Author Archives: Juan-antonio Fernández-madrigal

A practical example of mobile robot long term operation

September 14, 2017 08:53 ,

N. Hawes et al., The STRANDS Project: Long-Term Autonomy in Everyday Environments, IEEE Robotics & Automation Magazine, vol. 24, no. 3, pp. 146-156, DOI: 10.1109/MRA.2016.2636359.

Thanks to the efforts of the robotics and autonomous systems community, the myriad applications and capacities of robots are ever increasing. There is increasing demand from end users for autonomous service robots that can operate in real environments for extended periods. In the Spatiotemporal Representations and Activities for Cognitive Control in Long-Term Scenarios (STRANDS) project (http://strandsproject.eu), we are tackling this demand head-on by integrating state-of-the-art artificial intelligence and robotics research into mobile service robots and deploying these systems for long-term installations in security and care environments. Our robots have been operational for a combined duration of 104 days over four deployments, autonomously performing end-user-defined tasks and traversing 116 km in the process. In this article, we describe the approach we used to enable long-term autonomous operation in everyday environments and how our robots are able to use their long run times to improve their own performance.

Posted in: Robot applications , Tagged:

An application of POMDPs to robot surveillance

September 14, 2017 08:47 ,

S. Witwicki et al., Autonomous Surveillance Robots: A Decision-Making Framework for Networked Muiltiagent Systems, IEEE Robotics & Automation Magazine, vol. 24, no. 3, pp. 52-64, DOI: 10.1109/MRA.2017.2662222.

This article proposes an architecture for an intelligent surveillance system, where the aim is to mitigate the burden on humans in conventional surveillance systems by incorporating intelligent interfaces, computer vision, and autonomous mobile robots. Central to the intelligent surveillance system is the application of research into planning and decision making in this novel context. In this article, we describe the robot surveillance decision problem and explain how the integration of components in our system supports fully automated decision making. Several concrete scenarios deployed in real surveillance environments exemplify both the flexibility of our system to experiment with different representations and algorithms and the portability of our system into a variety of problem contexts. Moreover, these scenarios demonstrate how planning enables robots to effectively balance surveillance objectives, autonomously performing the job of human patrols and responders.

Posted in: Robot applications, Robot task planning , Tagged: , ,

Interesting approach to learning the sensorimotor behavior of a robot and of its predictive capabilities through NN

September 14, 2017 08:38 ,

R. Santos, R. Ferreira, Â. Cardoso and A. Bernardino, SNet: Co-Developing Artificial Retinas and Predictive Internal Models for Real Robots, IEEE Transactions on Cognitive and Developmental Systems, vol. 9, no. 3, pp. 213-222, DOI: 10.1109/TCDS.2016.2638885.

This paper focuses on a recently developed biologically inspired architecture, here denoted as sensorimotor network (SNet), able to co-develop sensorimotor structures directly from data acquired by a robot interacting with its environment. Such networks learn efficient internal models of the sensorimotor system, developing simultaneously sensor and motor representations as well as predictive models of the sensorimotor relationships adapted to their operating environment. Here, we describe our recent model of sensorimotor development and compare its performance with neural network models in predicting self-induced stimuli. In addition, we illustrate the influence of available resources and environment characteristics in the development of the SNet structures. Finally, an SNet is trained using real data recorded during a quadricopter drone flight.

Posted in: Developmental robotics , Tagged: ,

A new method to obtain WCET from binary code and to analyze the execution paths

September 3, 2017 08:25 ,

Thomas Sewell, Felix KamGernot Heiser, High-assurance timing analysis for a high-assurance real-time operating system, Real-Time Systems, Volume 53, Issue 5, pp 812–853, DOI: 10.1007/s1124.

Worst-case execution time (WCET) analysis of real-time code needs to be performed on the executable binary code for soundness. Obtaining tight WCET bounds requires determination of loop bounds and elimination of infeasible paths. The binary code, however, lacks information necessary to determine these bounds. This information is usually provided through manual intervention, or preserved in the binary by a specially modified compiler. We propose an alternative approach, using an existing translation-validation framework, to enable high-assurance, automatic determination of loop bounds and infeasible paths. We show that this approach automatically determines all loop bounds and many (possibly all) infeasible paths in the seL4 microkernel, as well as in standard WCET benchmarks which are in the language subset of our C parser. We also design and validate an improvement to the seL4 implementation, which permits a key part of the kernel’s API to be available to users in a mixed-criticality setting.

