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Publikationer

Här listas avdelningens 50 senaste publikationer från KTH:s publikationsportal DiVA.

Länk till hela publikationslistan för RPL i DiVA hittas i botten av denna lista.

Publikationer av författare från RPL

[1]
S. Hafner et al., "Sentinel-1 and Sentinel-2 Data Fusion for Urban Change Detection Using a Dual Stream U-Net," IEEE Geoscience and Remote Sensing Letters, vol. 19, 2022.
[2]
F. S. Barbosa, "Towards Safer and Risk-aware Motion Planning and Control for Robotic Systems," Doktorsavhandling : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2021:79, 2022.
[3]
C. Sprague och P. Ögren, "Continuous-Time Behavior Trees as Discontinuous Dynamical Systems," IEEE CONTROL SYSTEMS LETTERS, vol. 6, s. 1891-1896, 2022.
[4]
[5]
H. Song et al., "Herding by caging : a formation-based motion planning framework for guiding mobile agents," Autonomous Robots, vol. 45, no. 5, s. 613-631, 2021.
[6]
M. R. Fraune, N. Karatas och I. Leite, "Workshop YOUR study design! Participatory critique and refinement of participants' studies," i ACM/IEEE International Conference on Human-Robot Interaction, 2021, s. 688-690.
[7]
S. Gillet, "Autonomous robot behaviors for shaping group dynamics," i ACM/IEEE International Conference on Human-Robot Interaction, 2021, s. 601-603.
[8]
C. F. Weldon et al., "Exploring non-verbal gaze behavior in groups mediated by an adaptive robot," i ACM/IEEE International Conference on Human-Robot Interaction, 2021, s. 357-361.
[9]
K. Winkle et al., "Boosting robot credibility and challenging gender norms in responding to abusive behaviour : A case for feminist robots," i ACM/IEEE International Conference on Human-Robot Interaction, 2021, s. 29-37.
[10]
K. Winkle et al., "Assessing and addressing ethical risk from anthropomorphism and deception in socially assistive robots," i ACM/IEEE International Conference on Human-Robot Interaction, 2021, s. 101-109.
[11]
I. Torre et al., "The Effect of Audio-Visual Smiles on Social Influence in a Cooperative Human-Agent Interaction Task," ACM Transactions on Computer-Human Interaction, vol. 28, no. 6, 2021.
[12]
F. S. Barbosa et al., "Risk-Aware Motion Planning in Partially Known Environments," i 2021 60th IEEE Conference on Decision and Control (CDC), 2021.
[13]
K. Winkle, E. Senft och S. Lemaignan, "LEADOR : A Method for End-To-End Participatory Design of Autonomous Social Robots," Frontiers in Robotics and AI, vol. 8, 2021.
[14]
I. Mitsioni et al., "Interpretability in Contact-Rich Manipulation via Kinodynamic Images," i 2021 IEEE International Conference on Robotics and Automation (ICRA), 2021, s. 10175-10181.
[15]
I. Mitsioni, Y. Karayiannidis och D. Kragic, "Modelling and Learning Dynamics for Robotic Food-Cutting," i 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE), 2021, s. 1194-1200.
[16]
M. Pallin, J. Rashid och P. Ögren, "Formulation and Solution of the Multi-agent Concurrent Search and Rescue Problem," i IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2021, 2021, s. 27-33.
[17]
M. Pallin, J. Rashid och P. Ögren, "A Decentralized Asynchronous Collaborative Genetic Algorithm for Heterogeneous Multi-agent Search and Rescue Problems," i IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2021, 2021, s. 1-8.
[18]
P. Tajvar, "Safe data-driven control for robots with constrained motion," Doktorsavhandling : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2021:80, 2021.
[19]
M. Iovino et al., "Learning Behavior Trees with Genetic Programming in Unpredictable Environments," i 2021 IEEE International Conference on Robotics and Automation (ICRA), 2021, s. 459-4597.
[20]
G. F. Schuppe och J. Tumova, "Decentralized Multi-Agent Strategy Synthesis under LTLf Specifications via Exchange of Least-Limiting Advisers," i 2021 International Symposium on Multi-Robot and Multi-Agent Systems (MRS), 2021.
[21]
E. Englesson och H. Azizpour, "Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels," i 35th Conference on Neural Information Processing Systems (NeurIPS 2021)., 2021.
[22]
E. Englesson och H. Azizpour, "Consistency Regularization Can Improve Robustness to Label Noise," i International Conference on Machine Learning (ICML) Workshops, 2021 Workshop on Uncertainty and Robustness in Deep Learning, 2021.
[23]
F. Esposito et al., "Learning Task Constraints in Visual-Action Planning from Demonstrations," i 2021 30Th Ieee International Conference On Robot And Human Interactive Communication (Ro-Man), 2021, s. 131-138.
[24]
