Research line

Mobile Robotics and Intelligent Systems Image

The research activities of the MOBILE ROBOTICS line are aimed to endow mobile robots and ubiquitous computing devices the necessary skills to aid humans in everyday life activities. These skills range from pure perceptual activities such as tracking, recognition or situation awareness, to motion skills, such as localization, mapping, autonomous navigation, path planning or exploration.

Head of line: Alberto Sanfeliu Cortés

Head of line

Tech. transfer

Our activity finds applications in several fields through collaboration with our technological partners

Research projects

We carry out projects from national and international research programmes.
→ More about our research projects

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Urban service robotics

The group focuses on the design and development of service mobile robots for human assistance and human robot interaction. This includes research on novel hardware and software solutions to urban robotic services such as surveillance, exploration, cleaning, transportation, human tracking, human assistance and human guiding.

Research area 1 of Mobile Robotics

Social robotics

The group's work on social robotics has an emphasis in human robot interaction and collaboration, developing new techniques to predict and learn human behaviors, human-robot task collaboration, and the generation of emphatic robot behaviors using all types of sensors, computer vision techniques and cognitive systems technologies.

Research area 2 of Mobile Robotics

Robot localization and robot navigation

This research area tackles the creation of robust single and cooperative, indoor and outdoor robot localization solutions, using multiple sensor modalities such as GPS, computer vision and laser range finding, INS sensors and raw odometry. The area also seeks methods and algorithms for autonomous robot navigation, and robot formation; and the application of these methods on a variety of indoor and outdoor mobile robot platforms.

Research area 3 of Mobile Robotics

SLAM and robot exploration

We develop solutions for indoor and outdoor simultaneous localization and mapping using computer vision and three-dimensional range data using Bayesian estimation. The research includes the development of new filtering and smoothing algorithms that limit the load of maps using information theoretic measures; as well as the design and construction of novel sensors for outdoor mapping. This research area also studies methods for autonomous robotic exploration.

Research area 4 of Mobile Robotics

Tracking in computer vision

We study the development of robust algorithms for the detection and tracking of human activities in indoor and outdoor areas, with applications to service robotics, surveillance, and human-robot interaction. This includes the development of fixed/moving single camera tracking algorithms as well as detection and tracking methods over large camera sensor networks.

Research area 5 of Mobile Robotics

Object recognition

The group also performs research on object detection and object recognition in computer vision. Current research is heavily based on boosting and other machine learning methodologies that make extensive use of multiple view geometry. We also study the development of unique feature and scene descriptors, invariant to changes in illumination, cast shadows, or deformations.

Research area 6 of Mobile Robotics

These are the latest research projects of the Mobile Robotics and Intelligent Systems research line:

These are the most recent publications (2018 - 2017) of the Mobile Robotics and Intelligent Systems

  • J. Vallvé, J. Solà and J. Andrade-Cetto. Graph SLAM sparsification with populated topologies using factor descent optimization. IEEE Robotics and Automation Letters, 3(2): 1322-1329, 2018.

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  • A. Goldhoorn, A. Garrell Zulueta, R. Alquézar Mancho and A. Sanfeliu. Searching and tracking people with cooperative mobile robots. Autonomous Robots, 42(4): 739-759, 2018.

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  • V. Vaquero, A. Sanfeliu and F. Moreno-Noguer. Deep lidar CNN to understand the dynamics of moving vehicles, 2018 IEEE International Conference on Robotics and Automation, 2018, Brisbane, Australia, pp. 4504-4509.

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  • A. Pumarola, A. Agudo, L. Porzi, A. Sanfeliu, V. Lepetit and F. Moreno-Noguer. Geometry-aware network for non-rigid shape prediction from a single view, 2018 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2018, Salt Lake City, to appear.

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  • A. Pumarola, A. Agudo, A. Sanfeliu and F. Moreno-Noguer. Unsupervised person image synthesis in arbitrary poses, 2018 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2018, Salt Lake City, to appear.

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  • A. Pumarola, A. Agudo, A.M. Martinez, A. Sanfeliu and F. Moreno-Noguer. GANimation: Anatomically-aware facial animation from a single image, 15th European Conference on Computer Vision, 2018, Munich, in Computer Vision - ECCV 2018, Vol 11214 of Lecture Notes in Computer Science, pp. 835-851, 2018.

