Luis J. Manso

Luis J. Manso
Aston University · School of Engineering and Applied Science

PhD.

About

97
Publications
44,301
Reads
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851
Citations
Citations since 2016
58 Research Items
702 Citations
2016201720182019202020212022050100150
2016201720182019202020212022050100150
2016201720182019202020212022050100150
2016201720182019202020212022050100150
Additional affiliations
September 2010 - December 2010
University of Coimbra
Position
  • PhD Student
February 2010 - present
Universidad de Extremadura
Position
  • Researcher
Education
June 2010 - June 2013
Universidad de Extremadura
Field of study
  • Robotics
September 2009 - June 2010
University of Extremadura
Field of study
  • Computer Science
September 2008 - September 2009
University of the West of Scotland
Field of study
  • Information Technology

Publications

Publications (97)
Preprint
Full-text available
Self-supervised monocular depth estimation has been a subject of intense study in recent years, because of its applications in robotics and autonomous driving. Much of the recent work focuses on improving depth estimation by increasing architecture complexity. This paper shows that state-of-the-art performance can also be achieved by improving the...
Article
Contemporary Artificial Intelligence technologies allow for the employment of Computer Vision to discern good crops from bad, providing a step in the pipeline of selecting healthy fruit from undesirable fruit, such as those which are mouldy or damaged. State-of-the-art works in the field report high accuracy results on small datasets (<1000 images)...
Article
Full-text available
Autonomous navigation is a key skill for assistive and service robots. To be successful, robots have to minimise the disruption caused to humans while moving. This implies predicting how people will move and complying with social conventions. Avoiding disrupting personal spaces, people’s paths and interactions are examples of these social conventio...
Chapter
Full-text available
Minimising the discomfort caused by robots when navigating in social situations is crucial for them to be accepted. Graph Neural Networks can process representations including arbitrarily complex relationships between entities such as human interactions. This is particularly interesting in the context of social navigation, where relational informat...
Preprint
Full-text available
Contemporary Artificial Intelligence technologies allow for the employment of Computer Vision to discern good crops from bad, providing a step in the pipeline of selecting healthy fruit from undesirable fruit, such as those which are mouldy or gangrenous. State-of-the-art works in the field report high accuracy results on small datasets (<1000 imag...
Preprint
Full-text available
Autonomous navigation is a key skill for assistive and service robots. To be successful, robots have to minimise the disruption caused to humans while moving. This implies predicting how people will move and complying with social conventions. Avoiding disrupting personal spaces, people's paths and interactions are examples of these social conventio...
Article
Full-text available
Objective The novelty of this study consists of the exploration of multiple new approaches of data pre-processing of brainwave signals, wherein statistical features are extracted and then formatted as visual images based on the order in which dimensionality reduction algorithms select them. This data is then treated as visual input for 2D and 3D CN...
Preprint
Full-text available
Minimising the discomfort caused by robots when navigating in social situations is crucial for them to be accepted. The paper presents a machine learning-based framework that bootstraps existing one-dimensional datasets to generate a cost map dataset and a model combining Graph Neural Network and Convolutional Neural Network layers to produce cost...
Chapter
Social navigation datasets are necessary to assess social navigation algorithms and train machine learning algorithms. Most of the currently available datasets target pedestrians’ movements as a pattern to be replicated by robots. It can be argued that one of the main reasons for this to happen is that compiling datasets where real robots are manua...
Chapter
Full-text available
Autonomous navigation is a key skill for assistive and service robots. To be successful, robots have to comply with social rules, such as avoiding the personal spaces of the people surrounding them, or not getting in the way of human-to-human and human-to-object interactions. This paper suggests using Graph Neural Networks to model how inconvenient...
Preprint
Full-text available
Social navigation datasets are necessary to assess social navigation algorithms and train machine learning algorithms. Most of the currently available datasets target pedestrians' movements as a pattern to be replicated by robots. It can be argued that one of the main reasons for this to happen is that compiling datasets where real robots are manua...
Conference Paper
Estimating the location and orientation of humans is an essential skill for service and assistive robots. To achieve a reliable estimation in a wide area such as an apartment, multiple RGBD cameras are frequently used. Firstly, these setups are relatively expensive. Secondly, they seldom perform an effective data fusion using the multiple camera so...
Preprint
Full-text available
Estimating the location and orientation of humans is an essential skill for service and assistive robots. To achieve a reliable estimation in a wide area such as an apartment, multiple RGBD cameras are frequently used. Firstly, these setups are relatively expensive. Secondly, they seldom perform an effective data fusion using the multiple camera so...
