Publications – AMM Group

Single-View Shape Completion for Robotic Grasping in Clutter

Abstract: In vision-based robot manipulation, a single camera view can only capture one side of objects of interest, with additional occlusions in cluttered scenes further…

Learning differentiable dynamics models for shape control of deformable linear objects

Learning differentiable dynamics models for shape control of deformable linear objects Abstract Robots manipulating deformable linear objects (DLOs)—such as surgical sutures in medical robotics, or…

MPR-RL: Multi-Prior Regularized Reinforcement Learning for Knowledge Transfer

Abstract In manufacturing, assembly tasks have been a challenge for learning algorithms due to variant dynamics of different environments. Reinforcement learning (RL) is a promising…

Context-Aware Grasp Generation in Cluttered Scenes

Abstract:Conventional methods to autonomous grasping rely on a pre-computed database with known objects to synthesize grasps, which is not possible for novel objects. On the…

Null space based efficient reinforcement learning with hierarchical safety constraints

Null space based efficient reinforcement learning with hierarchical safety constraints Abstract Reinforcement learning is inherently unsafe for use in physical systems, as learning by trial-and-error…

[1]	F. Calatrava Nicolás, S. Miyauchi, V. Fortes Rey, P. Lukowicz, T. Stoyanov and O. Martínez Mozos. Embedded Inter-Subject Variability in Adversarial Learning for Inertial Sensor-Based Human Activity Recognition. In 2025 IEEE 35th International Workshop on Machine Learning for Signal Processing (MLSP) 2025 [ BibTeX \| DiVA ]
[2]	F. Calatrava Nicolás, L. Shakti Swarup Ray, V. Fortes Rey, P. Lukowicz and O. Martínez Mozos. FAME: Feature-Augmented Multi-View Ensemble Framework for Human Activity Recognition using Inertial Sensors. 2025 [ BibTeX \| DiVA ]
[3]	M. Iannotta. Holding Form in a Shifting World : Flexible and Reliable Robot Manipulation through Behavior Trees. Örebro University, School of Science and Technology, Ph.D. Thesis, 2025 [ BibTeX \| DiVA \| PDF ]
[4]	F. M. Calatrava Nicolás, V. Fortes Rey, P. Lukowicz and O. Martínez Mozos. Inertial Sensor-Based Hierarchical Contrastive Multi-View Learning for Human Activity Recognition. In ISWC '25 : Proceedings of the 2025 ACM International Symposium on Wearable Computers, pages 106-112, 2025 [ BibTeX \| DiVA ]
[5]	Y. Shih-Min, M. Magnusson, J. A. Stork and T. Stoyanov. KEA: Keeping Exploration Alive by Proactively Coordinating Exploration Strategies. 2025 [ BibTeX \| DiVA \| PDF ]
[6]	D. Caceres Dominguez. Learning Interpretable Robot Policies from Demonstration. Örebro University, School of Science and Technology, Ph.D. Thesis, 2025 [ BibTeX \| DiVA ]
[7]	D. Cáceres Domínguez, M. Iannotta, A. Kashyap, S. Sun, Y. Yang, C. Cella, M. Colombo, M. Pelosi, G. F. Preziosa, A. Tafuro, I. Zappa, F. Busch, Y. Dong, A. Longhini, H. Lu, R. I. Cabral Muchacho, J. Styrud, S. Fregnan, M. Guberina, Z. Jia, G. Carriero, S. Lindqvist, S. Di Castro and M. Iovino. The First WARA Robotics Mobile Manipulation Challenge - Lessons Learned. In 2025 European Conference on Mobile Robots (ECMR) 2025 [ BibTeX \| DiVA ]

