Papers by Michail G Lagoudakis
IEEE Transactions on Instrumentation and Measurement, 2010
Today's technology allows the construction of complex experimental apparatus with reasonable budg... more Today's technology allows the construction of complex experimental apparatus with reasonable budget. This paper supplies detailed guidelines for constructing a low-cost scaled automobile platform for research and education in vehicle dynamics and control. It summarizes the knowledge gathered when designing, building, and evaluating a model car, which was deployed in a real-world environment for testing an electronic stability control (ESC) algorithm. The model car was built using off-the-shelf hardware and open-source software. Data from a variety of onboard sensors are fused in real time so as to deliver accurate measurements to the ESC algorithm, whereas sensor fault diagnosis is achieved at the same time through an innovative approach based on artificial neural networks (NNs). The detailed presentation of this case study provides a roadmap on how a researcher can build effective experimental automotive platforms for research and educational purposes.
Journal of Intelligent and Robotic Systems, Jan 31, 2014
Articulated robots with multiple degrees of freedom, such as humanoid robots, have become popular... more Articulated robots with multiple degrees of freedom, such as humanoid robots, have become popular research platforms in robotics and artificial intelligence. Such robots can perform complex motions, including the balancing, walking, and kicking skills required in the RoboCup robot soccer competition. The design of complex dynamic motions is achievable only through the use of robot kinematics, which is an application of geometry to the study of arbitrary robotic chains. This thesis studies the problems of forward and inverse kinematics for the Aldebaran NAO humanoid robot and presents for the first time a complete analytical solution to both problems with no approximations, including an implementation of a software library for real-time execution. The forward kinematics allow NAO developers to map any configuration of the robot from its own joint space to the three-dimensional physical space, whereas the inverse kinematics provide closedform solutions to finding joint configurations that drive the end effectors of the robot to desired points in the three-dimensional space. The proposed solution was made feasible through a decomposition into five independent problems (head, two arms, two legs), the use of the Denavit-Hartenberg method, and the analytical solution of a non-linear system of equations. The main advantage of the proposed inverse kinematics compared to existing numerical approaches is its accuracy, its efficiency, and the elimination of singularities. The implemented NAO kinematics library, which additionally offers centerof-mass calculation, is demonstrated in two motion design tasks: pointing to the ball and basic balancing. The library has been integrated into the software architecture of the RoboCup team "Kouretes" and is currently being used in various motion design problems, such as dynamic balancing, trajectory following, dynamic kicking, and omnidirectional walking. First of all, I would like to thank Manolis Orf (a.k.a. "re palikari") for his help and his great ideas as well as for the great fights we had. Next, I would like to thank my advisor Michail G. Lagoudakis for his inspiration and the trust that he showed in me. Fanoula is the next person that I would like to thank¨. She helped me so much during this difficult period and I am so lucky that she still talks to me. Team Kouretes (N. Pav, A. Top, M. Kounoupidi, D. Janetatou, Orf, Iris), I can't understand why you still talk to me after all the things we've been through together in "ypoga". After all, I like this team and our lab more than I had imagined; thank you for your help and all the fun in the team. To sum up, I would like to thank my friends with whom I had the greatest five years of my life. N. Pavlakis (he paid five Euros for the second reference), E. Alimpertis, K.
Lecture Notes in Computer Science, 2010
arXiv (Cornell University), Dec 12, 2012
This paper investigates value function approx imation in the context of zero-sum Markov games, wh... more This paper investigates value function approx imation in the context of zero-sum Markov games, which can be viewed as a generalization of the Markov decision process (MDP) frame work to the two-agent case. We generalize er ror bounds from MDPs to Markov games and describe generalizations of reinforcement learn ing algorithms to Markov games. We present a generalization of the optimal stopping prob lem to a two-player simultaneous move Markov game. For this special problem, we provide stronger bounds and can guarantee convergence for LSTD and temporal difference learning with linear value function approximation. We demon strate the viability of value function approxima tion for Markov games by using the Least squares policy iteration (LSPI) algorithm to learn good policies for a soccer domain and a flow control problem.
