• 30 May 2023

    New job opportunity on behaviour modelling

    We are seeking a highly motivated and skilled Data Scientist to join our research team as a Knowledge Transfer Partnership (KTP) Associate. This exciting opportunity involves collaborating with researchers at Aston University and Legrand Care to develop innovative solutions in user behaviour modelling for fall prediction. The successful applicant will play a crucial role in advancing knowledge and making a real-world impact in healthcare technology.

    Both MSc and PhD applicants are welcome to apply for this 30 month post.

    Do not hesitate to ask if you have any questions!

    Application link: https://jobs.aston.ac.uk/Vacancy.aspx?ref=0429-23.

  • 7 January 2022

    PhD Studentships available!

    We have two PhD studentships available (application deadline 31st January 2022).
    More information


    1. Human Activity Analysis In Smart Environments
      • Area of Research: Assisted Living, Machine Learning, Artificial Intelligence
      • Aim and Objectives: Analysing human activity has a wide variety of applications, including but not limited to human-robot interaction, security and assisted living. Although limited by some technological, economical, ethical and privacy constraints, the impact of these applications is no longer a promise for the future, but a reality. Chairs and glasses are currently being used to monitor older people’s safety to promote healthy independent living with simple sensors such as fall detectors. Autonomous cars and robots analyse pedestrian behaviour to assess risk and comfort. The main goal of the project will be to analyse behaviour based on vision sensors that allow for non-invasive analysis. When considering vision-based data acquisition methods, non-invasiveness, accuracy and privacy form a triangle where one corner is sacrificed. Methods based on markers or wearables are accurate and only gather the necessary data, but are invasive. Non-invasive methods are either of limited accuracy or prone to generate serious privacy concerns. Processing the acquired data has similar limitations in terms of accuracy, privacy and response time. The aim of the PhD will be to remove or mitigate to the greatest possible extent these limitations. The student will design and develop models to implement data acquisition and activity analysis, and evaluate how these models perform considering accuracy, response time, privacy and non-invasiveness.
    2. Self-supervised Monocular Depth Estimation
      • Area of Research: Computer Vision
      • Project Summary, Aim and Objectives: This PhD project is a collaboration between Aston University and Aurrigo Ltd, a global leader in autonomous vehicle technology and manufacturer of autonomous passenger transportation systems. A detailed understanding of the 3D environment structure and the motion of dynamic objects is essential for autonomous navigation. This is usually achieved through a mixture of sensors such as Li-DAR, RADAR and cameras located around the vehicle. Recently there has been a major drive by some of the major Autonomous Vehicle (AV) manufacturers to remove their reliance on Li-DAR sensors. The reasons cited include their large size, high cost as well as lack of flexibility arising from the need to have pre-mapped Revised December 2021 environments for Li-DAR localization to work. In the last two years, several Deep Learning systems have been proposed that automatically convert a simple camera feed into a depth-map feed. However, despite promising results, these systems are not yet drop-in replacements for Li-DAR because there is a significant gap in accuracy and reliability. Our goal is to develop a monocular depth estimation technology that convincingly competes with state- of-the-art supervised methods of depth estimation as well as expensive sensor equipment (Li-DAR). To achieve this, we will leverage Aurrigo’s experience with autonomous vehicle perception systems as well as Aston’s leading research in 3D reconstruction from visual data. Alongside our main goal the PhD student will also be making contributions in the following secondary goals:
        • estimating the movement of dynamic objects in an image and the camera movement. The analysis will focus mainly on self-driving vehicles and develop a method of perception understanding for the camera.
        • the developing area of self-supervised learning to utilise more efficient learning of scenes.
        • using monocular depth estimations for scene construction and scene understanding.
        • making a detailed comparison between human perception and camera perception.

  • 6 May 2021

    PhD Studentship on Ethics-aware Cognitive Architectures for Ambient Intelligence (UK applicants only)

    The selected candidate will study ambient intelligent systems, focusing on the artificial intelligence models and the cognitive architectures required to provide the services that we aim for. This will be done while accounting for the aforementioned economic and societal issues. Edge computing will be leveraged for privacy and energy efficiency purposes. Data curation and model auditing will be carefully studied and implemented to prevent systemic biases.

    The student will deliver a cognitive architecture encompassing a series of state-of-the-art subsystems for perception, planning, user profiling and actuation, as well as a number of technology demonstrators to showcase the benefits of ethical ambient intelligence and the positive impact that it could have on our future society.

    Interested? Read more: https://jobs.aston.ac.uk/Vacancy.aspx?ref=R210156.
    If you have any questions, contact me at l.manso@aston.ac.uk.

