Rackham: An Interactive Robot-Guide

International audienceRackham is an interactive robot-guide that has been used in several places and exhibitions. This paper presents its design and reports on results that have been obtained after its deployment in a permanent exhibition. The project is conducted so as to incrementally enhance the robot functional and decisional capabilities based on the observation of the interaction between the public and the robot. Besides robustness and efficiency in the robot navigation abilities in a dynamic environment, our focus was to develop and test a methodology to integrate human-robot interaction abilities in a systematic way. We first present the robot and some of its key design issues. Then, we discuss a number of lessons that we have drawn from its use in interaction with the public and how that will serve to refine our design choices and to enhance robot efficiency and acceptability

Techniques d'automatique et de traitement du signal pour l'asservissement visuel et la perception auditive en robotique

The work developed in this manuscript essentially deals with a set of functional primitives in Robotics, whose scientific foundations are anchored in Automatic Control and Signal Processing. Far more than an application domain of theories developed elsewhere, Robotics, through its specificities or its constraints, often questions the state of the art in Control or Signal Processing, or even requires nontrivial methodological extensions. The richness of the dialog between these three scientific areas guided our research. A first part of our work has been geared towards the development of a generic framework to the ''multicriteria'' analysis and synthesis of visual-based control schemes, i.e.\ which take into account constraints (visibility, actuators' saturations, 3D constraints during the motion, etc.). These problems have been turned into the stability analysis / stabilization of uncertain nonlinear rational systems subject to rational constraints. The underlying theoretical issues are Lyapunov stability and LMI optimization. By duality, visual-based localization has been tackled by robust set-membership filtering techniques for rational systems. A second contribution takes place within the relatively new area of Robot Audition. We have proposed low-level auditory functions for detection, localization and extraction of sound sources. An original integrated auditory sensor developed at LAAS-CNRS has enabled their implementation. The underlying theoretical issues are array processing (beamforming, high resolution methods) and LMI optimization. More recently, the foundations of a new approach to voice activity detection have been seet, on the basis of stochastic matched filtering. In parallel to these targeted developments, a groundwork in stochastic filtering and change detection got materialized into scientific collaborations within targeted application domains: sequential Monte Carlo and Quasi Monte Carlo methods for visual tracking of people / gestures and for visual human motion capture; change detection and IMM filtering with heterogeneous state space models for dynamic scene monitoring and ARGOS localization. Some of the above themes ''merge'' into some structuring axes of our future developments. A particular effort will concern active perception (viz.\ which exploits proprioception and motion) declined in the context of binaural audition, as well as the fusion of embedded and deported auditory functions in intelligent environments.Les travaux présentés dans ce manuscrit d'Habilitation à Diriger des Recherches concernent essentiellement un ensemble de primitives du niveau fonctionnel de la Robotique, dont les fondements scientifiques sont ancrés dans l'Automatique et le Traitement du Signal. Bien plus qu'un domaine d'application de théories développées par ailleurs, la Robotique, par ses spécificités ou ses contraintes, " questionne " souvent l'état de l'art en Automatique et Signal, voire exige des extensions méthodologiques non triviales. C'est la richesse du dialogue entre ces trois disciplines qui a constitué le fil conducteur principal de nos recherches. Un premier volet de nos travaux vise à développer un cadre générique pour l'analyse et la synthèse "multicritères" de commandes référencées vision, i.e. qui prennent en compte l'ensemble des contraintes (visibilité, saturations d'actionneurs, contraintes 3D pendant le déplacement, etc.). Ces problèmes sont ramenés à l'analyse en stabilité / la stabilisation de systèmes non linéaires incertains rationnels sous contraintes rationnelles. Le support théorique est la théorie de Lyapunov et l'optimisation LMI. Par dualité, la localisation visuelle est abordée par des techniques de filtrage ensembliste robuste de systèmes rationnels. Une deuxième contribution s'inscrit dans la thématique relativement récente de l'Audition en Robotique. Nous proposons des fonctions auditives bas-niveau pour la détection de sources sonores, leur localisation et leur extraction. Un capteur auditif intégré original conçu au LAAS-CNRS permet leur implémentation. Le support théorique est le traitement d'antenne (formation de voie, méthodes à haute résolution) et l'optimisation LMI. Plus récemment, nous avons posé les fondements d'une nouvelle approche pour la détection d'activité vocale, sur la base du filtrage adapté stochastique. En parallèle à ces développements ciblés, un travail de fond dans les thématiques du filtrage stochastique et de la détection de ruptures s'est matérialisé par des collaborations scientifiques dans des domaines d'application ciblés : méthodes séquentielles de Monte Carlo et Quasi Monte Carlo pour le suivi visuel de personnes, de gestes, et la capture de mouvement par vision ; détection de ruptures et filtrage IMM entre modèles d'état d'ordres hétérogènes pour la surveillance de scènes dynamiques et la localisation ARGOS. Certaines des thématiques exposées ci-dessus se " rejoignent " au sein des axes structurants de nos développements futurs. Un effort particulier concernera la perception active (i.e. exploitant la proprioception et le mouvement), déclinée dans le cadre de l'audition binaurale, ainsi que la fusion de données auditives embarquées et déportées dans des lieux intelligents