2024

[1]	S. Gugliermo, D. Caceres Dominguez, M. Iannotta, T. Stoyanov and E. Schaffernicht. Evaluating behavior trees. Robotics and Autonomous Systems, 178, 2024 [ BibTeX \| DiVA ]
[2]	Y. Shih-Min, M. Magnusson, J. A. Stork and T. Stoyanov. Learning Extrinsic Dexterity with Parameterized Manipulation Primitives. In 2024 IEEE International Conference on Robotics and Automation (ICRA), pages 5404-5410, 2024 [ BibTeX \| DiVA \| PDF ]
[3]	Y. Yang, J. A. Stork and T. Stoyanov. Tracking Branched Deformable Linear Objects Using Particle Filtering on Depth Images. In 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE), pages 912-919, 2024 [ BibTeX \| DiVA \| PDF ]

2023

[1]	Y. Yang. Advancing Modeling and Tracking of Deformable Linear Objects for Real-World Applications. Örebro University, School of Science and Technology, Ph.D. Thesis, 2023 [ BibTeX \| DiVA ]
[2]	F. Rietz, S. Magg, F. Heintz, T. Stoyanov, S. Wermter and J. A. Stork. Hierarchical goals contextualize local reward decomposition explanations. Neural Computing & Applications, 35(23):16693-16704, 2023 [ BibTeX \| DiVA ]
[3]	Q. Yang, J. A. Stork and T. Stoyanov. Learn from Robot : Transferring Skills for Diverse Manipulation via Cycle Generative Networks. In 2023 IEEE 19th International Conference on Automation Science and Engineering (CASE) 2023 [ BibTeX \| DiVA \| PDF ]
[4]	F. M. Calatrava Nicolás and O. Martinez Mozos. Light Residual Network for Human Activity Recognition using Wearable Sensor Data. IEEE Sensors Letters, 7(10), 2023 [ BibTeX \| DiVA ]
[5]	Q. Yang. Robot Skill Acquisition through Prior-Conditioned Reinforcement Learning. Örebro University, School of Science and Technology, Ph.D. Thesis, 2023 [ BibTeX \| DiVA \| PDF ]

