Three ring microphone array for 3D sound localization and separation for mobile robot audition

Tamai, Y.; Sasaki, Yoko; Kagami, Satoshi; Mizoguchi, Hiroshi

doi:10.1109/iros.2005.1545095

Cited by 44 publications

(27 citation statements)

References 2 publications

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“…Pinpointing the actual location of the helicopter requires the direction as well as the distance to it. Determining the distance to a sound source without knowledge about its loudness is a challenging task [14], [7].…”

Section: A Initial Tests and Resultsmentioning

confidence: 99%

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Managing uncertainty in sound based control for an autonomous helicopter

Passow

Góngora

Smith

et al. 2009

2009 IEEE Workshop on Computational Intelligence in Vehicles and Vehicular Systems

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Abstract-In this paper we present our ongoing research using a multi-purpose, small and low cost autonomous helicopter platform (Flyper). We are building on previously achieved stable control using evolutionary tuning. We propose a sound based supervised method to localise the indoor helicopter and extract meaningful information to enable the helicopter to further stabilise its flight and correct its flightpath. Due to the high amount of uncertainty in the data, we propose the use of fuzzy logic in the signal processing of the sound signature. We discuss the benefits and difficulties using type-1 and type-2 fuzzy logic in this real-time systems and give an overview of our proposed system.

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Section: A Initial Tests and Resultsmentioning

confidence: 99%

“…For full localisation the distance to the sound source also needs to be determined. Other work shows distance estimation to unknown sound sources to be a challenging task where little accuracy is obtained [14], [7].…”

Section: B Sound Analysismentioning

confidence: 99%

Managing uncertainty in sound based control for an autonomous helicopter

Passow

Góngora

Smith

et al. 2009

2009 IEEE Workshop on Computational Intelligence in Vehicles and Vehicular Systems

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“…For this reason, less computationally expensive methods are usually used in audition systems for mobile robots. For example, a delay and sum beamforming is a common method for sound sources localization [47,48]. In the sound localization systems, based on the beamforming approach, microphone arrays are steered to multiple directions and the maxima of output signal energy are then searched.…”

Section: Sound Source Localization With a Microphone Arraymentioning

confidence: 99%

Designing a socially integrated mobile robot for ethological research

Gribovskiy

Halloy

Deneubourg

et al. 2018

Robotics and Autonomous Systems

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A robot introduced into an animal group, accepted by the animals as conspecifics, and capable of interacting with them is a very efficient tool for ethological research, particularly in studies of collective and social behavior. In this paper, we present the implementation of an autonomous mobile robot developed by the authors to study group behavior of chicks of the domestic chicken (Gallus gallus domesticus). We discuss the design of the robot and of the experimental setup that we built to run animal-robot experiments. The robot design was experimentally validated, it was demonstrated that the robot can be socially integrated into animal groups. The designed system opens new opportunities in the study of behavior in domestic fowl by using mobile robots. Being socially integrated into the animal group, mobile robots can profit from the positive feedback mechanism that plays key roles in animal collective behavior. They have potential applications in various domains, from pure scientific research to applied areas such as control and ensuring welfare of poultry.

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“…For full localisation the distance to the sound source needs also to be determined. Other work showed distance estimation to unknown sound sources to be a challenging task where only little accuracy is obtained [18], [13].…”

Section: Sense Of Soundmentioning

confidence: 99%

“…Determining the distance to a sound source without knowledge about its loudness is a challenging task [18], [13].…”

Section: Helicopter's Sound Signaturementioning

confidence: 99%

Mitigating the effect of background noise in sound based helicopter control

Passow

Coupland

Góngora

2010

International Conference on Fuzzy Systems

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Abstract-Our research focuses on the use of sound to enhance the control of an autonomous indoor helicopterFlyper. One of the many challenging problems in this project is managing the uncertainty which is present in input data and the control actions; this paper focuses on managing the uncertainty in the input data. We present a fuzzy logic system which infers how much confidence should be placed on a control decision based on the data which was used to make that decision. The input data is a supervised and sound based position estimate of the flying robot. The output of the fuzzy inference system provides us with a confidence parameter used to attenuate the position control of the autonomous helicopter. We performed test flights with and without the fuzzy confidence parameter and with and without artificial disturbance in form of concurrent speech. We employed a motion tracker to capture the helicopter's movement during all test flights. The analysis of the data collected shows encouraging results.

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Three ring microphone array for 3D sound localization and separation for mobile robot audition

Cited by 44 publications

References 2 publications

Managing uncertainty in sound based control for an autonomous helicopter

Managing uncertainty in sound based control for an autonomous helicopter

Designing a socially integrated mobile robot for ethological research

Mitigating the effect of background noise in sound based helicopter control

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