IEEE Robotics & Automation Magazine - December 2022 - 49

[88] F. Rezazadegan, S. Shirazi, B. Upcrofit, and M. Milford, " Action recognition:
From static datasets to moving robots, " in Proc. Int. Conf. Robot. Autom.
(ICRA), 2017, pp. 3185-3191, doi: 10.1109/ICRA.2017.7989361.
[89] P. Philipp, M. Bommersheim, S. Robert, and J. Beyerer, " Probabilistic
estimation of human interaction needs in context of a robotic assistance in
geriatrics, " Current Directions Biomed. Eng., vol. 5, no. 1, pp. 433-435, 2019,
doi: 10.1515/cdbme-2019-0109.
[90] D. Beßler, R. Porzel, P. Mihai, M. Beetz, R. Malaka, and J. Bateman, " A
formal model of affordances for flexible robotic task execution, " in Proc.
24th Eur. Conf. Artif. Intell. (ECAI), 2020, pp. 2425-2432, doi: 10.3233/
FAIA200374.
[91] I. Goodfellow et al., " Generative adversarial nets, " in Proc. Adv. Neural
Inf. Process. Syst., Curran Associates, 2014, vol. 27, pp. 1-9. [Online]. Available:
https://proceedings.neurips.cc/paper/2014/file/5ca3e9b122f61f8f06494c
97b1afccf3-Paper.pdf
[92] L. Alzubaidi et al., " Review of deep learning: Concepts, CNN architectures,
challenges, applications, future directions, " J. Big Data, vol. 8, no. 1, p.
53, 2021, doi: 10.1186/s40537-021-00444-8.
[93] W. S. McCulloch and W. Pitts, " A logical calculus of the ideas immanent
in nervous activity, " Bull. Math. Biophysics, vol. 5, no. 4, pp. 115-133, 1943,
doi: 10.1007/BF02478259.
[94] D. Purves, G. Augustine, D. Fitzpatrick, W. Hall, A. Lamantia, and L.
White, Neuroscience, 5th ed. Sunderland: Sinauer, 2011.
[95] L. Jiao and J. Zhao, " A survey on the new generation of deep learning in
image processing, " IEEE Access, vol. 7, pp. 172,231-172,263, Nov. 2019, doi:
10.1109/ACCESS.2019.2956508.
[96] K. O'Shea and R. Nash, " An introduction to convolutional neural networks, "
2015, arXiv:1511.08458.
[97] M. Everingham, L. Gool, C. K. I. Williams, J. Winn, and A. Zisserman,
" The PASCAL visual object classes (VOC) challenge, " Int. J. Comput. Vis., vol.
88, no. 2, pp. 303-338, 2009, doi: 10.1007/s11263-009-0275-4.
[98] O. Russakovsky et al., " ImageNet large scale visual recognition challenge, "
Int. J. Comput. Vis., vol. 115, no. 3, pp. 211-252, 2015, doi: 10.1007/
s11263-015-0816-y.
[99] T.-Y. Lin et al., " Microsoft COCO: Common objects in context, " in Proc.
Computer Vision - ECCV, Cham, Switzerland: Springer International Publishing,
2014, pp. 740-755, doi: 10.1007/978-3-319-10602-1_48.
[100] J. Mccormac, R. Clark, M. Bloesch, A. Davison, and S. Leutenegger,
" Fusion++: Volumetric object-level SLAM, " in Proc. 2018 Int. Conf. 3D Vis.
(3DV), pp. 32-41, doi: 10.1109/3DV.2018.00015.
[101] Y. Lin, J. Tremblay, S. Tyree, P. Vela, and S. Birchfield, " Multi-view
fusion for multi-level robotic scene understanding, " in Proc. IEEE/RSJ Int.
Conf. Intell. Robots Syst. (IROS), 2021, pp. 6817-6824, doi: 10.1109/
IROS51168.2021.9635994.
[102] A. Koubaa, Robot Operating System (ROS): The Complete Reference, vol.
1, 1st ed. Cham, Switzerland: Springer Publishing Company, 2016.
[103] J. Suchan and M. Bhatt, " Commonsense scene semantics for cognitive
robotics: Towards grounding embodied visuo-locomotive interactions, " in
Proc. IEEE Int. Conf. Comput. Vis. Workshops (ICCVW), 2017, pp. 742-750,
doi: 10.1109/ICCVW.2017.93.
[104] R. F. Salas-Moreno, R. A. Newcombe, H. Strasdat, P. H. J. Kelly, and A. J.
Davison, " SLAM++: Simultaneous localisation and mapping at the level of
objects, " in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2013, pp. 1352-
1359, doi: 10.1109/CVPR.2013.178.