2022

[1]	R. Barber, F. J. Ortiz, S. Garrido, F. Calatrava Nicolás, A. Mora, A. Prados, J. A. Vera-Repullo, J. Roca-González, I. Méndez and O. Martinez Mozos. A Multirobot System in an Assisted Home Environment to Support the Elderly in Their Daily Lives. Sensors, 22(20), 2022 [ BibTeX \| DiVA ]
[2]	D. Caceres Dominguez, M. Iannotta, J. A. Stork, E. Schaffernicht and T. Stoyanov. A Stack-of-Tasks Approach Combined With Behavior Trees : A New Framework for Robot Control. IEEE Robotics and Automation Letters, 7(4):12110-12117, 2022 [ BibTeX \| DiVA ]
[3]	D. C. Hoang, J. A. Stork and T. Stoyanov. Context-Aware Grasp Generation in Cluttered Scenes. In 2022 International Conference on Robotics and Automation (ICRA), pages 1492-1498, 2022 [ BibTeX \| DiVA \| PDF ]
[4]	M. Iannotta, D. Caceres Dominguez, J. A. Stork, E. Schaffernicht and T. Stoyanov. Heterogeneous Full-body Control of a Mobile Manipulator with Behavior Trees. In IROS 2022 Workshop on Mobile Manipulation and Embodied Intelligence (MOMA): Challenges and Opportunities 2022 [ BibTeX \| DiVA \| PDF ]
[5]	Y. Yang, J. A. Stork and T. Stoyanov. Learn to Predict Posterior Probability in Particle Filtering for Tracking Deformable Linear Objects. In 3rd Workshop on Robotic Manipulation of Deformable Objects: Challenges in Perception, Planning and Control for Soft Interaction (ROMADO-SI), IROS 2022, Kyoto, Japan 2022 [ BibTeX \| DiVA \| PDF ]
[6]	Y. Yang, J. A. Stork and T. Stoyanov. Learning differentiable dynamics models for shape control of deformable linear objects. Robotics and Autonomous Systems, 158, 2022 [ BibTeX \| DiVA ]
[7]	Q. Yang, J. A. Stork and T. Stoyanov. MPR-RL : Multi-Prior Regularized Reinforcement Learning for Knowledge Transfer. IEEE Robotics and Automation Letters, 7(3):7652-7659, 2022 [ BibTeX \| DiVA ]
[8]	J. P. A. Ivan, T. Stoyanov and J. A. Stork. Online Distance Field Priors for Gaussian Process Implicit Surfaces. IEEE Robotics and Automation Letters, 7(4):8996-9003, 2022 [ BibTeX \| DiVA ]
[9]	Y. Yang, J. A. Stork and T. Stoyanov. Online Model Learning for Shape Control of Deformable Linear Objects. In 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 4056-4062, 2022 [ BibTeX \| DiVA \| PDF ]
[10]	Y. Yang, J. A. Stork and T. Stoyanov. Particle Filters in Latent Space for Robust Deformable Linear Object Tracking. IEEE Robotics and Automation Letters, 7(4):12577-12584, 2022 [ BibTeX \| DiVA ]
[11]	F. Rietz, E. Schaffernicht, T. Stoyanov and J. A. Stork. Towards Task-Prioritized Policy Composition. 2022 [ BibTeX \| DiVA ]
[12]	Q. Yang, J. A. Stork and T. Stoyanov. Transferring Knowledge for Reinforcement Learning in Contact-Rich Manipulation. 2022 [ BibTeX \| DiVA ]
[13]	Q. Yang, A. Dürr, E. A. Topp, J. A. Stork and T. Stoyanov. Variable Impedance Skill Learning for Contact-Rich Manipulation. IEEE Robotics and Automation Letters, 7(3):8391-8398, 2022 [ BibTeX \| DiVA \| PDF ]
[14]	P. Güler, J. A. Stork and T. Stoyanov. Visual state estimation in unseen environments through domain adaptation and metric learning. Frontiers in Robotics and AI, 9, 2022 [ BibTeX \| DiVA ]
[15]	D. C. Hoang, J. A. Stork and T. Stoyanov. Voting and Attention-Based Pose Relation Learning for Object Pose Estimation From 3D Point Clouds. IEEE Robotics and Automation Letters, 7(4):8980-8987, 2022 [ BibTeX \| DiVA ]

2021

[1]	Q. Yang, A. Dürr, E. A. Topp, J. A. Stork and T. Stoyanov. Learning Impedance Actions for Safe Reinforcement Learning in Contact-Rich Tasks. In NeurIPS 2021 Workshop on Deployable Decision Making in Embodied Systems (DDM) 2021 [ BibTeX \| DiVA \| PDF ]
[2]	Y. Yang, J. A. Stork and T. Stoyanov. Learning to Propagate Interaction Effects for Modeling Deformable Linear Objects Dynamics. In 2021 IEEE International Conference on Robotics and Automation (ICRA) : IEEE International Conference on Robotics and Automation (ICRA 2021), Xi'an, China, May 30 - June 5, 2021, pages 1950-1957, 2021 [ BibTeX \| DiVA \| PDF ]
[3]	Q. Yang, J. A. Stork and T. Stoyanov. Null space based efficient reinforcement learning with hierarchical safety constraints. In 2021 European Conference on Mobile Robots (ECMR) 2021 [ BibTeX \| DiVA \| PDF ]
[4]	F. M. Calatrava-Nicolás, E. Gutiérrez-Maestro, D. Bautista-Salinas, F. J. Ortiz, J. R. González, J. A. Vera-Repullo, M. Jiménez-Buendía, I. Méndez, C. Ruiz-Esteban and O. Martinez Mozos. Robotic-Based Well-Being Monitoring and Coaching System for the Elderly in Their Daily Activities. Sensors, 21(20), 2021 [ BibTeX \| DiVA ]
[5]	D. C. Hoang. Vision-based Perception For Autonomous Robotic Manipulation. Örebro University, School of Science and Technology, Ph.D. Thesis, 2021 [ BibTeX \| DiVA \| PDF ]