Article
Full-text available
One of the aims of cognitive robotics is to endow robots with the ability to plan solutions for complex goals and then to enact those plans. Additionally, robots should react properly upon encountering unexpected changes in their environment that are not part of their planned course of actions. This requires a close coupling between deliberative an...
Article
Full-text available
Education is evolving to prepare students for the current sociotechnical changes. An increasing effort to introduce programming and other STEM-related subjects into the core curriculum of primary and secondary education is taking place around the world. The use of robots stands out among STEM initiatives, since robots are proving to be an engaging...
Article
Full-text available
Datasets are essential to the development and evaluation of machine learning and artificial intelligence algorithms. As new tasks are addressed, new datasets are required. Training algorithms for human-aware navigation is an example of this need. Different factors make designing and gathering data for human-aware navigation datasets challenging. Fi...
Chapter
Full-text available
Path planning is one of the most widely studied problems in robot navigation. It deals with estimating an optimal set of waypoints from an initial to a target coordinate. New generations of assistive robots should be able to compute these paths considering not only obstacles but also social conventions. This ability is commonly referred to as socia...
Article
Full-text available
Diabetes mellitus is a chronic disease defined as a state of hyperglycaemia in fasting or postprandial states. Patients with type 2 diabetes mellitus (T2DM) often show reduced physical function, including low levels of strength, balance or mobility. In this regard, the timed up and go (TUG) is a widely used physical fitness test in people with T2DM...
Preprint
Full-text available
Autonomous navigation is a key skill for assistive and service robots. To be successful, robots have to navigate avoiding going through the personal spaces of the people surrounding them. Complying with social rules such as not getting in the middle of human-to-human and human-to-object interactions is also important. This paper suggests using Grap...
Preprint
Full-text available
Adapting to social conventions is an unavoidable requirement for the acceptance of assistive and social robots. While the scientific community broadly accepts that assistive robots and social robot companions are unlikely to have widespread use in the near future, their presence in health-care and other medium-sized institutions is becoming a reali...
Preprint
Full-text available
This study suggests a new approach to EEG data classification by exploring the idea of using evolutionary computation to both select useful discriminative EEG features and optimise the topology of Artificial Neural Networks. An evolutionary algorithm is applied to select the most informative features from an initial set of 2550 EEG statistical feat...
Article
Objetivo: El Proyecto EuroAGE (Iniciativas innovadoras para el impulso del envejecimiento activo en la región EUROACE) plantea una red de laboratorios para el desarrollo de robots asistenciales en el hogar o en residencias geriátricas. El objetivo principal del proyecto es crear espacios colaborativos inteligentes entre los distintos participantes...
Article
Full-text available
Objetivo: La actividad física en los mayores juega un papel fundamental para mantener su salud física y mental, su calidad de vida y mantener su independencia. Dentro de la promoción de la actividad física, la tecnología juega un papel fundamental. Por ello, el objetivo de este trabajo ha sido el desarrollo y la validación preliminar de un ejercici...
Article
CORTEX is a cognitive robotics architecture inspired by three key ideas: modularity, internal modelling and graph representations. CORTEX is also a computational framework designed to support early forms of intelligence in human interacting robots by selecting, a priori, a functional decomposition of the capabilities of the robot. This set of abili...
Article
Full-text available
This study suggests a new approach to EEG data classification by exploring the idea of using evolutionary computation to both select useful discriminative EEG features and optimise the topology of Artificial Neural Networks. An evolutionary algorithm is applied to select the most informative features from an initial set of 2550 EEG statistical feat...
Article
Full-text available
The aim of the study was to build a low-cost mask-type eye tracker with accuracy and precision levels similar to those reported for commercial eye tracking devices. To this end, head-mounted hardware was designed and developed, while open-source software was modified for digital image capture, manipulation, and fixation analysis. An image recogniti...
Chapter
Full-text available
Navigation is one of the crucial skills autonomous robots need to perform daily tasks, and many of the rest depend on it. In this paper, we argue that this dependence goes both ways in advanced social autonomous robots. Manipulation, perception, and most importantly human-robot interaction are some of the skills in which navigation might rely on. T...
Chapter
Full-text available
The goal of the LifeBots project is the study and development of long-life mechanisms that facilitate and improve the integration of robotics platforms in smart homes to support elder and handicapped people. Specifically the system aims to design, build and validate an assistive ecosystem formed by a person living in a smart home with a social robo...