The design of complex dynamic motions for humanoid robots is achievable only through the use of r... more The design of complex dynamic motions for humanoid robots is achievable only through the use of robot kinematics. In this paper, we study the problems of forward and inverse kinematics for the Aldebaran NAO humanoid robot and present a complete, exact, analytical solution to both problems, including a software library implementation for realtime onboard execution. The forward kinematics allow NAO developers to map any configuration of the robot from its own joint space to the three-dimensional physical space, whereas the inverse kinematics provide closed-form solutions to finding joint configurations that drive the end effectors of the robot to desired target positions in the three-dimensional physical space. The proposed solution was made feasible through a decomposition into five independent problems (head, two arms, two legs), the use of the Denavit-Hartenberg method, and the analytical solution of a non-linear system of equations. The main advantage of the proposed inverse kinematics solution compared to existing approaches is its accuracy, its efficiency, and the elimination of singularities. In addition, we suggest a generic guideline for solving the inverse kinematics problem for other humanoid robots. The implemented, freely-available, NAO kinematics library, which additionally offers center-of-mass calculations, is demonstrated in two motion design tasks: basic center-of-mass balancing and pointing to the ball.
Ai Magazine, Dec 15, 2006
Service-oriented computing is an emerging computing paradigm for distributed systems that advocat... more Service-oriented computing is an emerging computing paradigm for distributed systems that advocates web-based interfaces for the distributed business processes of any enterprise. The interfaces, called web services, hold the promise for diluting the traditional challenges of interoperability, inflexibility, and performance that have long plagued traditional distributed systems. Web services research represents an emerging application test bed with its own distinct challenges and presents an opportunity for AI techniques to enter and affect this emerging area.
The Lancet, 2004
First, Das and colleagues considered only variables with ap value ≤0·05 in univariate analysis fo... more First, Das and colleagues considered only variables with ap value ≤0·05 in univariate analysis for inclusion in the MLR models. However, it is generally recommended that all variables with ap value of 0·25 in univariate analysis, or those regarded as being clinically important, ...
Lecture Notes in Computer Science, 2010
2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), Dec 1, 2019
Statistical Dialogue Systems (SDS) have proved their humongous potential over the past few years.... more Statistical Dialogue Systems (SDS) have proved their humongous potential over the past few years. However, the lack of efficient and robust representations of the belief state (BS) space refrains them from revealing their full potential. There is a great need for automatic BS representations, which will replace the old hand-crafted, variable-length ones. To tackle those problems, we introduce a novel use of Autoencoders (AEs). Our goal is to obtain a low-dimensional, fixed-length, and compact, yet robust representation of the BS space. We investigate the use of dense AE, Denoising AE (DAE) and Variational Denoising AE (VDAE), which we combine with GP-SARSA to learn dialogue policies in the PyDial toolkit. In this framework, the BS is normally represented in a relatively compact, but still redundant summary space which is obtained through a heuristic mapping of the original master space. We show that all the proposed AE-based representations consistently outperform the summary BS representation. Especially, as the Semantic Error Rate (SER) increases, the DAE/VDAE-based representations obtain state-of-the-art and sample efficient performance.
BHM Berg- und Hüttenmännische Monatshefte
The United Nations Sustainable Development Goal 12 is the foundation of the European University o... more The United Nations Sustainable Development Goal 12 is the foundation of the European University on Responsible Consumption and Production consortium (EURECA-PRO). This article introduces the eight EURECA-PRO partner universities: Montanuniversität Leoben (Austria), Technische Universität Bergakademie Freiberg (Germany), Technical University of Crete (Greece), University of León (Spain), Silesian University of Technology (Poland), Mittweida University of Applied Sciences (Germany), University of Petroşani (Romania), and Hasselt University (Belgium). In addition, each university’s role within the alliance and unique research and study programmes are outlined. The synergy created by EURECA-PRO enables the pursuit of an ambitious research agenda with five research “Lighthouse Missions” as well as the implementation of joint study programmes.
maida©cacs, usl. edu Neural maps have been recently proposed as an alter-native method for mobile... more maida©cacs, usl. edu Neural maps have been recently proposed as an alter-native method for mobile robot path planning (Glasius, Komoda, and Gielen 1995). However, these proposals are mostly theoretical and are primarily concerned with biological plausibility. Our purpose is to investigate their applicability on real robots. Information about the environment is mapped on a topologically ordered neural population. The diffusion dynamics force the network into a unique equilibrium state that defines the navigation landscape for the given target. A path from any initial position to the target (corresponding to the peak of the activation surface) is derived by a steepest ascent procedure. The figures below show an example on a 50 x 50 rectangular map (a. Environment, b. Contours of activation, c. Path). We attempted to implement the approach on a No-mad 200 mobile robot for sonar-based navigation. How-ever, we found that the neural map requires reorgani-zation in a polar topology that re...
decision support system to facilitate management of patients with acute gastrointestinal bleeding.
