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 (2020 - 2019) of the Mobile Robotics and Intelligent Systems

  • J. Martí, A. Santamaria-Navarro, C. Ocampo-Martínez and J. Andrade-Cetto. Multi-task closed-loop inverse kinematics stability through semidefinite programming, 2020 IEEE International Conference on Robotics and Automation, 2020, Paris, France, to appear.

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  • E. Corona, A. Pumarola, G. Alenyà and F. Moreno-Noguer. Context-aware human motion prediction, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020, Virtual, pp. 6992-7001, to appear.

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  • E. Corona, A. Pumarola, G. Alenyà, F. Moreno-Noguer and G. Rogez. Ganhand: Predicting human grasp affordances in multi-object scenes, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020, Virtual, pp. 5031-5041, to appear.

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  • A. Pumarola, S. Popov, F. Moreno-Noguer and V. Ferrari. C-Flow: Conditional generative flow models for images and 3D point clouds, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020, Virtual, to appear.

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  • A. Pumarola, A. Agudo, A.M. Martinez, A. Sanfeliu and F. Moreno-Noguer. GANimation: One-shot anatomically consistent facial animation. International Journal of Computer Vision, 128: 698-713, 2020.

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  • E. Repiso, A. Garrell Zulueta and A. Sanfeliu. Adaptive side-by-side social robot navigation to approach and interact with people. International Journal of Social Robotics: 1-22, 2020, to appear.

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  • J. Deray and J. Solà. Manif: A micro Lie theory library for state estimation in robotics applications. Journal of Open Source Software, 5(46): 1371, 2020.

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  • G. Ferrer and A. Sanfeliu. Anticipative kinodynamic planning: Multi-objective robot navigation in urban and dynamic environments. Autonomous Robots, 43: 1473-1488, 2019.

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  • V. Vaquero, K. Fischer, F. Moreno-Noguer, A. Sanfeliu and S. Milz. Improving map re-localization with deep 'movable' objects segmentation on 3D LiDAR point clouds, 2019 IEEE Intelligent Transportation Systems Conference, 2019, Auckland, New Zeland, pp. 942-949.

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  • A. Santamaria-Navarro, J. Solà and J. Andrade-Cetto. Visual Guidance of Unmanned Aerial Manipulators. Volume 125 of Springer Tracts in Advanced Robotics. Springer International Publishing, 2019.

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  • A. Jiménez, J. Andrade-Cetto, I. Tesfai, I. Dontas, C. Capitán, E. Oliveres, H. Jia and A. Kostaridis. Galileo and EGNOS as an asset for UTM safety and security, 25th Ka and Broadband Communications Conference, 2019, Sorrento, Italy.

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  • V. Vaquero, E. Repiso and A. Sanfeliu. Robust and real-time detection and tracking of moving objects with minimum 2D LiDAR information to advance autonomous cargo handling in ports. Sensors, 19(1): 107, 2019.

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  • N. Palomeras, M. Carreras and J. Andrade-Cetto. Active SLAM for autonomous underwater exploration. Remote Sensing, 11(23): 2827:1-19, 2019.

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  • M. Villamizar, A. Sanfeliu and F. Moreno-Noguer. Online learning and detection of faces with low human supervision. The Visual Computer, 35(3): 349-370, 2019.

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  • A. Pumarola, J. Sanchez, G. P. T. Choi, A. Sanfeliu and F. Moreno-Noguer. 3DPeople: Modeling the geometry of dressed humans, 17th International Conference on Computer Vision, 2019, Seoul, pp. 2242-2251.

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  • J. Pérez and A. Sanfeliu. Anticipatory kinodynamic motion planner for computing the best path and velocity trajectory in autonomous driving. Robotics and Autonomous Systems, 114: 93-105, 2019.

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  • A. Pumarola, V. Goswami, F. Vicente, F. de la Torre and F. Moreno-Noguer. Unsupervised image-to-video clothing transfer, 2019 ICCV Workshop on Computer Vision for Fashion, Art and Design, 2019, Seoul, pp. 3181-3184.

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  • A. Penate-Sanchez. Camera Pose Estimation in Complex Environments. LAP Lambert, 2019.

