VIS - Visió Artificial i Sistemes Intel·ligents

 

Recerca bàsica i aplicada al desenvolupament de sistemes intel•ligents capaços d'interactuar amb el món de forma autònoma i ubica. Aquests sistemes hauran de percebre, raonar, planificar, actuar i aprendre de l'experiència prèvia. El grup treballa activament en tres àrees: robòtica social i aèria ; visió per computador i reconeixement estructural de patrons. Dins de la robòtica social s’està treballant en els següents temes: Interacció robot-humà; localització i navegació social i autònoma de robots; localització i construcció simultània de mapes (SLAM); robòtica ubiqua; robòtica mòbil cooperativa; i robòtica aèria. En visió per computador es treballa en: seguiment, identificació i reconeixement de objectes; en xarxes de sensors de càmeres; fusió de dades; i percepció cooperativa. I en reconeixement estructural de patrons s'està treballant en mètodes de síntesi i coincidència de grafs i el la seva aplicació a la robòtica.

The Artificial Vision and Intelligent Systems Group (VIS) carries out basic and applied research with the aim of understanding and designing intelligent systems that are capable of interacting with the real world in an autonomous and wide-reaching manner. Such intelligent systems must perceive, reason, plan, act and learn from previous experiences. The group works on the following topics: robust colour image segmentation and labelling, pattern recognition, viewpoint invariant object learning and recognition, object tracking, face tracking, biometrics, processing and analysis of medical images for diagnosis, document analysis, mobile robot navigation, simultaneous localisation and map building, visual servoing, and human-computer interaction. The possible areas of application of the VIS?s research include the automotive and transport industry, the biomedical imaging industry, the space industry, robotics applications, security, home and office automation, the entertainment industry, and future computing enviro

The Artificial Vision and Intelligent Systems Group (VIS) carries out basic and applied research with the aim of understanding and designing intelligent systems that are capable of interacting with the real world in an autonomous and wide-reaching manner. Such intelligent systems must perceive, reason, plan, act and learn from previous experiences. The group works on the following topics: robust colour image segmentation and labelling, pattern recognition, viewpoint invariant object learning and recognition, object tracking, face tracking, biometrics, processing and analysis of medical images for diagnosis, document analysis, mobile robot navigation, simultaneous localisation and map building, visual servoing, and human-computer interaction. The possible areas of application of the VIS?s research include the automotive and transport industry, the biomedical imaging industry, the space industry, robotics applications, security, home and office automation, the entertainment industry, and future computing enviro

Recent Submissions

  • Human-robot collaborative minimum time search through sub-priors in ant colony optimization 

    Gil Viyuela, Óscar; Sanfeliu Cortés, Alberto (Institute of Electrical and Electronics Engineers (IEEE), 2024-11)
    Article
    Open Access
    Human-Robot Collaboration (HRC) has evolved into a highly promising issue owing to the latest breakthroughs in Artificial Intelligence (AI) and Human-Robot Interaction (HRI), among other reasons. This emerging growth ...

  • Cybernetic Avatars and society 

    Nakano, Yukiko; Kanda, Takayuki; Even, J.; Sanfeliu Cortés, Alberto; Garrell Zulueta, Anais; Kukita, Minao; Shimpo, Fumio; Yuasa, Harumichi; Tsugita, Shun (Springer, 2024-11-15)
    Part of book or chapter of book
    Open Access
    Toward a future symbiotic society with Cybernetic Avatars (CAs), it is crucial to develop socially well-accepted CAs and to discuss legal, ethical, and socioeconomic issues to update social rules and norms. This chapter ...

  • Force and velocity prediction in human-robot collaborative transportation tasks through video retentive networks 

    Domínguez Vidal, José Enrique; Sanfeliu Cortés, Alberto (Institute of Electrical and Electronics Engineers (IEEE), 2024)
    Conference report
    Open Access
    In this article, we propose a generalization of a Deep Learning State-of-the-Art architecture such as Retentive Networks so that it can accept video sequences as input. With this generalization, we design a force/velocity ...

  • Human-robot harvesting plan negotiation: perception, grape mapping and shared planning 

    Dalmasso Blanch, Marc; García Ruiz, Francisco; Ciarfuglia, Thomas A.; Saraceni, Leonardo; Motoi, Ionut M.; Gil Moya, Emilio; Sanfeliu Cortés, Alberto (2024)
    Conference report
    Open Access
    In this paper we present an application of plan negotiation for distributing work in Human-Robot Teams (HRT), engaging in a shared plan generation process. This model has been experimented over data collected from a real-life ...