2020

[1]	D. Sun, A. Kiselev, Q. Liao, T. Stoyanov and A. Loutfi. A New Mixed Reality - based Teleoperation System for Telepresence and Maneuverability Enhancement. IEEE Transactions on Human-Machine Systems, 50(1):55-67, 2020 [ BibTeX \| DiVA \| PDF ]
[2]	J. A. Stork and T. Stoyanov. Ensemble of Sparse Gaussian Process Experts for Implicit Surface Mapping with Streaming Data. In IEEE International Conference on Robotics and Automation, pages 10758-10764, 2020 [ BibTeX \| DiVA ]
[3]	V. E. Arriola-Rios, P. Güler, F. Ficuciello, D. Kragic, B. Siciliano and J. L. Wyatt. Modeling of Deformable Objects for Robotic Manipulation : A Tutorial and Review. Frontiers in Robotics and AI, 7, 2020 [ BibTeX \| DiVA ]
[4]	D. C. Hoang, A. Lilienthal and T. Stoyanov. Object-RPE : Dense 3D Reconstruction and Pose Estimation with Convolutional Neural Networks. Robotics and Autonomous Systems, 133, 2020 [ BibTeX \| DiVA \| PDF ]
[5]	D. C. Hoang, A. Lilienthal and T. Stoyanov. Panoptic 3D Mapping and Object Pose Estimation Using Adaptively Weighted Semantic Information. IEEE Robotics and Automation Letters, 5(2):1962-1969, 2020 [ BibTeX \| DiVA ]
[6]	D. Sun, Q. Liao, A. Kiselev, T. Stoyanov and A. Loutfi. Shared mixed reality-bilateral telerobotic system. Robotics and Autonomous Systems, 134, 2020 [ BibTeX \| DiVA ]

