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Journal of Physical Agents
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This is an Open Access Journal

Open Access journal
ISSN (Print) 1888-0258
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Special Issue on Advances on Physical Agents 2016
- Authors: Antonio Bandera
  Pages: 1 - 2
  Abstract: The Workshop on Physical Agents is a forum for information and experience exchange in different areas regarding the concept of embodied agents, especially applied to the control and coordination of autonomous systems: robots, mobile robots, domotics, agents, industrial applications or complex systems. This special issue brings together a selection of revised and extended papers that were first presented at the XVII Workshop on Physical Agents (WAF’2016), which was held on June 16-17, 2016 at the School of Telecommunication Engineering and Information Technology of the University of Málaga (Spain).
  PubDate: 2017-07-04
  DOI: 10.14198/JoPha.2017.8.1.01
  Issue No: Vol. 8, No. 1 (2017)
3D object detection with deep learning
- Authors: Félix Escalona, Angel Rodriguez, Francisco Gomez-Donoso, Jesus Martinez-Gomez, Miguel Cazorla
  Pages: 3 - 10
  Abstract: Finding an appropriate environment representation is a crucial problem in robotics. 3D data has been recently used thanks to the advent of low cost RGB-D cameras. We propose a new way to represent a 3D map based on the information provided by an expert. Namely, the expert is the output of a Convolutional Neural Network trained with deep learning techniques. Relying on such information, we propose the generation of 3D maps using individual semantic labels, which are associated with environment objects or semantic labels. So, for each label we are provided with a partial 3D map whose data belong to the 3D perceptions, namely point clouds, which have an associated probability above a given threshold. The final map is obtained my registering and merging all these partial maps. The use of semantic labels provide us a with way to build the map while recognizing objects.
  PubDate: 2017-07-04
  DOI: 10.14198/JoPha.2017.8.1.02
  Issue No: Vol. 8, No. 1 (2017)
Orientation Estimation by Means of Extended Kalman Filter, Quaternions,
and Charts
- Authors: Pablo Bernal-Polo, Humberto Martínez-Barberá
  Pages: 11 - 24
  Abstract: In this paper, an orientation estimation algorithm is presented. This algorithm is based on the Extended Kalman Filter, and uses quaternions as the orientation descriptor. For the filter update, measures from an inertial measurement unit (IMU) are used. The IMU consists in a triaxial angular rate sensor, and an also triaxial accelerometer.Quaternions describing orientations live in the unit sphere of R^4. Knowing that this space is a manifold, and applying some basic concepts regarding these mathematical objects, an algorithm that reminds the also called ''Multiplicative Extended Kalman Filter'' arises in a natural way.The algorithm is tested in a simulated experiment, and in a real one.
  PubDate: 2017-07-04
  DOI: 10.14198/JoPha.2017.8.1.03
  Issue No: Vol. 8, No. 1 (2017)
Automatic Human Body Feature Extraction in Serious Games applied to
rehabilitation Robotics
- Authors: Pedro Núñez, Eva Mogena, José Luis González
  Pages: 25 - 32
  Abstract: Current modern society is characterized by an increasing level of elderly population. This population group is usually ligated to important physical and cognitive impairments, which implies that older people need the care, attention and supervision by health professionals. In this paper, a new system for supervising rehabilitation therapies using autonomous robots for elderly is presented. The therapy explained in this work is a modified version of the classical ’Simon Says’ game, where a robot executes a list of motions and gestures that the human has to repeat each time with a more level of difficulty. The success of this therapy from the point of view of the software is to provide from an algorithm that detect and classified the gestures that the human is imitating. The algorithm proposed in this paper is based on the analysis of sequences of images acquired by a low cost RGB-D sensor. A set of human body features is detected and characterized during the motion, allowing the robot to classify the different gestures. In addition, this paper describes the human-robot interaction performed by the ’Simon Says’ game implementation. Experimental results demonstrate the robustness and accuracy of the detection and classification method, which is crucial for the development of the therapy.
  PubDate: 2017-07-04
  DOI: 10.14198/JoPha.2017.8.1.04
  Issue No: Vol. 8, No. 1 (2017)
Use and advances in the Active Grammar-based Modeling architecture
- Authors: Luis Jesús Manso Fernández-Argüelles
  Pages: 33 - 38
  Abstract: 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 implementation issues of the Active Grammar-based Modeling architecture (AGM), as well as the latest developments thereof. AGM is flexible, modular and designed with computation distribution and scalability in mind. In addition to a continuous refactoring of the API library and planner, the most relevant improvements are an enhanced mission specification syntax, support for representations combining symbolic and metric properties, redesigned communication patterns, and extended middleware support.A few use examples are presented to demonstrate successful application of the architecture and why some of its features were needed.
  PubDate: 2017-07-04
  DOI: 10.14198/JoPha.2017.8.1.05
  Issue No: Vol. 8, No. 1 (2017)
Generation and control of locomotion patterns for biped robots by using
central pattern generators
- Authors: Julián Efrén Cristiano Rodríguez, Domènec Puig Valls, Miguel Angel García García
  Pages: 40 - 47
  Abstract: This paper presents an efficient closed-loop locomotion control system for biped robots that operates in the joint space. The robot’s joints are directly driven through control signals generated by a central pattern generator (CPG) network. A genetic algorithm is applied in order to find out an optimal combination of internal parameters of the CPG given a desired walking speed in straight line. Feedback signals generated by the robot’s inertial and force sensors are directly fed into the CPG in order to automatically adjust the locomotion pattern over uneven terrain and to deal with external perturbations in real time. Omnidirectional motion is achieved by controlling the pelvis motion. The performance of the proposed control system has been assessed through simulation experiments on a NAO humanoid robot.
  PubDate: 2017-07-04
  DOI: 10.14198/JoPha.2017.8.1.06
  Issue No: Vol. 8, No. 1 (2017)

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