Conference Paper
Full-text available
This work aims to find discriminative EEG-based features and appropriate classification methods that can categorise brainwave patterns based on their level of activity or frequency for mental state recognition useful for human-machine interaction. By using the Muse headband with four EEG sensors (TP9, AF7, AF8, TP10), we categorised three possible...
Conference Paper
Full-text available
Emotion expression is a type of nonverbal communication (i.e. wordless cues) between people, where affect plays the role of interpersonal communication with information conveyed by facial and/or body expressions. Much can be understood about how people are feeling through their expressions, which are crucial for everyday communication and interacti...
Article
Full-text available
Traditionally robots are mostly known by society due to the wide use of manipulators, which are generally placed in controlled environments such as factories. However, with the advances in the area of mobile robotics, they are increasingly inserted into social contexts, i.e., in the presence of people. The adoption of socially acceptable behaviours...
Article
Full-text available
Obtaining good quality image features is of remarkable importance for most computer vision tasks. It has been demonstrated that the first layers of the human visual cortex are devoted to feature detection. The need for these features has made line, segment, and corner detection one of the most studied topics in computer vision. HT3D is a recent var...
Conference Paper
Full-text available
In the current state-of-the-art, social robots per-forming non-trivial tasks often spend most of their time finding and modeling objects. In this paper we present the extension of a cognitive architecture that reduces the time and effort a robot needs to retrieve objects in a household scenario. We upgrade our previous Passive Learning Sensor algor...
Conference Paper
Full-text available
Comprehensive Geriatric Assessment (CGA) is an integrated clinical process to evaluate the frailty of elderly persons in order to create therapy plans that improve their quality of life. For robotizing these tests, we are designing and developing CLARC, a mobile robot able to help the physician to capture and manage data during the CGA procedures,...
Chapter
Full-text available
Autonomous robots that are interfaced with virtual or augmented reality gaming are increasingly being developed to provide repetitive intensive practice to promote increased compliance and facilitate better outcomes in neurorehabilitation therapies. These therapist robots, equipped with a set of sensors and actuators for monitorizing the environmen...
Article
Full-text available
This paper presents a method to reduce the time spent by a robot with cognitive abilities when looking for objects in unknown locations. It describes how machine learning techniques can be used to decide which places should be inspected first, based on images that the robot acquires passively. The proposal is composed of two concurrent processes. T...
Article
Full-text available
The Hough Transform (HT) is an effective and popular technique for detecting image features such as lines and curves. From its standard form, numerous variants have emerged with the objective, in many cases, of extending the kind of image features that could be detected. Particularly, corner and line segment detection using HT has been separately a...
Article
Full-text available
Object detection and classification have countless applications in human–robot interacting systems. It is a necessary skill for autonomous robots that perform tasks in household scenarios. Despite the great advances in deep learning and computer vision, social robots performing non-trivial tasks usually spend most of their time finding and modeling...
Article
Full-text available
The choice of using a robotic architecture and one of its possible implementations is one of the most crucial design decisions when developing robots. Such decision affects the whole development process, the limitations of the robot, and changing minds can be prohibitively time consuming. This paper presents the redesign and the most relevant imple...
Poster
Full-text available
The Robotics Cognitive Architecture CORTEX is introduced along with two use cases where itis being applied.
Conference Paper
Full-text available
Collaboration is an essential feature of human social interaction. Briefly, when two or more people agree on a common goal and a joint intention to reach that goal, they have to coordinate their actions to engage in joint actions, planning their courses of actions according to the actions of the other partners. The same holds for teams where the pa...
Chapter
Full-text available
Enabling autonomous mobile manipulators to collaborate with people is a challenging research field with a wide range of applications. Collaboration means working with a partner to reach a common goal and it involves performing both, individual and joint actions, with her. Human-robot collaboration requires, at least, two conditions to be efficient:...
Chapter
Full-text available
Robot navigation and manipulation in partially known indoor environments is usually organized as two complementary activities, local displacement control and global path planning. Both activities have to be connected across different space and time scales in order to obtain a smooth and responsive system that follows the path and adapts to the unfo...