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  • E. Repiso, F. Zanlungo, T. Kanda, A. Garrell Zulueta and A. Sanfeliu. People's V-formation and side-by-side model adapted to accompany groups of people by social robots, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019, Macau, pp. 202-2088.

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  • J. Vallvé, J. Solà and J. Andrade-Cetto. Pose-graph SLAM sparsification using factor descent. Robotics and Autonomous Systems, 119: 108-118, 2019.

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  • M. Galvan, E. Repiso and A. Sanfeliu. Robot navigation to approach people using G2-spline path planning and extended social force model, 4th Iberian Robotics Conference, 2019, Porto, Portugal, Vol 1093 of Advances in Intelligent Systems and Computing, pp. 15-27, Springer.

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  • A. Santamaria-Navarro, J. Solà and J. Andrade-Cetto. Odometry estimation for aerial manipulation. In Aerial Robotic Manipulation. Vol 129 of Springer Tracts in Advanced Robotics, 219-228. Springer, 2019.

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  • B. Magyar, N. Tsiogkas, J. Deray, S. Pfeiffer and D. Lane. Timed-elastic bands for manipulation motion planning. IEEE Robotics and Automation Letters, 4(4): 3513-3520, 2019.

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  • E. Guerra, A. Pumarola, A. Grau and A. Sanfeliu. Perception for detection and grasping. In Aerial Robotic Manipulation. Vol 129 of Springer Tracts in Advanced Robotics, 275-283. Springer, 2019.

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  • M. Fourmy, D. Atchuthan, N. Mansard, J. Solà and T. Flayols. Absolute humanoid localization and mapping based on IMU Lie group and fiducial markers, 2019 IEEE-RAS International Conference on Humanoid Robots, 2019, , pp. 237-243.

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  • A. Amor, A. Ruiz, F. Moreno-Noguer and A. Sanfeliu. Precise localization for aerial inspection using augmented reality markers. In Aerial Robotic Manipulation. Vol 129 of Springer Tracts in Advanced Robotics, 249-259. Springer, 2019.

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  • A. Garrell Zulueta, C. Coll, R. Alquézar Mancho and A. Sanfeliu. Teaching a drone to accompany a person from demonstrations using non-linear ASFM, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019, Macau, pp. 1985-1991.

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  • A. Pumarola, A. Vakhitov, A. Agudo, F. Moreno-Noguer and A. Sanfeliu. Relative localization for aerial manipulation with PL-SLAM. In Aerial Robotic Manipulation. Vol 129 of Springer Tracts in Advanced Robotics, 239-248. Springer, 2019.

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  • M. Dalmasso, A. Garrell Zulueta, P. Jiménez and A. Sanfeliu. Human-robot collaborative navigation search using social reward sources, 4th Iberian Robotics Conference, 2019, Porto, Portugal, Vol 1093 of Advances in Intelligent Systems and Computing, pp. 84-95, Springer.

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  • M. Villamizar and A. Sanfeliu. Robust perception for aerial inspection: Adaptive and on-line techniques. In Aerial Robotic Manipulation. Vol 129 of Springer Tracts in Advanced Robotics, 261-273. Springer, 2019.

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  • O. Gil and A. Sanfeliu. Effects of a social force model reward in robot navigation based on deep reinforcement learning, 4th Iberian Robotics Conference, 2019, Porto, Portugal, Vol 1093 of Advances in Intelligent Systems and Computing, pp. 213-224, Springer.

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  • A. Santamaria-Navarro, J. Andrade-Cetto and V. Lippiello. Visual servoing of aerial manipulators. In Aerial Robotic Manipulation. Vol 129 of Springer Tracts in Advanced Robotics, 191-202. Springer, 2019.

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  • J. Deray, B. Magyar, J. Solà and J. Andrade-Cetto. Timed-elastic smooth curve optimization for mobile-base planning, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019, Macau, pp. 3143-3149.

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  • J. Deray, J. Solà and J. Andrade-Cetto. Joint on-manifold self-calibration of odometry model and sensor extrinsics using pre-integration, 9th European Conference on Mobile Robots, 2019, Prague, pp. 1-6.

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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
Group photo

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