Research line

Mobile Robotics and Intelligent Systems

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.
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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 (2025 - 2024) of the Mobile Robotics and Intelligent Systems

  • A. Santamaria-Navarro, S. Hernández, F. Herrero, A. López, I. del Pino, N.A. Rodríguez, C. Fernandez, A. Baldó, C. Lemardelé, A. Garrell Zulueta, J. Vallvé, H. Taher, A.M. Puig-Pey, L. Pagès and A. Sanfeliu. Towards the deployment of an autonomous last-mile delivery robot in urban areas. IEEE Robotics and Automation Magazine, 2025.

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  • P. Vial, J. Solà, N. Palomeras and M. Carreras. On Lie group IMU and linear velocity preintegration for autonomous navigation considering the Earth rotation compensation. IEEE Transactions on Robotics, 41: 1346-1364, 2025.

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  • F. Gebelli, L.B. Hriscu, R. Ros, S. Lemaignan, A. Sanfeliu and A. Garrell Zulueta. Personalised explainable robots using LLMs, 2025 ACM/IEEE International Conference on Human-Robot Interaction, 2025, Melbourne, Australia, pp. 1304-1308.

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  • P.T. Singamaneni, P. Bachiller, L.J. Manso, A. Garrell Zulueta, A. Sanfeliu, A. Spalanzani and R. Alami. A survey on socially aware robot navigation: taxonomy and future challenges. The International Journal of Robotics Research, 43(10): 1533-1572, 2024.

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  • O. Gil. Robot navigation issues and human-robot collaborative search using deep learning methods, 2024 IRI Doctoral Day, 2024, Barcelona, pp. 8.

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  • J.E. Domínguez and A. Sanfeliu. Voice Command Recognition for Explicit Intent Elicitation in Collaborative Object Transportation Tasks: a ROS-based Implementation, 2024 ACM/IEEE International Conference on Human-Robot Interaction, 2024, Boulder, CO, USA, pp. 412–416.

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  • H. Taher. Deep learning-based scene understanding for urban autonomous navigation, 2024 IRI Doctoral Day, 2024, Barcelona, pp. 17.

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  • J.E. Domínguez, N.A. Rodríguez and A. Sanfeliu. Perception–intention–action cycle in human–robot collaborative tasks: The collaborative lightweight object transportation use-case. International Journal of Social Robotics, 2024, to appear.

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  • Y. Tian. Bio-inspired event-driven intelligence for ego-motion estimation, 2024 IRI Doctoral Day, 2024, Barcelona, pp. 18.

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  • M. Dalmasso, V. Sanchez-Anguix, A. Garrell Zulueta, P. Jiménez and A. Sanfeliu. Exploring Preferences in Human-Robot Navigation Plan Proposal Representation, 2024 ACM/IEEE International Conference on Human-Robot Interaction, 2024, Boulder, CO, USA, pp. 369-373.

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  • Y. Tian and J. Andrade-Cetto. SDformerFlow: Spiking neural network transformer for event-based optical flow, 27th International Conference on Pattern Recognition, 2024, Kolkata, in Pattern Recognition, Vol 15315 of Lecture Notes in Computer Science, pp. 475-491, 2024, Cham.

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  • J.A. Aguilar, D. Chanal, D. Chamagne, N. Yousfi, M. Péra, A.P. Husar and J. Andrade-Cetto. A hybrid control-oriented PEMFC model based on echo state networks and Gaussian radial basis functions. Energies, 17(2): 508, 2024.

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  • M. Dalmasso, F. Garcia-Ruiz, T. Ciarfuglia, L. Saraceni, I. M. Motoi, E. Gil and A. Sanfeliu. Human-robot harvesting plan negotiation: Perception, grape mapping and shared planning, 7th Iberian Robotics Conference, 2024, Madrid, Spain, pp. 1-8.

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  • F. Gebelli, R. Ros and A. Garrell Zulueta. Participatory design for explainable robots, 2024 Workshop on Explainability for Human-Robot Collaboration at the 2024 ACM/IEEE International Conference on Human-Robot Interaction, 2024, USA.

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  • D. Natera-de Benito, A. Favata, J. Exposito, R. Gallart, O. Moya, S. Roca, A. Marzabal, L. van Noort, C. Torras, A. Nascimento, J. Medina-Cantillo, R. Pàmies-Vilà and J.M. Font. Advancing upper limb motor function evaluation in DMD and SMA via kinematic parameterization with the wearable device , 2024 Annual Congress of the World Muscle Society, 2024, Prague, pp. 14.

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  • F. Gebelli, R. Ros, S. Lemaignan and A. Garrell Zulueta. Co-designing explainable robots: a participatory design approach for HRI, 33rd IEEE International Symposium on Robot and Human Interactive Communication, 2024, Pasadena, California, USA, pp. 1564-1570, IEEE.

