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.
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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 (2024 - 2023) of the Mobile Robotics and Intelligent Systems

  • 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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  • 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, 2024, to appear.

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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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  • 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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  • 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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  • 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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  • A. Agha, K. Otsu, B. Morrell, 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, 2024, to appear.

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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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  • O. Gil and A. Sanfeliu. Human-robot collaborative minimum time search through sub-priors in ant colony optimization. IEEE Robotics and Automation Letters, 2024, to appear.

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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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  • 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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  • 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. Rodríguez 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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  • W.O. Chamorro, J. Solà and J. Andrade-Cetto. Event-IMU fusion strategies for faster-than-IMU estimation throughput, 4th CVPR International Workshop on Event Vision, 2023, Vancouver, pp. 3975-3982.

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  • A.M. Puig-Pey, J.L. Zamora, B. Amante, J. Moreno, A. Garrell Zulueta, A. Grau, Y. Bolea, A. Santamaria-Navarro and A. Sanfeliu. Human acceptance in the human-robot interaction scenario for last-mile goods delivery, 2023 IEEE International Conference on Advanced Robotics and Its Social Impacts, 2023, Berlin, Germany, pp. 33-39.

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  • Y. Tian and J. Andrade-Cetto. Egomotion from event-based SNN optical flow, 2023 ACM International Conference on Neuromorphic Systems, 2023, Santa Fe, NM, USA, pp. 8:1-8.

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  • E. Repiso, A. Garrell Zulueta and A. Sanfeliu. Real-life experiment metrics for evaluating human-robot collaborative navigation tasks, 32nd IEEE International Symposium on Robot and Human Interactive Communication, 2023, Busan, Korea, pp. 660-667.

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  • C. Lemardelé, A. Baldó, A. Aniculaesei, A. Rausch, M. Conill, L. Everding, T. Vietor, T. Hegerhorst, R. Henze, L. Mátyus, L. Pagès, V. Roca, A. Sanfeliu, A. Santamaria-Navarro and I. Tóháti. The LogiSmile Project - Piloting Autonomous Vehicles for Last-Mile Logistics in European cities. Transportation Research Procedia, 71: 180-187, 2023.

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  • G. Coll, I.J. Torres, A. Grau, E. Guerra and A. Sanfeliu. Accurate detection and depth estimation of table grapes and peduncles for robot harvesting, combining monocular depth estimation and CNN methods. Computers and Electronics in Agriculture: 108362, 2023.

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  • O. Gil and A. Sanfeliu. Human motion trajectory prediction using the Social Force Model for real-time and low computational cost applications, 6th Iberian Robotics Conference, 2023, Coimbra, Portugal, pp. 235–247, Springer.

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  • J.E. Domínguez and A. Sanfeliu. Inference vs. explicitness. Do we really need the perfect predictor? The human-robot collaborative object transportation case, 32nd IEEE International Symposium on Robot and Human Interactive Communication, 2023, Busan, Korea, pp. 1866-1871.

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  • J.E. Domínguez and A. Sanfeliu. Improving human-robot interaction effectiveness in human-robot collaborative object transportation using force prediction, 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2023, Detroit, MI, USA, pp. 7839-7845.

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  • A. Dhamanaskar, M. Dimiccoli, E. Corona, A. Pumarola and F. Moreno-Noguer. Enhancing egocentric 3D pose estimation with third person views . Pattern Recognition, 138(109358), 2023.

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  • C. Debeunne, J. Vallvé, A. Torres and D. Vivet. Fast bi-monocular visual odometry using factor graph sparsification, 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2023, Detroit, MI, USA, pp. 10716-10722.

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  • 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, 22(1): 9-18, 2023.

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  • F. Rivas-Manzaneque, J. Sierra-Acosta, A. Penate-Sanchez, F. Moreno-Noguer and A. Ribeiro. NeRFLight: Fast and light neural radiance fields using a shared feature grid, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023, Vancouver, Canada, pp. 12417-12427.

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  • J. Laplaza, R. Romero, A. Sanfeliu and A. Garrell Zulueta. Body gesture recognition to control a social mobile robot, 2023 ACM/IEEE International Conference on Human-Robot Interaction, 2023, Stockholm, in Companion of the HRI'23, pp. 456-460.

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  • T. Ciarfuglia, I. Motoi, L. Saraceni, M. Fawakherji, A. Sanfeliu and D. Nardi. Weakly and semi-supervised detection, segmentation and tracking of table grapes with limited and noisy data. Computers and Electronics in Agriculture, 205: 107624, 2023.

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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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