi: 10.1177/0278364913496484.
[41] D. Meignan, A. Koukam, and J.-C. Créput, " Coalition-based metaheuristic: A
self-adaptive metaheuristic using reinforcement learning and mimetism, " J.
Heuristics, vol. 16, no. 6, pp. 859-879, Dec. 2010, doi: 10.1007/s10732-009-9121-7.
[42] B. A. Ferreira, T. Petrovic´, M. Orsag, J. R. M. de Dios, and S. Bogdan,
" Distributed allocation and scheduling of tasks with cross-schedule dependencies
for heterogeneous multi-robot teams, " 2021. [Online]. Available: https://arxiv.org/
abs/2109.03089
DECEMBER 2023 IEEE ROBOTICS & AUTOMATION MAGAZINE
87
https://www.arxiv.org/abs/2109.03089 https://www.arxiv.org/abs/2109.03089
IEEE Robotics & Automation Magazine - December 2023

Table of Contents for the Digital Edition of IEEE Robotics & Automation Magazine - December 2023