Broadband variations of the music high-resolution method for sound source localization in robotics

International audienceThe MUSIC algorithm (multiple signal classification) is a well-known high-resolution method to sound source localization. However, as it is essentially narrowband, several extensions can be envisaged when dealing with broadband sources like human voice. This paper presents such extensions and proposes a comparative study w.r.t. specific robotics constraints. An online beamspace MUSIC method, together with a recently developed beamforming scheme, are shown to constitute a mathematically sound and potentially efficient solution

Convex optimization and modal analysis for beamforming in robotics : théoretical and implementation issues

International audienceThis paper deals with sound source localization in mobile robotics. This context opens new areas of research as it involves some specific constraints such as real time performance or embeddability. Quite often, broadband beamforming techniques are sought for, exploiting small-sized microphone arrays. A new approach to the design of broadband nearfield or farfield beamformers is first described, based on modal analysis and convex optimization. Original considerations related to the involvement of the theoretical beam-pattern into the real integrated acoustic sensor are then presented, which lead to alleviate some constraints during the optimization process and enable the use of smaller arrays. The whole method is illustrated on an example

Low-Complexity IMM Smoothing for Jump Markov Nonlinear Systems

Pré-print, dernière versionInternational audienceA suboptimal algorithm to fixed-interval and fixed-lag smoothing for Markovian switching systems is proposed. It infers a Gaussian mixture approximation of the smoothing pdf by combining the statistics produced by an IMM filter into an original backward recursive process. The number of filters and smoothers is equal to the constant number of hypotheses in the posterior mixture. A comparison, conducted on simulated case studies, shows that the investigated method performs significantly better than equivalent algorithms

A Fixed-Interval Smoother with Reduced Complexity for Jump Markov Nonlinear Systems

International audienceA suboptimal algorithm to fixed-interval smoothing for nonlinear Markovian switching systems is proposed. It infers a Gaussian mixture approximation to the posterior smoothing pdf by combining the statistics produced by an IMM filter into an original backward recursive process. The complexity is limited, as the number of underlying filters and smoothers is equal to the constant number of hypotheses in the posterior mixture. A comparison, conducted on realistic simulated target tracking case studies, shows that the investigated method performs significantly better than equivalent algorithms

Multi-Step-Ahead Information-Based Feedback Control for Active Binaural Localization

International audienceBinaural sound localization is known to be improved by incorporating the movement of the sensor. "Active" schemes based on this paradigm can overcome conventional limitations such as front-back ambiguity and source range recovery. Starting from a Gaussian prior on the relative position of a source, this paper determines the motion of a binaural sensor which leads to the most effective path for localization. To this aim, a reward function is defined as the conditional expectation, over the yet unknown N next observations, of the entropy of the N-step-ahead posterior pdf of the relative source position. The optimal motion of the binaural sensor is obtained from a constrained optimization problem involving the automatic differentiation of the reward function. The method is validated in simulation, and is being implemented on a real-life robotic test bed

Hrtf-based source azimuth estimation and activity detection from a binaural sensor

International audienceA theoretically grounded scheme to Direction of Arrival (DOA) estimation and Source Activity Detection (SAD) is proposed, on the basis of a pair of microphones. The method can capture the effects of the robot's scatterers, if any. The DOA estimator takes place within a probabilistic framework and outputs the Maximum Likelihood Estimate (MLE) of the DOA with respect to the collected audio data. Besides, the SAD relies on statistical identification. The behavior of the estimator is studied under various operating modes, considering free-field propagation and scattering by a rigid spherical head. Experimental results validate the approach

Prototyping filter-sum beamformers for sound source localization in mobile robotics

International audienceThe work presented in this paper comes as a part of a project which aims at developing an auditory system for a mobile robot. It presents a sound source localization strategy which enables the sensing of signals within a direction of arrival and frequency domain of interest while rejecting other data. A rapid prototyping method is proposed to design filter-sum beamformers on the basis of convex optimization. This method is well-suited to robotics applications as it copes with real-time constraints and allows the localization of broadband signals such as human voice. Numerous simulation results are used to illustrate the reasoning

Acoustic models and kalman filtering strategies for active binaural sound localization

International audienceThis paper deals with binaural sound localization. An active strategy is proposed, relying on a precise model of the dynamic changes induced by motion on the auditive perception. The proposed framework allows motions of both the sound source and the sensor. The resulting stochastic discrete-time model is then exploited together with Unscented Kalman filtering to provide range and azimuth estimation. Simulations and experiments show the effectiveness of the method