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.
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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 (2023 - 2022) of the Mobile Robotics and Intelligent Systems

  • J.L. Crowley, J. Coutaz, J. Grosinger, J. Vazquez, C. Angulo, A. Sanfeliu, L. Iocchi and A.G. Cohn. A hierarchical framework for collaborative Artificial Intelligence. IEEE Pervasive Computing, 2023, to appear.

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  • E. Repiso, A. Garrell Zulueta and A. Sanfeliu. Adaptive social planner to accompany people in real-life dynamic environments. International Journal of Social Robotics, 2023, to appear.

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  • J.E. Domínguez, N.A. Rodriguez and A. Sanfeliu. Perception-intention-action cycle as a human acceptable way for improving human-robot collaborative tasks, 2023 ACM/IEEE International Conference on Human-Robot Interaction, 2023, Stockholm, in Companion of the HRI'23, pp. 567-571.

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  • I. Geer, J. Vallvé and J. Solà. IMU preintegration for 2D SLAM problems using Lie Groups, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022, Kyoto, pp. 1367-1373.

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  • J. Solà, J. Vallvé, J. Casals, J. Deray, M. Fourmy, D. Atchuthan, A. Corominas Murtra and J. Andrade-Cetto. WOLF: A modular estimation framework for robotics based on factor graphs. IEEE Robotics and Automation Letters, 7(2): 4710-4717, 2022.

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  • C. Mastalli, W. Merkt, J. Martí, H. Ferrolho, J. Solà, N. Mansard and S. Vijayakumar. A feasibility-driven approach to control-limited DDP. Autonomous Robots, 46(8): 985–1005, 2022.

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  • J. Laplaza, N.A. Rodriguez, J.E. Domínguez, F. Herrero, S. Hernández, A. López, A. Sanfeliu and A. Garrell Zulueta. IVO Robot: A new social robot for Human-Robot collaboration, 2022 ACM/IEEE International Conference on Human-Robot Interaction, 2022, Sapporo, Japan, pp. 860–864.

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  • A.M. Puig-Pey, A. Sanfeliu, C. Leroux, P. Dario, R. Rasso, B.C. Arrue, P. Soueres, F. Dailami, V. Vasco, M. Munih, A. Ijspeert and W. Roozing. A new methodological approach to analyze human roles in human-robot interaction scenarios, 2022 IEEE International Conference on Advanced Robotics and Its Social Impacts, 2022, Long Beach (CA), pp. 1-6, IEEE, to appear.

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  • J. Laplaza, A. Garrell Zulueta, F. Moreno-Noguer and A. Sanfeliu. Context and intention for 3D human motion prediction: Experimentation and user study in handover tasks, 31st IEEE International Symposium on Robot and Human Interactive Communication, 2022, Napoli, Italy, pp. 630-635.

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  • W.O. Chamorro, J. Solà and J. Andrade-Cetto. Event-based line SLAM in real-time. IEEE Robotics and Automation Letters, 7(3): 8146-8153, 2022.

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  • J.A. Aguilar, J. Andrade-Cetto and A.P. Husar. Control oriented estimation of the exchange current density in PEM fuel cells via stochastic filtering. International Journal of Energy Research, 46(15): 22516-22529, 2022.

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  • E. Canas, A.M. Garcia, C. Angulo and A. Garrell Zulueta. Initial test of “BabyRobot” behaviour on a teleoperated toy substitution: Improving the motor skills of toddlers, 2022 ACM/IEEE International Conference on Human-Robot Interaction, 2022, Sapporo, Japan, pp. 708-712.

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  • M. Peral, A. Sanfeliu and A. Garrell Zulueta. Efficient hand gesture recognition for human-robot interaction. IEEE Robotics and Automation Letters, 7(4): 10272-10279, 2022.

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  • Y. Tian and J. Andrade-Cetto. Spiking neural network for event camera ego-motion estimation, 2022 nanoGe MAT-SUS Symposium on Neuromorphic Sensory-Processing-Learning Systems inspired in Computational Neuroscience, 2022, Barcelona.

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  • N. Ugrinovic, A. Pumarola, A. Sanfeliu and F. Moreno-Noguer. Single-view 3d body and cloth reconstruction under complex poses, 17th International Conference on Computer Vision Theory and Applications, 2022, Online.

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  • A. Agha-mohammadi, K. Otsu, B. Morrell, D. Fan, R. Thakker, A. Santamaria-Navarro and . et al. NeBula: Team CoSTAR’s robotic autonomy solution that won phase II of DARPA Subterranean Challenge. Journal of Field Robotics, 2(47): 1432–1506, 2022.

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  • Y. Tian and J. Andrade-Cetto. Event transformer FlowNet for optical flow estimation, 2022 British Machine Vision Conference, 2022, London.

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  • O. Castro, E. Repiso, A. Garrell Zulueta and A. Sanfeliu. Classification of humans social relations within urban areas, 5th Iberian Robotics Conference, 2022, Zaragoza, Spain, Vol 590 of Lecture Notes in Networks and Systems, pp. 27-39.

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  • M. Saboia Da Silva, L. Clark, V. Thangavelu, J. Edlund, K. Otsu, G.J. Correa, V.S. Varadharajan, A. Santamaria-Navarro, T. Touma, A. Bouman, H. Melikyan, T. Pailevanian, S. Kim, A. Archanian, T.S. Vaquero, G. Beltrame, N. Napp, G. Pessin and A. Agha-mohammadi. ACHORD: Communication-aware multi-robot coordination with intermittent connectivity. IEEE Robotics and Automation Letters, 7(4): 10184-10191, 2022.

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  • O. Gil and A. Sanfeliu. Robot navigation anticipative strategies in deep reinforcement motion planning, 5th Iberian Robotics Conference, 2022, Zaragoza, Spain, Vol 590 of Lecture Notes in Networks and Systems, pp. 67-78.

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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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