Aural Servo: Sensor-Based Control From Robot Audition

Magassouba, Aly; Bertin, Nancy; Chaumette, François

doi:10.1109/tro.2018.2805310

Cited by 10 publications

(4 citation statements)

References 27 publications

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“…Juang et al [64] developed a line follower which was able to infer forward, lateral and angular velocity commands using path curvature estimation and PID control from monocular RGB images. Magassouba et al [65] introduced an aural servo framework based on auditory perception, enabling robot motions to be directly linked to lowlevel auditory features through a feedback loop.…”

Section: Local Planningmentioning

confidence: 99%

Perception for Humanoid Robots

Roychoudhury,

Khorshidi,

Agrawal

et al. 2023

Curr Robot Rep

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Purpose of Review The field of humanoid robotics, perception plays a fundamental role in enabling robots to interact seamlessly with humans and their surroundings, leading to improved safety, efficiency, and user experience. This scientific study investigates various perception modalities and techniques employed in humanoid robots, including visual, auditory, and tactile sensing by exploring recent state-of-the-art approaches for perceiving and understanding the internal state, the environment, objects, and human activities. Recent Findings Internal state estimation makes extensive use of Bayesian filtering methods and optimization techniques based on maximum a-posteriori formulation by utilizing proprioceptive sensing. In the area of external environment understanding, with an emphasis on robustness and adaptability to dynamic, unforeseen environmental changes, the new slew of research discussed in this study have focused largely on multi-sensor fusion and machine learning in contrast to the use of hand-crafted, rule-based systems. Human robot interaction methods have established the importance of contextual information representation and memory for understanding human intentions. Summary This review summarizes the recent developments and trends in the field of perception in humanoid robots. Three main areas of application are identified, namely, internal state estimation, external environment estimation, and human robot interaction. The applications of diverse sensor modalities in each of these areas are considered and recent significant works are discussed.

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Section: Local Planningmentioning

confidence: 99%

Perception for Humanoid Robots

Roychoudhury,

Khorshidi,

Agrawal

et al. 2023

Curr Robot Rep

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“…This work is motivated by recent studies on binaural localizations for indoor environments that utilized ITD in a 3D space [ 40 ], both ILD and ITD [ 41 ] in a 2D space, and DRR for distance estimation of up to 3 m [ 42 ]. The aforementioned literatures however did not use pinnae for front-rear disambiguation, hence requiring either a servo system to integrate rotational and translational movements of the receiver or other algorithms to solve for unobservable states in the front-rear confusion areas until the source can be correctly localized.…”

Section: Introductionmentioning

confidence: 99%

Binaural Modelling and Spatial Auditory Cue Analysis of 3D-Printed Ears

Ting

Ahmad

Goh

et al. 2021

Sensors

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In this work, a binaural model resembling the human auditory system was built using a pair of three-dimensional (3D)-printed ears to localize a sound source in both vertical and horizontal directions. An analysis on the proposed model was firstly conducted to study the correlations between the spatial auditory cues and the 3D polar coordinate of the source. Apart from the estimation techniques via interaural and spectral cues, the property from the combined direct and reverberant energy decay curve is also introduced as part of the localization strategy. The preliminary analysis reveals that the latter provides a much more accurate distance estimation when compared to approximations via sound pressure level approach, but is alone not sufficient to disambiguate the front-rear confusions. For vertical localization, it is also shown that the elevation angle can be robustly encoded through the spectral notches. By analysing the strengths and shortcomings of each estimation method, a new algorithm is formulated to localize the sound source which is also further improved by cross-correlating the interaural and spectral cues. The proposed technique has been validated via a series of experiments where the sound source was randomly placed at 30 different locations in an outdoor environment up to a distance of 19 m. Based on the experimental and numerical evaluations, the localization performance has been significantly improved with an average error of 0.5 m from the distance estimation and a considerable reduction of total ambiguous points to 3.3%.

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“…In the last few years, many SSRL algorithms have been applied to intelligent robots. [1][2][3] Confronted with sound recognition, frequency domain analysis is frequently adopted. 4 Detected principal frequency components are classified to predefined frequency domain space to determine whether it is the certain audio type.…”

Section: Introductionmentioning

confidence: 99%

Efficient and robust approaches for three-dimensional sound source recognition and localization using humanoid robots sensor arrays

Chen

Liu

Chen

2020

International Journal of Advanced Robotic Systems

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Efficient and robust sound source recognition and localization is one of the basic techniques for humanoid robots in terms of reaction to environments. Due to the fixed sensor arrays and limited computation resources in humanoid robots, there comes challenge for sound source recognition and localization. This article proposes a sound source recognition and localization framework to realize real-time and precise sound source recognition and localization system using humanoid robots’ sensor arrays. The type of the audio is recognized according to the cross-correlation function. And steered response power-phase transform function in discrete angle space is used to search the sound source direction. The sound source recognition and localization framework presents a new multi-robots collaboration system to get the precise three-dimensional sound source position and introduces a distance weighting revision way to optimize the localization performance. Additionally, the experiment results carried out on humanoid robot NAO demonstrate that the proposed approaches can recognize and localize the sound source efficiently and robustly.

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Aural Servo: Sensor-Based Control From Robot Audition

Cited by 10 publications

References 27 publications

Perception for Humanoid Robots

Perception for Humanoid Robots

Binaural Modelling and Spatial Auditory Cue Analysis of 3D-Printed Ears

Efficient and robust approaches for three-dimensional sound source recognition and localization using humanoid robots sensor arrays

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