  • 4 March 2020

    RoboComp in Google Summer of Code 2020

    RoboComp has been accepted in Google Summer of Code 2020! You have a list of all the ideas that we have for GSoC'20 in https://robocomp.github.io/web/gsoc/2020/ideas/. I have also added a section to my website where I give a little bit more detail for the two ideas I will be mentoring: https://ljmanso.com/gsoc.
  • 4 December 2019

    New project section: SNGNN

    I have just included in the website a section for my new project SNGNN: link. SNGNN is a Graph Neural Network to model adherence to social-navigation conventions for robots. Given a particular scenario composed of a room with any number of walls, objects and people (who can be interacting with each other) the network provides a social adherence ratio from 0 to 1. This information can be used to plan paths for human-aware navigation. More information in the project's page.
    This video showcases SNGNN's ability to adapt to an increasing number of people. Personal spaces shrink as the density of people in the room increases.
  • 28 August 2019

    MDPI Special Issue of Applied Sciences on Cognitive Robotics

    A new MDPI Special Issue of Applied Sciences on Cognitive Robotics has been announced:
    Link to the Special Issue: https://www.mdpi.com/journal/applsci/special_issues/cognitive_robotics
    Deadline: 15 May 2020 (articles can be submitted and published before the deadline).
    Impact factor: 2.217

    There is a growing desire to develop robots that are capable of helping humans with daily tasks. Cognitive robots need to explore and understand their environment, choose a safe and human-aware course of action, and learn—not only from experience but also through interaction. In particular, cognitive robotics aims to endow robots with the capacity to plan solutions for complex goals and to enact those plans while being reactive to unexpected changes in their environments. Among the limiting factors for their application in real-life scenarios, there are clearly ethical, technological, and economic challenges.

    Cognitive robotics includes studies on advanced mechatronics, artificial intelligence, and machine learning, as well as cognitive psychology and brain science in the frame of cognitive science. The aim of this Special Issue is to gather scientific papers addressing any of the challenges of cognitive robotics. The topics of this Special Issue include, but are not limited to, the following:
    - Active perception
    - Architectures and frameworks for cognition
    - Cognitive human-robot interaction
    - Cognitive modelling and development
    - Knowledge discovery and representation in robots
    - Learning for action and interaction
    - Cognitive architectures for interactive robots
    - Neurorobotics
    - Social and assistive robots

    Guest editors:
    Prof Antonio Bandera
    Dr Luis J. Manso
    Dr Zoe Falomir
  • 4 August 2019

    PhD Studentship position: Deep Learning in Graph Domains for Sensorised Environments (re-opened)

    Applications are invited for a studentship in the Aston Institute of Urban Technology and the Environment (ASTUTE), funded by the School of Engineering and Applied Science. The topic of the studentship will be Deep Learning in Graph Domains for Sensorised environments.
    More information: https://jobs.aston.ac.uk/Vacancy.aspx?ref=R190311
    Application form: https://map.aston.ac.uk/urd/sits.urd/run/siw_ipp_lgn.login?process=siw_ipp_app&&code1=EAS031PR&code2=0032
    Don't hesitate to contact me in case you have any questions.
  • 3 June 2019

    PhD Studentship position: Deep Learning in Graph Domains for Sensorised Environments

    Applications are invited for a studentship in the Aston Institute of Urban Technology and the Environment (ASTUTE), funded by the School of Engineering and Applied Science. The topic of the studentship will be Deep Learning in Graph Domains for Sensorised environments.
    More information: https://jobs.aston.ac.uk/Vacancy.aspx?ref=R190198
    Don't hesitate to contact me in case you have any questions.
  • 14 March 2019

    New paper in Complexity

    New paper published in the journal of Complexity (Hindawi) entitled "A Deep Evolutionary Approach to Bioinspired Classifier Optimisation for Brain-Machine Interaction" (Jordan J. Bird, Diego R. Faria, Luis J. Manso, Anikó Ekárt, and Christopher D. Buckingham).
  • 26 February 2019

    RoboComp got accepted in Google's GSoC'19

    Google has officially announced the list of organisations participating in GSoC'19 and RoboComp is in! The next important deadlines are:
    • 26 February - 25 March: Students get involved in the project and disscuss ideas with the mentors. If you're thinking about participating as a student, please follow all the tutorials.
    • 25 March - April 9: Student application process.
    • May 6: The list of accepted students is announced.
    Theres a RoboComp-specific FAQ.
  • 21 January 2019

    New paper in UK-RAS-19

    New paper accepted in UK-RAS 2019 Conference entitled "A Bioinspired Approach for Mental Emotional State Perception towards Social Awareness in Robotics" (Jordan J. Bird, Anikó Ekárt, Diego R. Faria and Luis J. Manso).

  • 19 January 2019

    New paper in Cognitive Systems Research

    New paper published in the journal of Cognitive Systems Research (Elsevier) entitled "The CORTEX Cognitive Robotics Architecture: use cases" (P. Bustos, L.J. Manso, A.J. Bandera, J.P. Bandera, I. Garcia-Varea, J. Martinez-Gomez). LINK TO THE ARTICLE.