Earlier Works

[1]	D. Sun, Q. Liao, T. Stoyanov, A. Kiselev and A. Loutfi. Bilateral telerobotic system using Type-2 fuzzy neural network based moving horizon estimation force observer for enhancement of environmental force compliance and human perception. Automatica, 106:358-373, 2019 [ BibTeX \| DiVA ]
[2]	D. C. Hoang, T. Stoyanov and A. J. Lilienthal. Object-RPE : Dense 3D Reconstruction and Pose Estimation with Convolutional Neural Networks for Warehouse Robots. In 2019 European Conference on Mobile Robots, ECMR 2019 : Proceedings 2019 [ BibTeX \| DiVA \| PDF ]
[3]	C. Gabellieri, A. Palleschi, A. Mannucci, M. Pierallini, E. Stefanini, M. G. Catalano, D. Caporale, A. Settimi, T. Stoyanov, M. Magnusson, M. Garabini and L. Pallottino. Towards an Autonomous Unwrapping System for Intralogistics. IEEE Robotics and Automation Letters, 4(4):4603-4610, 2019 [ BibTeX \| DiVA \| PDF ]
[4]	B. Della Corte, H. Andreasson, T. Stoyanov and G. Grisetti. Unified Motion-Based Calibration of Mobile Multi-Sensor Platforms With Time Delay Estimation. IEEE Robotics and Automation Letters, 4(2):902-909, 2019 [ BibTeX \| DiVA ]
[5]	D. R. Canelhas, T. Stoyanov and A. J. Lilienthal. A Survey of Voxel Interpolation Methods and an Evaluation of Their Impact on Volumetric Map-Based Visual Odometry. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA),, pages 6337-6343, 2018 [ BibTeX \| DiVA \| PDF ]
[6]	T. Stoyanov, R. Krug, A. Kiselev, D. Sun and A. Loutfi. Assisted Telemanipulation : A Stack-Of-Tasks Approach to Remote Manipulator Control. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 6640-6645, 2018 [ BibTeX \| DiVA ]
[7]	J. Lundell, R. Krug, E. Schaffernicht, T. Stoyanov and V. Kyrki. Safe-To-Explore State Spaces : Ensuring Safe Exploration in Policy Search with Hierarchical Task Optimization. In IEEE-RAS Conference on Humanoid Robots, pages 132-138, 2018 [ BibTeX \| DiVA ]
[8]	D. R. Canelhas, E. Schaffernicht, T. Stoyanov, A. Lilienthal and A. J. Davison. Compressed Voxel-Based Mapping Using Unsupervised Learning. Robotics, 6(3), 2017 [ BibTeX \| DiVA ]
[9]	P. Güler, A. Pieropan, M. Ishikawa and D. Kragic. Estimating deformability of objects using meshless shape matching. In 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 5941-5948, 2017 [ BibTeX \| DiVA ]
[10]	H. Andreasson, D. Adolfsson, T. Stoyanov, M. Magnusson and A. Lilienthal. Incorporating Ego-motion Uncertainty Estimates in Range Data Registration. In 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 1389-1395, 2017 [ BibTeX \| DiVA ]
[11]	J. Ahtiainen, T. Stoyanov and J. Saarinen. Normal Distributions Transform Traversability Maps : LIDAR-Only Approach for Traversability Mapping in Outdoor Environments. Journal of Field Robotics, 34(3):600-621, 2017 [ BibTeX \| DiVA ]
[12]	D. R. Canelhas, T. Stoyanov and A. J. Lilienthal. From Feature Detection in Truncated Signed Distance Fields to Sparse Stable Scene Graphs. IEEE Robotics and Automation Letters, 1(2):1148-1155, 2016 [ BibTeX \| DiVA \| PDF ]
[13]	T. Stoyanov, R. Krug, R. Muthusamy and V. Kyrki. Grasp Envelopes : Extracting Constraints on Gripper Postures from Online Reconstructed 3D Models. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 885-892, 2016 [ BibTeX \| DiVA \| PDF ]
[14]	T. Stoyanov, N. Vaskevicius, C. A. Mueller, T. Fromm, R. Krug, V. Tincani, R. Mojtahedzadeh, S. Kunaschk, R. M. Ernits, D. R. Canelhas, M. Bonilla, S. Schwertfeger, M. Bonini, H. Halfar, K. Pathak, M. Rohde, G. Fantoni, A. Bicchi, A. Birk, A. J. Lilienthal and W. Echelmeyer. No More Heavy Lifting : Robotic Solutions to the Container-Unloading Problem. IEEE robotics & automation magazine, 23(4):94-106, 2016 [ BibTeX \| DiVA ]
