Publications
Below are the divisions's 50 latest publications according to the KTH library database DiVA.
Link to the full list for RPL in KTH's publication portal can be found at the bottom of this list. Researchers also maintain individual publication lists, see People in the menu on the main page.
Publikationer av författare från RPL
[1]
H. Lameris et al.,
"Prosody-Controllable Spontaneous TTS with Neural HMMs,"
in International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023.
[2]
Y. Xie, N. Bore and J. Folkesson,
"Neural Network Normal Estimation and Bathymetry Reconstruction From Sidescan Sonar,"
IEEE Journal of Oceanic Engineering, vol. 48, no. 1, pp. 218-232, 2023.
[3]
M. Iovino,
"Learning Behavior Trees for Collaborative Robotics,"
Doctoral thesis Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2023:46, 2023.
[4]
F. Baldassarre,
"Structured Representations for Explainable Deep Learning,"
Doctoral thesis Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2023:49, 2023.
[5]
F. Baldassarre, A. El-Nouby and H. Jégou,
"Variable Rate Allocation for Vector-Quantized Autoencoders,"
in ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023.
[6]
L. Guastoni et al.,
"Deep reinforcement learning for turbulent drag reduction in channel flows,"
The European Physical Journal E Soft matter, vol. 46, no. 4, 2023.
[7]
M. Lippi et al.,
"Enabling Visual Action Planning for Object Manipulation Through Latent Space Roadmap,"
IEEE Transactions on robotics, vol. 39, no. 1, pp. 57-75, 2023.
[8]
H. Hu, F. Baldassarre and H. Azizpour,
"Learnable Masked Tokens for Improved Transferability of Self-supervised Vision Transformers,"
in Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part III, 2023, pp. 409-426.
[9]
A. A. Medbouhi et al.,
"InvMap and Witness Simplicial Variational Auto-Encoders,"
MACHINE LEARNING AND KNOWLEDGE EXTRACTION, vol. 5, no. 1, pp. 199-236, 2023.
[10]
T.-M. Nguyen et al.,
"SLICT : Multi-Input Multi-Scale Surfel-Based Lidar-Inertial Continuous-Time Odometry and Mapping,"
IEEE Robotics and Automation Letters, vol. 8, no. 4, pp. 2102-2109, 2023.
[11]
F. J. Lawin et al.,
"Is Markerless More or Less? : Comparing a Smartphone Computer Vision Method for Equine Lameness Assessment to Multi-Camera Motion Capture,"
Animals, vol. 13, no. 3, 2023.
[12]
D. Marta et al.,
"Aligning Human Preferences with Baseline Objectives in Reinforcement Learning,"
in International Conference on Robotics and Automation, 2023.
[13]
M. Vahs, C. Pek and J. Tumova,
"Risk-aware Spatio-temporal Logic Planning in Gaussian Belief Spaces,"
(Manuscript).
[14]
E. Bartoli, F. I. Dogan and I. Leite,
"Contextualized Knowledge Graph Embeddings for Activity Prediction in Service Robotics,"
in Workshop on Semantic Scene Understanding for Human-Robot Interaction, ACM/IEEE International Conference on Human Robot Interaction, 2023.
[15]
F. I. Dogan,
"Robots That Understand Natural Language Instructions and Resolve Ambiguities,"
Doctoral thesis : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2023:16, 2023.
[16]
F. I. Dogan, G. I. Melsión and I. Leite,
"Leveraging Explainability for Understanding Object Descriptions in Ambiguous 3D Environments,"
Frontiers in Robotics and AI, vol. 9, 2023.
[17]
T. Olugbade et al.,
"Human Movement Datasets : An Interdisciplinary Scoping Review,"
ACM Computing Surveys, vol. 55, no. 6, 2023.
[18]
Ö. Özkahraman,
"Multi-Agent Mission Planning and Execution for Small Autonomous Underwater Vehicles,"
Doctoral thesis : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2023:5, 2023.
[19]
R. Tu,
"A Further Step of Causal Discovery towards Real-World Impacts,"
Doctoral thesis Stockholm, Sweden : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2023:6, 2023.
[20]
R. Parasuraman, B.-C. Min and P. Ögren,
"Rapid prediction of network quality in mobile robots,"
Ad hoc networks, vol. 138, 2023.
[21]
A. F. T. Winfield et al.,
"Ethical Risk Assessment for Social Robots : Case Studies in Smart Robot Toys,"
in Intelligent Systems, Control and Automation: Science and Engineering, : Springer Nature, 2022, pp. 61-76.
[22]
X. Zhu, A. Maki and L. Hanson,
"Unsupervised domain adaptive object detection for assembly quality inspection,"
in Proceedings 15th CIRP Conference on Intelligent Computation in Manufacturing Engineering, ICME 2021, 2022, pp. 477-482.
[23]
M. Iovino et al.,
"On the programming effort required to generate Behavior Trees and Finite State Machines for robotic applications,"
(Manuscript).
[24]
F. Baldassarre et al.,
"Quantitative Metrics for Evaluating Explanations of Video DeepFake Detectors,"
in 33rd British Machine Vision Conference (BMVC), 2022.
[25]
F. Baldassarre and H. Azizpour,
"Towards Self-Supervised Learning of Global and Object-Centric Representations,"
in ICLR Workshop on the Elements of Reasoning, Objects, Structure and Causality, 2022.