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  • A. Ollero, G. Heredia, A. Franchi, G. Antonelli, K. Kondak, A. Sanfeliu, A. Viguria, J.R. Martínez de Dios, F. Pierri, J. Cortés, A. Santamaria-Navarro, M.A. Trujillo, R. Balachandran, J. Andrade-Cetto and A. Rodríguez. The AEROARMS project: Aerial robots with advanced manipulation capabilities for inspection and maintenance. IEEE Robotics and Automation Magazine, 2018, to appear.

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  • V. Vaquero, A. Sanfeliu and F. Moreno-Noguer. Hallucinating dense optical flow from sparse lidar for autonomous vehicles, 2018 International Conference on Pattern Recognition, 2018, Beijing, China, to appear.

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  • M. Villamizar, J. Andrade-Cetto, A. Sanfeliu and F. Moreno-Noguer. Boosted random ferns for object detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(2): 272-288, 2018.

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  • R. Valencia and J. Andrade-Cetto. Mapping, Planning and Exploration with Pose SLAM. Volume 119 of Springer Tracts in Advanced Robotics. Springer, 2018.

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  • A. Santamaria-Navarro, G. Loianno, J. Solà, V. Kumar and J. Andrade-Cetto. Autonomous navigation of micro aerial vehicles: State estimation using fast and low-cost sensors. Autonomous Robots, 42(6): 1263-1280, 2018.

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  • V. Vaquero, G. Ros, F. Moreno-Noguer, A. M. and A. Sanfeliu. Joint coarse-and-fine reasoning for deep optical flow, 24th IEEE International Conference on Image Processing, 2017, Beijing, pp. 2558-2562.

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  • V. Vaquero, I. del Pino, F. Moreno-Noguer, J. Solà, A. Sanfeliu and J. Andrade-Cetto. Deconvolutional networks for point-cloud vehicle detection and tracking in driving scenarios, 8th European Conference on Mobile Robots, 2017, Paris, France, pp. 1-7.

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  • J. Vallvé, J. Solà and J. Andrade-Cetto. Factor descent optimization for sparsification in graph SLAM, 8th European Conference on Mobile Robots, 2017, Paris, France, pp. 1-6.

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  • I. del Pino, V. Vaquero, B. Masini, J. Solà, F. Moreno-Noguer, A. Sanfeliu and J. Andrade-Cetto. Low resolution lidar-based multi object tracking for driving applications, 3rd Iberian Robotics Conference, 2017, Seville, in Robot 2017: Third Iberian Robotics Conference, Vol 694 of Advances in Intelligent Systems and Computing, pp. 287-298, Springer.

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  • A. Garrell Zulueta, L.A. Garza, M. Villamizar, F. Herrero and A. Sanfeliu. Aerial social force model: A new framework to accompany people using autonomous flying robots, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017, Vancouver, Canada, pp. 7011-7017.

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  • E. Repiso, G. Ferrer and A. Sanfeliu. On-line adaptive side-by-side human robot companion in dynamic urban environments, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017, Vancouver, Canada, pp. 872-877.

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  • M. Villamizar, A. Garrell Zulueta, A. Sanfeliu and F. Moreno-Noguer. Random clustering ferns for multimodal object recognition. Neural Computing and Applications, 28(9): 2445-2460, 2017.

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  • E. Repiso, A. Garrell Zulueta and A. Sanfeliu. On-line adaptive side-by-side human robot companion to approach a moving person to interact, 3rd Iberian Robotics Conference, 2017, Seville, in Robot 2017: Third Iberian Robotics Conference, Vol 694 of Advances in Intelligent Systems and Computing, pp. 113-125, Springer.

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  • R. Rossi, A. Santamaria-Navarro, J. Andrade-Cetto and P. Rocco. Trajectory generation for unmanned aerial manipulators through quadratic programming. IEEE Robotics and Automation Letters, 2(2): 389-396, 2017.

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  • L. Porzi, S. Rota-Bulò, A. Penate-Sanchez, E. Ricci and F. Moreno-Noguer. Learning depth-aware deep representations for robotic perception. IEEE Robotics and Automation Letters, 2(2): 468-475, 2017.