Planning has been one of the main research areas in AI. For about three decades AI researchers ex... more Planning has been one of the main research areas in AI. For about three decades AI researchers explore alternative paths to build intelligent agents with advanced planning capabilities. However, the classical AI planning techniques suffer from inapplicability to real world domains, due to several assumptions adopted to facilitate research. Attempts to apply planning into real domains must address the problem of uncertainty, which requires a revision of the classical planning framework. Probabilistic models seem to offer a promising alternative, providing models of planning where plans can be represented, generated and evaluated under a standard probabilistic interpretation of uncertainty. This survey paper 1 attempts to cover the recent work in this direction and trigger the interest of the reader for further study and exploration.
Planning has been one of the main research areas in AI. For about three decades AI researchers ex... more Planning has been one of the main research areas in AI. For about three decades AI researchers explore alternative paths to build intelligent agents with advanced planning capabilities. However, the classical AI planning techniques suffer from inapplicability to real world domains, due to several assumptions adopted to facilitate research. Attempts to apply planning into real domains must address the problem of uncertainty, which requires a revision of the classical planning framework. Probabilistic models seem to offer a promising alternative, providing models of planning where plans can be represented, generated and evaluated under a standard probabilistic interpretation of uncertainty. This survey paper 1 attempts to cover the recent work in this direction and trigger the interest of the reader for further study and exploration.
The Lancet, 2004
First, Das and colleagues considered only variables with ap value ≤0·05 in univariate analysis fo... more First, Das and colleagues considered only variables with ap value ≤0·05 in univariate analysis for inclusion in the MLR models. However, it is generally recommended that all variables with ap value of 0·25 in univariate analysis, or those regarded as being clinically important, ...
The Spare Allocation problem (or equivalently Vertex Cover in bipartite graphs) deals with the op... more The Spare Allocation problem (or equivalently Vertex Cover in bipartite graphs) deals with the optimal allocation of spare rows and columns over a two-dimensional array of cells, some of which are faulty. The purpose is to repair all the faulty cells using spares with the minimum possible overall cost. In order to solve the problem optimally, a branch and bound algorithm is employed. Several heuristics for pruning the search tree and a heuristic that estimates the final cost from partial solutions are used to inform and guide the search procedure, leading to an effective A* search algorithm. However, memory limitations on one hand and the good enough quality of the heuristic function that low bounds the cost, on the other, force an Iterative Deepening implementation of the algorithm (IDA * ). Moving in the parallel implementation, many complications arise. A * is by its nature sequential and attempts to parallelize it, led to an amount of redundant search and/or early memory overflows. IDA * provides for parallelism, but work balancing issues should be addressed carefully. The final parallel IDA * search algorithm is scalable and leads to a significant amount of speedup, as demonstrated by the experimental results.
BHM Berg- und Hüttenmännische Monatshefte
Academia has entered a new teaching, learning, and researching era: an era in which more and more... more Academia has entered a new teaching, learning, and researching era: an era in which more and more services turn to digital and online forms, distances are eliminated, geographical borders disappear, and telepresence becomes common. Though accelerated by the pandemic of the last two years, this transition has been in progress for some time. The importance of creatively nurturing students, academic, and scientific staff in the realms of education, practical knowledge, skills, and competence growth has only increased. Investing in best practices in this digital world, both in teaching and in research, supports a connection between the academic world and society at large, raises societal, environmental awareness, and promotes innovation and excellence at all levels. Each of these considerations plays an important role for the EURECA-PRO European University Alliance, a group of eight partner universities from different European countries working together to establish a modern, diverse Eu...
Drones
Uncrewed aerial vehicles (UAVs) are continuously gaining popularity in a wide spectrum of applica... more Uncrewed aerial vehicles (UAVs) are continuously gaining popularity in a wide spectrum of applications, while their positioning and navigation most often relies on Global Navigation Satellite Systems (GNSS). However, numerous conditions and practices require UAV operation in GNSS-denied environments, including confined spaces, urban canyons, vegetated areas and indoor places. For the purposes of this study, an integrated UAV navigation system was designed and implemented which utilizes GNSS, visual, depth and inertial data to provide real-time localization. The implementation is built as a package for the Robotic Operation System (ROS) environment to allow ease of integration in various systems. The system can be autonomously adjusted to the flight environment, providing spatial awareness to the aircraft. This system expands the functionality of UAVs, as it enables navigation even in GNSS-denied environments. This integrated positional system provides the means to support fully auto...
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Papers by Michail G Lagoudakis