[26]
P. Poklukar et al.,
"Geometric Multimodal Contrastive Representation Learning,"
in International Conference On Machine Learning, Vol 162, 2022.
[27]
M. Couto et al.,
"Child-robot interaction Design, evaluation, and novel solutions,"
Interaction Studies : Social Behaviour and Communication in Biological and Artificial Systems, vol. 23, no. 2, pp. 151-156, 2022.
[28]
R. Stower et al.,
"Exploring space for robot mistakes in child robot interactions,"
Interaction Studies : Social Behaviour and Communication in Biological and Artificial Systems, vol. 23, no. 2, pp. 243-288, 2022.
[29]
C. I. Sprague and P. Ögren,
"Adding Neural Network Controllers to Behavior Trees without Destroying Performance Guarantees,"
in 2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC), 2022, pp. 3989-3996.
[30]
A. Khoche et al.,
"Semantic 3D Grid Maps for Autonomous Driving,"
in 2022 IEEE 25TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2022, pp. 2681-2688.
[31]
J. R. Baldvinsson et al.,
"IL-GAN : Rare Sample Generation via Incremental Learning in GANs,"
in 2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022), 2022, pp. 621-626.
[32]
M. Vasco et al.,
"How to Sense the World : Leveraging Hierarchy in Multimodal Perception for Robust Reinforcement Learning Agents,"
in Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, 2022, pp. 1301-1309.
[33]
M. J. Mamghani et al.,
"A Novel Optimal PI Controller Based DC/DC Boost Converter Application,"
in 2022 IEEE 13TH INTERNATIONAL SYMPOSIUM ON POWER ELECTRONICS FOR DISTRIBUTED GENERATION SYSTEMS (PEDG), 2022.
[34]
F. Ruggeri et al.,
"Safety-based Dynamic Task Offloading for Human-Robot Collaboration using Deep Reinforcement Learning,"
in 2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2022, pp. 2119-2126.
[35]
T. N. Le et al.,
"A Novel Simulation-Based Quality Metric for Evaluating Grasps on 3D Deformable Objects,"
in 2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2022, pp. 3123-3129.
[36]
J. Kamat et al.,
"BITKOMO : Combining Sampling and Optimization for Fast Convergence in Optimal Motion Planning,"
in 2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2022, pp. 4492-4497.
[37]
A. Linard et al.,
"Inference of Multi-Class STL Specifications for Multi-Label Human-Robot Encounters,"
in 2022 IEEE/RSJ international conference on intelligent robots and systems (IROS), 2022, pp. 1305-1311.
[38]
M. Lippi et al.,
"Augment-Connect-Explore : a Paradigm for Visual Action Planning with Data Scarcity,"
in 2022 IEEE/RSJ international conference on intelligent robots and systems (IROS), 2022, pp. 754-761.
[39]
I. Athanasiadis, N. Bore and J. Folkesson,
"Underwater Image Classification via Multiview-based Auxiliary Learning,"
in 2022 OCEANS HAMPTON ROADS, 2022.
[40]
H. Yin, M. C. Welle and D. Kragic,
"Embedding Koopman Optimal Control in Robot Policy Learning,"
in 2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2022, pp. 13392-13399.
[41]
A. Reichlin et al.,
"Back to the Manifold : Recovering from Out-of-Distribution States,"
in 2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2022, pp. 8660-8666.
[42]
C. Chamzas et al.,
"Comparing Reconstruction- and Contrastive-based Models for Visual Task Planning,"
in 2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2022, pp. 12550-12557.
[43]
H. Yin, C. K. Verginis and D. Kragic,
"Consensus-based Normalizing-Flow Control : A Case Study in Learning Dual-Arm Coordination,"
in 2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2022, pp. 10417-10424.
[44]
L. Ericson and P. Jensfelt,
"FloorGenT : Generative Vector Graphic Model of Floor Plans for Robotics,"
in 2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2022, pp. 12485-12491.
[45]
M. Vahs, C. Pek and J. Tumova,
"Gaussian Belief Space Planning Under Temporal Logic Specifications,"
in Workshop on Safe and Reliable Robot Autonomy under Uncertainty, 2022.
[46]
C. Sylla et al.,
"Smart Toys, Smart Tangibles, Robots and other Smart Things for Children,"
International Journal of Child-Computer Interaction, vol. 33, pp. 100489, 2022.
[47]
L. Rixon Fuchs, A. Gallstrom and A. Maki,
"Towards Dense Point Correspondence with PatchMatch in Low-Resolution Sonar Images,"
in 2022 IEEE/OES AUTONOMOUS UNDERWATER VEHICLES SYMPOSIUM (AUV), 2022.
[48]
Y. Xie, N. Bore and J. Folkesson,
"Towards Differentiable Rendering for Sidescan Sonar Imagery,"
in 2022 IEEE/OES AUTONOMOUS UNDERWATER VEHICLES SYMPOSIUM (AUV), 2022.
[49]
A. Güneysu Özgür et al.,
"The effect of gamified robot-enhanced training on motor performance in chronic stroke survivors,"
Heliyon, vol. 8, no. 11, pp. e11764, 2022.
[50]
P. Khanna, M. Björkman and C. Smith,
"Human Inspired Grip-Release Technique for Robot-Human Handovers,"
in 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids), 2022, pp. 694-701.