[15]	R. Krug, T. Stoyanov, V. Tincani, H. Andreasson, R. Mosberger, G. Fantoni and A. J. Lilienthal. The Next Step in Robot Commissioning : Autonomous Picking and Palletizing. IEEE Robotics and Automation Letters, 1(1):546-553, 2016 [ BibTeX \| DiVA \| PDF ]
[16]	H. Andreasson, A. Bouguerra, M. Cirillo, D. N. Dimitrov, D. Driankov, L. Karlsson, A. J. Lilienthal, F. Pecora, J. P. Saarinen, A. Sherikov and T. Stoyanov. Autonomous transport vehicles : where we are and what is missing. IEEE robotics & automation magazine, 22(1):64-75, 2015 [ BibTeX \| DiVA ]
[17]	M. Magnusson, N. Vaskevicius, T. Stoyanov, K. Pathak and A. Birk. Beyond points : Evaluating recent 3D scan-matching algorithms. In 2015 IEEE International Conference on Robotics and Automation (ICRA), 2015 June(2015-June):3631-3637, 2015 [ BibTeX \| DiVA \| PDF ]
[18]	H. Andreasson, J. Saarinen, M. Cirillo, T. Stoyanov and A. Lilienthal. Fast, continuous state path smoothing to improve navigation accuracy. In IEEE International Conference on Robotics and Automation (ICRA), 2015, pages 662-669, 2015 [ BibTeX \| DiVA ]
[19]	R. Krug, T. Stoyanov and A. Lilienthal. Grasp Envelopes for Constraint-based Robot Motion Planning and Control. In Robotics: Science and Systems Conference : Workshop on Bridging the Gap between Data-driven and Analytical Physics-based Grasping and Manipulation 2015 [ BibTeX \| DiVA \| PDF ]
[20]	R. Krug, T. Stoyanov, V. Tincani, H. Andreasson, R. Mosberger, G. Fantoni, A. Bicchi and A. Lilienthal. On Using Optimization-based Control instead of Path-Planning for Robot Grasp Motion Generation. In IEEE International Conference on Robotics and Automation (ICRA) - Workshop on Robotic Hands, Grasping, and Manipulation 2015 [ BibTeX \| DiVA \| PDF ]
[21]	V. Tincani, M. Catalano, G. Grioli, T. Stoyanov, R. Krug, A. J. Lilienthal, G. Fantoni and A. Bicchi. Sensitive Active Surfaces on the Velvet II Dexterous Gripper. , pages 2744-2750, 2015 [ BibTeX \| DiVA ]
[22]	V. Tincani, T. Stoyanov, R. Krug, M. Catalano, G. Grioli, A. J. Lilienthal, G. Fantoni and A. Bicchi. The Grasp Acquisition Strategy of the Velvet II. 2015 [ BibTeX \| DiVA ]
[23]	H. Andreasson, J. Saarinen, M. Cirillo, T. Stoyanov and A. Lilienthal. Drive the Drive : From Discrete Motion Plans to Smooth Drivable Trajectories. Robotics, 3(4):400-416, 2014 [ BibTeX \| DiVA \| PDF ]
[24]	R. Krug, T. Stoyanov, M. Bonilla, V. Tincani, N. Vaskevicius, G. Fantoni, A. Birk, A. Lilienthal and A. Bicchi. Improving Grasp Robustness via In-Hand Manipulation with Active Surfaces. In Workshop on Autonomous Grasping and Manipulation : An Open Challenge 2014 [ BibTeX \| DiVA \| PDF ]
[25]	N. Vaskevicius, C. A. Mueller, M. Bonilla, V. Tincani, T. Stoyanov, G. Fantoni, K. Pathak, A. J. Lilienthal, A. Bicchi and A. Birk. Object recognition and localization for robust grasping with a dexterous gripper in the context of container unloading. , pages 1270-1277, 2014 [ BibTeX \| DiVA ]
[26]	V. H. Bennetts, E. Schaffernicht, T. Stoyanov, A. J. Lilienthal and M. Trincavelli. Robot Assisted Gas Tomography - Localizing Methane Leaks in Outdoor Environments. In 2014 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), pages 6362-6367, 2014 [ BibTeX \| DiVA ]
[27]	V. Hernandez Bennetts, E. Schaffernicht, T. Stoyanov, A. J. Lilienthal and M. Trincavelli. Robot assisted gas tomography : an alternative approach for the detection of fugitive methane emissions. In Workshop on Robot Monitoring 2014 [ BibTeX \| DiVA ]