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  • A. Garrell Zulueta, M. Villamizar, F. Moreno-Noguer and A. Sanfeliu. Teaching robot’s proactive behavior using human assistance. International Journal of Social Robotics, 9(2): 231-249, 2017.

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  • L. Porzi, A. Penate-Sanchez, E. Ricci and F. Moreno-Noguer. Depth-aware convolutional neural networks for accurate 3D pose estimation in RGB-D images, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017, Vancouver, Canada, pp. 5777-5783.

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  • J. Deray, J. Solà and J. Andrade-Cetto. Word ordering and document adjacency for large loop closure detection in 2D laser maps. IEEE Robotics and Automation Letters, 2(3): 1532-1539, 2017.

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  • A. Grau, Y. Bolea, A. Sanfeliu and A.M. Puig-Pey. The ECHORD++ Project: Robotics in a public economy, 24th International Scientifc Conference on Economic and Social Development, 2017, Warsaw, Poland, pp. 40-49.

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  • A. Pumarola, A. Vakhitov, A. Agudo, A. Sanfeliu and F. Moreno-Noguer. PL-SLAM: Real-time monocular visual SLAM with points and lines, 2017 IEEE International Conference on Robotics and Automation, 2017, Singapore, pp. 4503-4508.

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  • A. Goldhoorn, A. Garrell Zulueta, R. Alquézar Mancho and A. Sanfeliu. Searching and tracking people in urban environments with static and dynamic obstacles. Robotics and Autonomous Systems, 98: 147-157, 2017.

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  • G. Ferrer, A. Garrell Zulueta, F. Herrero and A. Sanfeliu. Robot social-aware navigation framework to accompany people walking side-by-side. Autonomous Robots, 41(4): 775-793, 2017.

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  • A. Grau, Y. Bolea, A.M. Puig-Pey, A. Sanfeliu and J. Casanovas. Sustainable technology results for sewage networks in smart cities, 5th IFIP Conference on Sustainable Internet and ICT for Sustainability, 2017, Funchal, Portugal, pp. 1-4.

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  • A. Santamaria-Navarro, P. Grosch, V. Lippiello, J. Solà and J. Andrade-Cetto. Uncalibrated visual servo for unmanned aerial manipulation. IEEE/ASME Transactions on Mechatronics, 22(4): 1610-1621, 2017.

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  • J. Pérez and A. Sanfeliu. Path and velocity trajectory selection in an anticipative kinodynamic motion planner for autonomous driving, 3rd Iberian Robotics Conference, 2017, Seville, in Robot 2017: Third Iberian Robotics Conference, Vol 694 of Advances in Intelligent Systems and Computing, pp. 434-445, Springer.

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  • D. Lunni, A. Santamaria-Navarro, R. Rossi, P. Rocco, L. Bascetta and J. Andrade-Cetto. Nonlinear model predictive control for aerial manipulation, 2017 International Conference on Unmanned Aircraft Systems, 2017, Miami, pp. 87-93.

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  • P. Lepej, A. Santamaria-Navarro and J. Solà. A flexible hardware-in-the-loop architecture for UAVs, 2017 International Conference on Unmanned Aircraft Systems, 2017, Miami, pp. 1751-1756.

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  • A.M. Puig-Pey, Y. Bolea, A. Grau and J. Casanovas. Public entities driven robotic innovation in urban areas. Robotics and Autonomous Systems, 92: 162-172, 2017.

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Mobile Robotics Laboratory

The Mobile Robotics Laboratory is an experimental area primarily devoted to hands-on research with mobile robot devices. The lab includes 3 Pioneer platforms, 2 service robots for urban robotics research based on Segway platforms, and a 4-wheel rough outdoor mobile robot, a six-legged LAURON-III walking robot, and a vast number of sensors and cameras.

Mobile Robotics Laboratory

Barcelona Robot Laboratory

The Barcelona Robot Lab encompasses an outdoor pedestrian area of 10.000 sq m., and is provided with 21 fixed cameras, a set of heterogeneous robots, full coverage of wifi and mica devices, and partial gps coverage. The area has moderate vegetation and intense cast shadows, making computer vision algorithms more than challenging.

Barcelona Robot Laboratory
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