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  • B. Amante, A.M. Puig-Pey, J.L. Zamora, J. Moreno and A. Sanfeliu. Robots in waste management. Detritus. Multidisciplinary Journal for Circular Economy and Sustainable Management of Residues, 29: 179-190, 2024.

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  • B. Morrell, K. Otsu, A. Agha, D. Fan, S. Kim, M.F. Ginting, X. Lei, J. Edlund, S. Fakoorian, A. Bouman, F. Chavez, T. Kim, G.J. Correa, M. Saboia Da Silva, A. Santamaria-Navarro and . et al. An Addendum to NeBula: Towards extending TEAM CoSTAR’s solution to larger scale environments. IEEE Transactions on Field Robotics, 1: 476-526, 2024.

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  • J. Laplaza, F. Moreno-Noguer and A. Sanfeliu. Enhancing robotic collaborative tasks through contextual human motion prediction and intention inference. International Journal of Social Robotics: 1-20, 2024, to appear.

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  • N. Ugrinovic, A. Ruiz, A. Agudo, A. Sanfeliu and F. Moreno-Noguer. PIRO: Permutation-invariant relational network for multi-person 3D pose estimation, 19th International Conference on Computer Vision Theory and Applications, 2024, Rome (Italy), pp. 295-305.

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  • S.H. Seo, D.J. Rea, K. Kochigami, T. Kanda, J.E. Young, Y. Nakano, A. Sanfeliu and H. Ishiguro. Symbiotic society with avatars (SSA): Toward empowering social interactions beyond space and time, 2024 ACM/IEEE International Conference on Human-Robot Interaction, 2024, Boulder, CO, USA, pp. 1352-1354.

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  • J.E. Domínguez and A. Sanfeliu. Exploring transformers and visual transformers for force prediction in human-robot collaborative transportation tasks, 2024 IEEE International Conference on Robotics and Automation, 2024, Yokohama (Japan), pp. 3191-3197.

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  • J. Palmieri, P. Di Lillo, A. Sanfeliu and A. Marino. Perception-driven shared control architecture for agricultural robots performing harvesting tasks, 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024, Abu Dhabi, UAE, pp. 9328-9334.

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  • J.E. Domínguez and A. Sanfeliu. Anticipation and proactivity. Unraveling both concepts in human-robot interaction through a handover example, 33rd IEEE International Symposium on Robot and Human Interactive Communication, 2024, Pasadena, California, USA, pp. 957-962, IEEE.

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  • P. Falqueto, A. Sanfeliu, L. Palopoli and D. Fontanelli. Learning priors of human motion with vision transformers, 48th IEEE International Conference on Computers, Software, and Applications , 2024, Osaka, Japan, pp. 382-389.

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  • O. Gil and A. Sanfeliu. Human-robot collaborative minimum time search through sub-priors in ant colony optimization. IEEE Robotics and Automation Letters, 9(11): 10216-10223, 2024.

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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, 16: 1189-1221, 2024.

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  • J.E. Domínguez and A. Sanfeliu. Force and velocity prediction in human-robot collaborative transportation tasks through video retentive networks, 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024, Abu Dhabi, UAE, pp. 9307-9313.

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  • I. del Pino, A. Santamaria-Navarro, A. Garrell Zulueta, F. Torres and J. Andrade-Cetto. Probabilistic graph-based real-time ground segmentation for urban robotics. IEEE Transactions on Intelligent Vehicles, 9(5): 4989-5002, 2024.

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  • J. Laplaza, J.J. Oliver, A. Sanfeliu and A. Garrell Zulueta. Body gestures recognition for social human-robot interaction, 7th Iberian Robotics Conference, 2024, Madrid, Spain.

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  • M. Dalmasso, J.E. Domínguez, I.J. Torres, P. Jiménez, A. Garrell Zulueta and A. Sanfeliu. Shared task representation for human–robot collaborative navigation: The collaborative search case. International Journal of Social Robotics, 16: 145-171, 2024.

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  • F. Gebelli, R. Ros, S. Lemaignan and A. Garrell Zulueta. Evaluating the impact of explainability on the users’ mental models of robots over time, 33rd IEEE International Symposium on Robot and Human Interactive Communication, 2024, Pasadena, California, USA, IEEE.

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  • P. Vial, N. Palomeras, J. Solà and M. Carreras. Underwater Pose SLAM using GMM scan matching for a mechanical profiling sonar. Journal of Field Robotics, 41: 511-538, 2024.

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  • J.E. Domínguez. Perception, prediction and planning techniques in collaboration human-robot tasks, 2024 IRI Doctoral Day, 2024, Barcelona, pp. 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
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