[28]	R. Krug, T. Stoyanov, M. Bonilla, V. Tincani, N. Vaskevicius, G. Fantoni, A. Birk, A. J. Lilienthal and A. Bicchi. Velvet fingers : grasp planning and execution for an underactuated gripper with active surfaces. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages 3669-3675, 2014 [ BibTeX \| DiVA ]
[29]	J. Saarinen, H. Andreasson, T. Stoyanov and A. J. Lilienthal. 3D normal distributions transform occupancy maps : an efficient representation for mapping in dynamic environments. The international journal of robotics research, 32(14):1627-1644, 2013 [ BibTeX \| DiVA ]
[30]	R. Mojtahedzadeh, T. Stoyanov and A. J. Lilienthal. Application Based 3D Sensor Evaluation : A Case Study in 3D Object Pose Estimation for Automated Unloading of Containers. In Proceedings of the European Conference on Mobile Robots (ECMR), pages 313-318, 2013 [ BibTeX \| DiVA ]
[31]	T. Stoyanov, R. Mojtahedzadeh, H. Andreasson and A. J. Lilienthal. Comparative evaluation of range sensor accuracy for indoor mobile robotics and automated logistics applications. Robotics and Autonomous Systems, 61(10):1094-1105, 2013 [ BibTeX \| DiVA ]
[32]	T. Stoyanov, M. Magnusson and A. J. Lilienthal. Comparative evaluation of the consistency of three-dimensional spatial representations used in autonomous robot navigation. Journal of Field Robotics, 30(2):216-236, 2013 [ BibTeX \| DiVA ]
[33]	J. Saarinen, T. Stoyanov, H. Andreasson and A. J. Lilienthal. Fast 3D mapping in highly dynamic environments using normal distributions transform occupancy maps. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 4694-4701, 2013 [ BibTeX \| DiVA ]
[34]	D. R. Canelhas, T. Stoyanov and A. J. Lilienthal. Improved local shape feature stability through dense model tracking. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 3203-3209, 2013 [ BibTeX \| DiVA ]
[35]	H. Almqvist, M. Magnusson, T. Stoyanov and A. J. Lilienthal. Improving Point-Cloud Accuracy from a Moving Platform in Field Operations. In 2013 IEEE International Conference on Robotics and Automation (ICRA), pages 733-738, 2013 [ BibTeX \| DiVA ]
[36]	J. Saarinen, H. Andreasson, T. Stoyanov and A. J. Lilienthal. Normal distributions transform monte-carlo localization (NDT-MCL). In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 382-389, 2013 [ BibTeX \| DiVA ]
[37]	T. Stoyanov, J. Saarinen, H. Andreasson and A. J. Lilienthal. Normal distributions transform occupancy map fusion : simultaneous mapping and tracking in large scale dynamic environments. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 4702-4708, 2013 [ BibTeX \| DiVA ]
[38]	J. Saarinen, H. Andreasson, T. Stoyanov, J. Ala-Luhtala and A. J. Lilienthal. Normal distributions transform occupancy maps : application to large-scale online 3D mapping. In IEEE International Conference on Robotics and Automation, pages 2233-2238, 2013 [ BibTeX \| DiVA ]
[39]	D. R. Canelhas, T. Stoyanov and A. J. Lilienthal. SDF tracker : a parallel algorithm for on-line pose estimation and scene reconstruction from depth images. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 3671-3676, 2013 [ BibTeX \| DiVA ]
[40]	T. Stoyanov, M. Magnusson, A. J. Lilienthal and H. Andreasson. Fast and accurate scan registration through minimization of the distance between compact 3D NDT Representations. The international journal of robotics research, 31(12):1377-1393, 2012 [ BibTeX \| DiVA ]
[41]	K. Charusta, R. Krug, T. Stoyanov, D. Dimitrov and B. Iliev. Generation of independent contact regions on objects reconstructed from noisy real-world range data. In 2012 IEEE International Conference on Robotics and Automation (ICRA), pages 1338-1344, 2012 [ BibTeX \| DiVA ]