  • Body gestures recognition for social human-robot interaction 

    Laplaza Galindo, Javier; Sanfeliu Cortés, Alberto; Garrell Zulueta, Anais (Institute of Electrical and Electronics Engineers (IEEE), 2024)
    Conference report
    Open Access
    In this paper, a solution for human gesture classification is proposed. The solution uses a Deep Learning model and is meant to be useful for non-verbal communication between humans and robots. The research focuses on the ...

  • TAENet: transencoder-based all-in-one image enhancement with depth awareness 

    Fang, Wanchuan; Wang, Chuansheng; Li, Zuoyong; Grau Saldes, Antoni; Lai, Taotao; Chen, Jianzhang (Springer, 2024-06-08)
    Article
    Restricted access - publisher's policy
    Recently, CNN-based all-in-one image enhancement methods have been proposed to solve multiple image degradation tasks. However, these CNN-based methods usually have two limitations. One limitation is that they usually ...

  • DedustGAN: unpaired learning for image dedusting based on Retinex with GANs 

    Meng, Xianglong; Huang, Jiayan; Li, Zuoyong; Wang, Chuansheng; Teng, Shenghua; Grau Saldes, Antoni (Elsevier, 2024-06-01)
    Article
    Restricted access - publisher's policy
    Image dedusting has gained increasing attention as a preprocessing step for computer vision tasks. Current traditional image dedusting methods rely on a variety of constraints or priors, which are easy to be limited in ...

  • Toward the deployment of an autonomous last-mile delivery robot in urban areas: the ona prototype platform 

    Santamaria Navarro, Àngel; Hernández Juan, Sergi; Herrero Cotarelo, Fernando; López Mellado, Alejandro; Pino Bastida, Iván del; Rodriguez Linares, Nicolás; Fernández, Carlos; Baldó Oliva, Albert; Lemardele, Clement; Garrell Zulueta, Anais; Vallvé, Joan; Taher, Hafsa; Puig-Pey Clavería, Ana María; Pagès, Laia; Sanfeliu Cortés, Alberto (2024-01-01)
    Article
    Open Access
    Nowadays, the skyrocketing last-mile freight transportation in urban areas is leading to very negative effects (e.g., pollution, noise or traffic congestion), which could be minimized by using autonomous electric vehicles. ...

  • Robots in waste management 

    Amante García, Beatriz; Puig-Pey Clavería, Ana María; Zamora i Mestre, Joan-Lluís; Moreno Sanz, Joan; Sanfeliu Cortés, Alberto (2024-12-01)
    Article
    Restricted access - publisher's policy
    There are different strategies for urban waste management. At present, solutions are being sought for example to the noise that the collections cause to the inhabitants in the cities, as well as the environmental impact. ...

  • Dehazing quality evaluation algorithm integrating dark channel theory and image depth estimation 

    Huang, Jiayan; Xu, Xin Xin; Luo, Shao Ye; Zhao, Wan Qi; Fan, Haoyi; Grau Saldes, Antoni; Guerra Paradas, Edmundo; Wang, Chuansheng; Zhang, Fuquan (2024-05-01)
    Article
    Open Access
    Image dehazing is an important research topic and hotspot in the fields of image processing and computer vision. Therefore, evaluating the performance of image dehazing algorithms has become an import research issue. ...

  • Exploring transformers and visual transformers for force prediction in human-robot collaborative transportation tasks 

    Domínguez Vidal, José Enrique; Sanfeliu Cortés, Alberto (Institute of Electrical and Electronics Engineers (IEEE), 2024)
    Conference report
    Restricted access - publisher's policy
    In this paper, we analyze the possibilities offered by Deep Learning State-of-the-Art architectures such as Transformers and Visual Transformers in generating a prediction of the human’s force in a Human-Robot collaborative ...

  • Human motion trajectory prediction using the social force model for real-time and low computational cost applications 

    Gil Viyuela, Óscar; Sanfeliu Cortés, Alberto (Springer, 2023)
    Conference report
    Restricted access - publisher's policy
    Human motion trajectory prediction is a very important functionality for human-robot collaboration, specifically in accompanying, guiding, or approaching tasks, but also in social robotics, self-driving vehicles, or ...

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