Mobile robot programming using natural language

Lauria, Stanislao; Bugmann, Guido; Kyriacou, Theocharis; Klein, Ewan

doi:10.1016/s0921-8890(02)00166-5

Cited by 120 publications

(53 citation statements)

References 5 publications

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“…In this context, two domains of interaction that humans exploit with great fidelity are spoken language, and the visual ability to observe and understand intentional action. A good deal of research effort has been dedicated to the specification and implementation of spoken language systems for human-robot interaction (Crangle & Suppes 1994, Lauria et al 2002, Severinson-Eklund 2003, Kyriacou et al 2005, Mavrides & Roy 2006. The research described in the current chapter extends these approaches with a Spoken Language Programming system that allows a more detailed specification of conditional execution, and by using language as a compliment to vision-based action perception as a mechanism for indicating how things are to be done, in the context of cooperative, turn-taking behavior.…”

Section: Discussionmentioning

confidence: 99%

“…Part of the challenge is to define an intermediate layer of language-commanded robot actions that are well adapted to a class of HRI cooperation tasks. This is similar to the language-based task analysis in Lauria et al (2002). An essential part of the analysis we perform concerns examining a given task scenario and determining the set of action/command primitives that satisfy two requirements.…”

Section: Language and Meaningmentioning

confidence: 99%

“…In this context, (Lauria et al 2002) asked naïve subjects to provide verbal instructions to a robot in a miniature-town navigation task. Based on an analysis of the resulting speech corpora, they identified a set of verbal action chunks that could map onto robot control primitives.…”

Section: Spoken Language Programmingmentioning

confidence: 99%

See 2 more Smart Citations

Spoken Language and Vision for Adaptive Human-Robot Cooperation

Dominey¹

2007

Humanoid Robots: New Developments

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Section: Discussionmentioning

confidence: 99%

Section: Language and Meaningmentioning

confidence: 99%

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Spoken Language and Vision for Adaptive Human-Robot Cooperation

Dominey¹

2007

Humanoid Robots: New Developments

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“…We call this type of method the Direct Commanding Method (DCM), in which users directly send commands to robots in order to control them. Plenty of studies have used DCM, such as gestures [7,8,9], speech recognition [10,11,12], and control devices like joysticks [13,14,15]. Figure 1 shows the DCM interaction model.…”

Section: Direct Commanding Methodsmentioning

confidence: 99%

Extending Commands Embedded in Actions for Human-Robot Cooperative Tasks

Kobayashi

Yamada

2010

Int J of Soc Robotics

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In this paper, we propose a novel method to control a robot without robot manipulation. Users do not need to precisely manipulate the robot and to learn the manipulation method. The proposed method can send commands to a robot by using a human action sequence that achieves their own task. In order to enable the robot to achieve tasks, we introduce a keepbased interaction in which a human keeps an action in the sequence for a certain period. The advantages of our method are efficiency improved by not requiring additional human actions, and functionality to enable a robot to perform further actions. We consider that the efficiency is supported by users' physical workloads and cognitive loads. Users' physical workloads would not be increased because the proposed method does not require additional human actions. However, the effect of the proposed method on users' cognitive loads is unknown. We applied the method to a desktop sweeping task by a human and a small mobile robot, and conducted an experiment with participants to measure users' cognitive loads in a cooperative sweeping task. As a result, we found that the proposed method had a lower cognitive load than a typical conventional method.

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“…Under this requirement there have been several research issues currently active in the Robotics community. These issues include speaker localization [1] [5], speech separation and enhancement [2], speech recognition and natural dialog [3], and speaker identification and multi-modal interaction [4] etc. Among them, speaker localization using either biological hearing principle [5] or microphone array [1] has drawn lots of attentions for many years [6].…”

Section: Introductionmentioning

confidence: 99%

Simultaneous localization of mobile robot and multiple sound sources using microphone array

Chan

Wang

et al. 2009

2009 IEEE International Conference on Robotics and Automation

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Abstract-Sound source localization is an important function in robot audition. The existing works perform sound source localization using static microphone arrays. This work proposes a framework that simultaneously localizes the mobile robot and multiple sound sources using a microphone array on the robot. First, an eigenstructure-based generalized cross correlation method for estimating time delays between microphones under multi-source environments is described. A method to compute the far field source directions as well as the speed of sound using the estimated time delays is proposed. In addition, the correctness of the sound speed estimate is utilized to eliminate spurious sources, which greatly enhances the robustness of sound source detection. The arrival angles of the detected sound sources are used as observations in a bearings-only SLAM procedure. As the source signals are not persistent and there is no identification of the signal content, data association is unknown which is solved using FastSLAM. The experimental results demonstrate the effectiveness of the proposed approaches.

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Mobile robot programming using natural language

Cited by 120 publications

References 5 publications

Spoken Language and Vision for Adaptive Human-Robot Cooperation

Spoken Language and Vision for Adaptive Human-Robot Cooperation

Extending Commands Embedded in Actions for Human-Robot Cooperative Tasks

Simultaneous localization of mobile robot and multiple sound sources using microphone array

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