W. Yin et al., "Graph-based Normalizing Flow for Human Motion Generation and Reconstruction," i 2021 30th IEEE international conference on robot and human interactive communication (RO-MAN), 2021, s. 641-648.
[25]
S. Manzinger, C. Pek och M. Althoff, "Using Reachable Sets for Trajectory Planning of Automated Vehicles," IEEE Transactions on Intelligent Vehicles, vol. 6, no. 2, s. 232-248, 2021.
[26]
M. Ning et al., "YOLOv4-object : an Efficient Model and Method for Object Discovery," i 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC), 2021, s. 31-36.
[28]
K. Andersson, "Improving Fixed Wing UAV Endurance, by Cooperative Autonomous Soaring," Doktorsavhandling Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2021:65, 2021.
[29]
P. Schillinger et al., "Adaptive heterogeneous multi-robot collaboration from formal task specifications," Robotics and Autonomous Systems, vol. 145, 2021.
[31]
D. Kragic och Y. Sandamirskaya, "Effective and natural human-robot interaction requires multidisciplinary research," SCIENCE ROBOTICS, vol. 6, no. 58, 2021.
[32]
M. C. Welle et al., "Partial caging : a clearance-based definition, datasets, and deep learning," Autonomous Robots, vol. 45, no. 5, s. 647-664, 2021.
[33]
A. Longhini et al., "Textile Taxonomy and Classification Using Pulling and Twisting," i IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) : Prague/Online 27.09-01.10.2021, 2021, s. 7541-7548.
[34]
T. Kucherenko, "Developing and evaluating co-speech gesture-synthesis models for embodied conversational agents," Doktorsavhandling : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2021:75, 2021.
[35]
R. Nagy et al., "A Framework for Integrating Gesture Generation Models into Interactive Conversational Agents," i 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS)., 2021.
[36]
M. C. Welle, "Learning Structured Representations for Rigid and Deformable Object Manipulation," Doktorsavhandling Stockholm, Sweden : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2021:72, 2021.
[37]
A. L. Gert et al., "COORDINATING WITH A ROBOT PARTNER AFFECTS ACTION MONITORING RELATED NEURAL PROCESSING," Psychophysiology, vol. 58, s. S60-S60, 2021.
[38]
M. M. N. Bienkiewicz et al., "Bridging the gap between emotion and joint action," Neuroscience and Biobehavioral Reviews, vol. 131, s. 806-833, 2021.
[39]
C. Chernik, P. Tajvar och J. Tumova, "Robust Feedback Motion Primitives for Exploration of Unknown Terrains," i IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021.
[41]
U. Wennberg och G. E. Henter, "The Case for Translation-Invariant Self-Attention in Transformer-Based Language Models," i ACL-IJCNLP 2021 : THE 59TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS AND THE 11TH INTERNATIONAL JOINT CONFERENCE ON NATURAL LANGUAGE PROCESSING, VOL 2, 2021, s. 130-140.
[42]
C. Ceylan, S. Franzen och F. T. Pokorny, "Learning Node Representations Using Stationary Flow Prediction on Large Payment and Cash Transaction Networks," i International Conference On Machine Learning, Vol 139, 2021.
[43]
I. Torre et al., "Dimensional perception of a ‘smiling McGurkeffect’," i 2021 9th International Conference on Affective Computing and Intelligent Interaction (ACII), 2021.
[44]
I. Torre et al., "Exploring the Effects of Virtual Agents’ Smiles on Human-Agent Interaction : A Mixed-Methods Study," i 2021 9th International Conference on Affective Computing and Intelligent Interaction (ACII), 2021.
[45]
N. Masud, "About Physical Human Robotic Interaction for Assistive Exoskeletons," Doktorsavhandling Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2021:58, 2021.
[46]
H. Eivazi et al., "Recurrent neural networks and Koopman-based frameworks for temporal predictions in a low-order model of turbulence," International Journal of Heat and Fluid Flow, vol. 90, 2021.
[47]
T. Kucherenko et al., "Speech2Properties2Gestures : Gesture-Property Prediction as a Tool for Generating Representational Gestures from Speech," i IVA '21 : Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents, 2021, s. 145-147.
[48]
S. van Waveren et al., "Exploring Non-Expert Robot Programming Through Crowdsourcing," Frontiers in Robotics and AI, vol. 8, 2021.
[49]
K. Grover et al., "Semantic Abstraction-Guided Motion Planning for scLTL Missions in Unknown Environments," i ROBOTICS : SCIENCE AND SYSTEM XVII, 2021.
[50]
A. Guemes et al., "From coarse wall measurements to turbulent velocity fields through deep learning," Physics of fluids, vol. 33, no. 7, 2021.
Fullständig lista i KTH:s publikationsportal