Posted in: Real-Time Systems , Tagged: ,

Evidence of the dicotomy reactive/predictive control in the brain

August 26, 2017 11:45 ,

Mattie Tops, Markus Quirin, Maarten A.S. Boksem, Sander L. Koole, Large-scale neural networks and the lateralization of motivation and emotion, International Journal of Psychophysiology, Volume 119, 2017, Pages 41-49, DOI: 10.1016/j.ijpsycho.2017.02.004.

Several lines of research in animals and humans converge on the distinction between two basic large-scale brain networks of self-regulation, giving rise to predictive and reactive control systems (PARCS). Predictive (internally-driven) and reactive (externally-guided) control are supported by dorsal versus ventral corticolimbic systems, respectively. Based on extant empirical evidence, we demonstrate how the PARCS produce frontal laterality effects in emotion and motivation. In addition, we explain how this framework gives rise to individual differences in appraising and coping with challenges. PARCS theory integrates separate fields of research, such as research on the motivational correlates of affect, EEG frontal alpha power asymmetry and implicit affective priming effects on cardiovascular indicators of effort during cognitive task performance. Across these different paradigms, converging evidence points to a qualitative motivational division between, on the one hand, angry and happy emotions, and, on the other hand, sad and fearful emotions. PARCS suggests that those two pairs of emotions are associated with predictive and reactive control, respectively. PARCS theory may thus generate important new insights on the motivational and emotional dynamics that drive autonomic and homeostatic control processes.

Posted in: Psycho-physiological bases of engineering , Tagged: , ,

Chaos theory for modeling behavior of mobile robots that solve tasks evolutionarily

August 26, 2017 08:09 ,

Federico Da Rold, Chaotic analysis of embodied and situated agents, Robotics and Autonomous Systems, Volume 95, 2017, Pages 143-159, DOI: 10.1016/j.robot.2017.06.004.

Embodied and situated view of cognition is a transdisciplinary framework which stresses the importance of real time and dynamical interaction of an agent with the surrounding environment. This article presents a series of evolutionary robotics experiments that operationalize such concept, training miniature two-wheeled mobile robots to autonomously solve a temporal task. In order to provide a numerical description of the robots’ behavior, chaotic measures are estimated on the attractor reconstructed from the recorded positions of the agent. Chaos theory provides a rigorous mathematical framework consistent with an antireductionist approach, useful for understanding embodied and situated systems while avoiding a decomposition of the integrated system brain–body–environment. Time series are analyzed in detail using nonlinear mathematical tools in order to verify the presence of low-dimensional deterministic dynamical systems, a fundamental prerequisite for chaos theory. In particular, the recorded time series are evaluated with nonlinear prediction error to unveil deterministic dynamics, cross-prediction error to determine the stationarity of the signal, and surrogate data testing to verify the existence of nonlinear components in the underlying system. Estimators for quantifying level of chaos and fractal dimension are applied to suitable datasets. Results show that robots governed by a chaotic dynamic are more efficient at adapting to environments never experience during evolution, demonstrating robustness towards novel and unpredictable situations. Furthermore, chaotic measures, in particular fractal dimension, are correlated with the performance if robots exhibit a similar behavioral strategy.

Posted in: Developmental robotics , Tagged: , ,

Improving orientation estimation in a mobile robot for doing better odometry

August 26, 2017 08:05 ,

M.T. Sabet, H.R. Mohammadi Daniali, A.R. Fathi, E. Alizadeh, Experimental analysis of a low-cost dead reckoning navigation system for a land vehicle using a robust AHRS, Robotics and Autonomous Systems, Volume 95, 2017, Pages 37-51, DOI: 10.1016/j.robot.2017.05.010.