[105] A. Rosinol, M. Abate, Y. Chang, and L. Carlone, " Kimera: An opensource
library for real-time metric-semantic localization and mapping, " in
Proc. IEEE Int. Conf. Robot. Autom. (ICRA), 2020, pp. 1689-1696, doi:
10.1109/ICRA40945.2020.9196885.
[106] A. Rosinol, A. Gupta, M. Abate, J. Shi, and L. Carlone, " 3D dynamic
scene graphs: Actionable spatial perception with places, objects, and
humans, " 2020, arXiv:2002.06289.
[107] R. Szeliski, Computer Vision: Algorithms and Applications, 1st ed. Berlin,
Heidelberg: Springer-Verlag, 2010.
[108] E. J. Gibson, " Perceptual learning, " Annu. Rev. Psychol., vol. 14, no. 1,
pp. 29-56, 1963, doi: 10.1146/annurev.ps.14.020163.000333.
[109] A. Farahani, S. Voghoei, K. Rasheed, and H. R. Arabnia, " A brief review
of domain adaptation, " in Advances in Data Science and Information Engineering,
R. Stahlbock, G. M. Weiss, M. Abou-Nasr, C. Y. Yang, H. R. Arabnia,
and L. Deligiannidis, Eds. Cham, Switzerland: Springer International Publishing,
2021, pp. 877-894.
[110] H. Qin and D. Zhang, " A perpetual learning algorithm that incrementally
improves performance with deliberation, " IEEE Access, vol. 8, pp.
131,425-131,438, Jul. 2020, doi: 10.1109/ACCESS.2020.3009718.
[111] S. Thrun and T. M. Mitchell, " Lifelong robot learning, " Robot.
Auton. Syst., vol. 15, nos. 1-2, pp. 25-46, 1995, doi: 10.1016/0921
-8890(95)00004-Y.
[112] B. D. Argall, S. Chernova, M. Veloso, and B. Browning, " A survey of
robot learning from demonstration, " Robot. Auton. Syst., vol. 57, no. 5, pp.
469-483, 2009, doi: 10.1016/j.robot.2008.10.024.
[113] C.-C. Carbon, " Understanding human perception by human-made
illusions, " Front. Hum. Neurosci., vol. 8, p. 566, Jul. 2014, doi: 10.3389/
fnhum.2014.00566.
[114] S. Dörr, Cloud-based Cooperative Long-term SLAM for Mobile Robots in
Industrial Applications (ser. Stuttgarter Beiträge zur Produktionsforschung).
Stuttgart, Germany: Fraunhofer Verlag, 2020.
[115] B. Kehoe, S. Patil, P. Abbeel, and K. Goldberg, " A survey of research on
cloud robotics and automation, " IEEE Trans. Autom. Sci. Eng. (from
July 2004), vol. 12, no. 2, pp. 398-409, Apr. 2015, doi: 10.1109/TASE.
2014.2376492.
[116] A. Miller, K. Rim, P. Chopra, P. Kelkar, and M. Likhachev, " Cooperative
perception and localization for cooperative driving, " in Proc. IEEE Int. Conf.
Robot. Autom. (ICRA), 2020, pp. 1256-1262, doi: 10.1109/
ICRA40945.2020.9197463.
Florenz Graf, Department of Robot and Assistive Systems,
Fraunhofer IPA, Stuttgart 70569, Germany. E-mail: florenz.
graf@ipa.fraunhofer.de.
Jochen Lindermayr, Department of Robot and Assistive Systems,
Fraunhofer IPA, Stuttgart 70569, Germany. E-mail:
jochen.lindermayr@ipa.fraunhofer.de.
Çağatay Odabaşi, Department of Robot and Assistive Systems,
Fraunhofer IPA, Stuttgart 70569, Germany. E-mail: cagatay.
odabasi@ipa.fraunhofer.de.
Marco F. Huber, Center for Cyber Cognitive Intelligence,
Fraunhofer IPA, and Institute of Industrial Manufacturing
and Management IFF, University of Stuttgart, Stuttgart 70569,
Germany. E-mail: marco.huber@ieee.org.
DECEMBER 2022 * IEEE ROBOTICS & AUTOMATION MAGAZINE *
49
https://proceedings.neurips.cc/paper/2014/file/5ca3e9b122f61f8f06494c97b1afccf3-Paper.pdf https://proceedings.neurips.cc/paper/2014/file/5ca3e9b122f61f8f06494c97b1afccf3-Paper.pdf
IEEE Robotics & Automation Magazine - December 2022

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