Todor Stoyanov

Todor Stoyanov

Associate Professor (head)

AASS Research Center
School of Science and Technology
Örebro University
70182 Örebro, Sweden
Room T2252c
Phone
todor.stoyanov@oru.se

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Brief CV

I am an Associate Professor in Computer Science at Örebro University since August 2018. My primary research interests lie in autonomy for mobile robots, with a focus on perception algorithms and motion synthesis for manipulation. I hold a PhD in Computer Science from Örebro University, defended in 2012, on the topic of autonomous robot navigation.

I am also a WASP affiliated faculty. I serve as PI for one collaborative WASP project since June 2019. 

Supervision and Teaching

I am currently co-supervising the following PhD students:

  • Quanato Yang, working on continuous reinforcement learning;
  • Yuxuan Yang, working on model learning and state estimation for deformable linear objects, such as cables and hoses;
  • Marco Iannottta, industrial PhD student working on generalizable skill acquisition through reinforcement learning;
  • David Caceres Dominguez, industrial PhD student working on interactive learning and learning from demonstrations for manipulation;
  • Shih-Min Yang, working on learning for perception and manipulation;

My former students at Örebro University:

  • Dinh-Cuong Hoang, defended his PhD thesis “Vision-based Perception For Autonomous Robotic Manipulation” in Decemeber 2021.
  • Daniel R. Canelhas, defended his PhD thesis “Truncated Signed Distance Fields Applied To Robotics” in April 2016. (second supervisor)

Publications

Journal Articles

[1] S. Gugliermo, D. C. Dominguez, M. Iannotta, T. Stoyanov and E. Schaffernicht. Evaluating behavior trees. Robotics and Autonomous Systems, 178, 2024BibTeX | 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, 2023BibTeX | DiVA ]
[3] D. C. 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, 2022BibTeX | DiVA ]
[4] Y. Yang, J. A. Stork and T. Stoyanov. Learning differentiable dynamics models for shape control of deformable linear objects. Robotics and Autonomous Systems, 158, 2022BibTeX | DiVA ]
[5] 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, 2022BibTeX | DiVA ]
[6] 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, 2022BibTeX | DiVA ]
[7] 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, 2022BibTeX | DiVA ]
[8] 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, 2022BibTeX | DiVA | PDF ]
[9] 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, 2022BibTeX | DiVA ]
[10] 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, 2022BibTeX | DiVA ]
[11] 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, 2020BibTeX | DiVA | PDF ]
[12] 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, 2020BibTeX | DiVA | PDF ]
[13] 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, 2020BibTeX | DiVA ]
[14] D. Sun, Q. Liao, A. Kiselev, T. Stoyanov and A. Loutfi. Shared mixed reality-bilateral telerobotic system. Robotics and Autonomous Systems, 134, 2020BibTeX | DiVA ]
[15] 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, 2019BibTeX | DiVA ]
[16] 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, 2019BibTeX | DiVA | PDF ]
[17] 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, 2019BibTeX | DiVA ]
[18] D. R. Canelhas, E. Schaffernicht, T. Stoyanov, A. Lilienthal and A. J. Davison. Compressed Voxel-Based Mapping Using Unsupervised Learning. Robotics, 6(3), 2017BibTeX | DiVA ]
[19] 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, 2017BibTeX | DiVA ]
[20] 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, 2016BibTeX | DiVA | PDF ]
[21] 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, 2016BibTeX | DiVA ]
[22] 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, 2016BibTeX | DiVA | PDF ]
[23] 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, 2015BibTeX | DiVA ]
[24] 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, 2014BibTeX | DiVA | PDF ]
[25] 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, 2013BibTeX | DiVA ]
[26] 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, 2013BibTeX | DiVA ]
[27] 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, 2013BibTeX | DiVA ]
[28] 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, 2012BibTeX | DiVA ]

Book Chapters

[1] 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, 2009BibTeX | DiVA ]

Refereed Conference and Workshop Articles

[1] 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, 2024BibTeX | DiVA | PDF ]
[2] 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) 2023BibTeX | DiVA | PDF ]
[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, 2022BibTeX | DiVA | PDF ]
[4] M. Iannotta, D. C. 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 2022BibTeX | 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 2022BibTeX | DiVA | PDF ]
[6] 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, 2022BibTeX | DiVA | PDF ]
[7] F. Rietz, E. Schaffernicht, T. Stoyanov and J. A. Stork. Towards Task-Prioritized Policy Composition. 2022BibTeX | DiVA ]
[8] Q. Yang, J. A. Stork and T. Stoyanov. Transferring Knowledge for Reinforcement Learning in Contact-Rich Manipulation. 2022BibTeX | DiVA ]
[9] 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) 2021BibTeX | DiVA | PDF ]
[10] 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, 2021BibTeX | DiVA | PDF ]
[11] 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) 2021BibTeX | DiVA | PDF ]
[12] 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, 2020BibTeX | DiVA ]
[13] 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 2019BibTeX | DiVA | PDF ]
[14] 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, 2018BibTeX | DiVA | PDF ]
[15] 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, 2018BibTeX | DiVA ]
[16] 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, 2018BibTeX | DiVA ]
[17] 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, 2017BibTeX | DiVA ]
[18] 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, 2016BibTeX | DiVA | PDF ]
[19] 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, 2015BibTeX | DiVA | PDF ]
[20] 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, 2015BibTeX | DiVA ]
[21] 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 2015BibTeX | DiVA | PDF ]
[22] 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 2015BibTeX | DiVA | PDF ]
[23] 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, 2015BibTeX | DiVA ]
[24] 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. 2015BibTeX | DiVA ]
[25] 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 2014BibTeX | DiVA | PDF ]
[26] 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, 2014BibTeX | DiVA ]
[27] 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, 2014BibTeX | DiVA ]
[28] 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 2014BibTeX | DiVA ]
[29] 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, 2014BibTeX | 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, 2013BibTeX | DiVA ]
[31] 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, 2013BibTeX | DiVA ]
[32] 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, 2013BibTeX | DiVA ]
[33] 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, 2013BibTeX | DiVA ]
[34] 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, 2013BibTeX | DiVA ]
[35] 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, 2013BibTeX | DiVA ]
[36] 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, 2013BibTeX | DiVA ]
[37] 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, 2013BibTeX | DiVA ]
[38] 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, 2012BibTeX | DiVA ]
[39] 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, 2012BibTeX | DiVA ]
[40] 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) 2012BibTeX | DiVA ]
[41] 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, 2011BibTeX | DiVA | PDF ]
[42] 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) 2011BibTeX | DiVA ]
[43] 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 2010BibTeX | DiVA ]
[44] 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, 2010BibTeX | DiVA | PDF ]
[45] 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) 2009BibTeX | DiVA ]
[46] 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, 2009BibTeX | DiVA | PDF ]
[47] 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, 2009BibTeX | DiVA ]
[48] 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, 2008BibTeX | DiVA ]
[49] 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. 2008BibTeX | DiVA ]
[50] S. Carpin, T. Stoyanov, Y. Nevatia, M. Lewis and J. Wang. Quantitative Assessments of USARSim Accuracy. 2006BibTeX | DiVA ]

Theses

[1] 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, 2012BibTeX | DiVA ]