In navigation and motion control of an autonomous vehicle, estimation of attitude and heading is an important issue especially when the localization sensors such as GPS are not available and the vehicle is navigated by the dead reckoning (DR) strategies. In this paper, based on a new modeling framework an Extended Kalman Filter (EKF) is utilized for estimation of attitude, heading and gyroscope sensor bias using a low-cost MEMS inertial sensor. The algorithm is developed for accurate estimation of attitude and heading in the presence of external disturbances including external body accelerations and magnetic disturbances. In this study using the proposed attitude and heading reference system (AHRS) and an odometer sensor, a low-cost aided DR navigation system has been designed. The proposed algorithm application is evaluated by experimental tests in different acceleration bound and existence of external magnetic disturbances for a land vehicle. The results indicate that the roll, pitch and heading are estimated by mean value errors about 0.83%, 0.68% and 1.13%, respectively. Moreover, they indicate that a relative navigation error about 3% of the traveling distance can be achieved using the developed approach in during GPS outages.

Posted in: Mobile Robot Localization, Robot sensors , Tagged: ,

On how the simplification on physics made in computer games for real-time execution can explain the simplification on physics made by infants when understanding the world

August 17, 2017 11:39 ,

Tomer D. Ullman, Elizabeth Spelke, Peter Battaglia, Joshua B. Tenenbaum, Mind Games: Game Engines as an Architecture for Intuitive Physics, Trends in Cognitive Sciences, Volume 21, Issue 9, 2017, Pages 649-665, DOI: 10.1016/j.tics.2017.05.012.

We explore the hypothesis that many intuitive physical inferences are based on a mental physics engine that is analogous in many ways to the machine physics engines used in building interactive video games. We describe the key features of game physics engines and their parallels in human mental representation, focusing especially on the intuitive physics of young infants where the hypothesis helps to unify many classic and otherwise puzzling phenomena, and may provide the basis for a computational account of how the physical knowledge of infants develops. This hypothesis also explains several ‘physics illusions’, and helps to inform the development of artificial intelligence (AI) systems with more human-like common sense.

Posted in: Probability and statistics, Psycho-physiological bases of engineering , Tagged:

Optimization algorithms inspired in chemical reactions

August 15, 2017 10:18 ,

Nazmul Siddique, Hojjat Adeli, Nature-Inspired Chemical Reaction Optimisation Algorithms, Cognitive Computation, Volume 9, Issue 4, pp 411–422, DOI: 10.1007/s12559-017-9485-1.

Nature-inspired meta-heuristic algorithms have dominated the scientific literature in the areas of machine learning and cognitive computing paradigm in the last three decades. Chemical reaction optimisation (CRO) is a population-based meta-heuristic algorithm based on the principles of chemical reaction. A chemical reaction is seen as a process of transforming the reactants (or molecules) through a sequence of reactions into products. This process of transformation is implemented in the CRO algorithm to solve optimisation problems. This article starts with an overview of the chemical reactions and how it is applied to the optimisation problem. A review of CRO and its variants is presented in the paper. Guidelines from the literature on the effective choice of CRO parameters for solution of optimisation problems are summarised.

Posted in: Uncategorized , Tagged: ,

Identification of beacons for localization by using LEDs with light patterns as IDs

August 10, 2017 10:10 ,

G. Simon, G. Zachár and G. Vakulya, Lookup: Robust and Accurate Indoor Localization Using Visible Light Communication, IEEE Transactions on Instrumentation and Measurement, vol. 66, no. 9, pp. 2337-2348, DOI: 10.1109/TIM.2017.2707878.

A novel indoor localization system is presented, where LED beacons are utilized to determine the position of the target sensor, including a camera, an inclinometer, and a magnetometer. The beacons, which can be a part of the existing lighting infrastructure, transmit their identifiers for long distances using visible light communication techniques. The sensor is able to sense and detect the high-frequency (flicker free) code by properly undersampling the transmitted signal. The localization is performed using novel geometric and consensus-based techniques, which tolerate well measurement inaccuracies and sporadic outliers. The performance of the system is analyzed using simulations and real measurements. According to large-scale tests in realistic environments, the accuracy of the proposed system is in the low decimeter range.

Posted in: Mobile Robot Localization , Tagged: ,