[42]	T. Stoyanov, M. Magnusson and A. J. Lilienthal. Point Set Registration through Minimization of the L-2 Distance between 3D-NDT Models. In 2012 IEEE International Conference on Robotics and Automation (ICRA), pages 5196-5201, 2012 [ BibTeX \| DiVA ]
[43]	H. Andreasson and T. Stoyanov. Real time registration of RGB-D data using local visual features and 3D-NDT registration. In Proc. of International Conference on Robotics and Automation (ICRA) Workshop on Semantic Perception, Mapping and Exploration (SPME) 2012 [ BibTeX \| DiVA ]
[44]	T. D. Stoyanov. Reliable autonomus navigation in semi-structured environments using the three-dimensional normal distributions transform (3D-NDT). Örebro University, School of Science and Technology, Ph.D. Thesis, 2012 [ BibTeX \| DiVA ]
[45]	T. Stoyanov, A. Louloudi, H. Andreasson and A. J. Lilienthal. Comparative evaluation of range sensor accuracy in indoor environments. In Proceedings of the 5th European Conference on Mobile Robots, ECMR 2011, pages 19-24, 2011 [ BibTeX \| DiVA \| PDF ]
[46]	T. Stoyanov, M. Magnusson, H. Almqvist and A. J. Lilienthal. On the Accuracy of the 3D Normal Distributions Transform as a Tool for Spatial Representation. In 2011 IEEE International Conference on Robotics and Automation (ICRA) 2011 [ BibTeX \| DiVA ]
[47]	G. Ferri, A. Mondini, A. Manzi, B. Mazzolai, C. Laschi, V. Mattoli, M. Reggente, T. Stoyanov, A. J. Lilienthal, M. Lettere and P. Dario. DustCart, a Mobile Robot for Urban Environments : Experiments of Pollution Monitoring and Mapping during Autonomous Navigation in Urban Scenarios. In Proceedings of ICRA Workshop on Networked and Mobile Robot Olfaction in Natural, Dynamic Environments 2010 [ BibTeX \| DiVA ]
[48]	T. Stoyanov, M. Magnusson, H. Andreasson and A. J. Lilienthal. Path planning in 3D environments using the normal distributions transform. In IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems (IROS 2010), pages 3263-3268, 2010 [ BibTeX \| DiVA \| PDF ]
[49]	T. Stoyanov and A. J. Lilienthal. Maximum Likelihood Point Cloud Acquisition from a Rotating Laser Scanner on a Moving Platform. In Proceedings of the IEEE International Conference on Advanced Robotics (ICAR) 2009 [ BibTeX \| DiVA ]
[50]	T. Stoyanov and A. J. Lilienthal. Maximum likelihood point cloud acquisition from a mobile platform. In International conference on advanced robotics, ICAR 2009., pages 1-6, 2009 [ BibTeX \| DiVA \| PDF ]
[51]	A. Birk, J. Poppinga, T. Stoyanov and Y. Nevatia. Planetary Exploration in USARSim : A Case Study including Real World Data from Mars. In RoboCup 2008 : Robot Soccer World Cup XII, pages 463-472, 2009 [ BibTeX \| DiVA ]
[52]	M. Pfingsthorn, Y. Nevatia, T. Stoyanov, R. Rathnam, S. Markov and A. Birk. Towards Cooperative and Decentralized Mapping in the Jacobs Virtual Rescue Team. In RoboCup 2008 : Robot Soccer World Cup XII Vol 5399, 5399:225-234, 2009 [ BibTeX \| DiVA ]
[53]	Y. Nevatia, T. Stoyanov, R. Rathnam, M. Pfingsthorn, S. Markov, R. Ambrus and A. Birk. Augmented Autonomy : Improving human-robot team performance in Urban Search and Rescue. In 2008 IEEE/RSJ International Conference on Robots and Intelligent Systems, vols 1-3, conference proceedings, pages 2103-2108, 2008 [ BibTeX \| DiVA ]
[54]	A. Birk, T. Stoyanov, Y. Nevatia, R. Ambrus, J. Poppinga and K. Pathak. Terrain Classification for Autonomous Robot Mobility : from Safety, Security Rescue Robotics to Planetary Exploration. 2008 [ BibTeX \| DiVA ]

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