Using gesture and speech control for commanding a robot assistant

Rogalla, O.; Ehrenmann, M.; Zöllner, R.; Becher, Regine; Dillmann, R.

doi:10.1109/roman.2002.1045664

Cited by 89 publications

(53 citation statements)

References 11 publications

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“…Heads and hands are found with reasonable accuracy based purely on their color. 24,40 Skin color occupies a rather well-defined area in color spaces (such as Hue, Saturation, and Intensity, L*a*b*, and YIQ) so can be used for segmentation (see Figure 2 and Hasanuzzaman et al, 19 Rogalla et al, 41 and Yin and Zhu 53 ). Combined histogram-matching and blob-tracking with Camshift 7 or the Viterbi algorithm 54 is a popular approach due to its speed, ease of implementation, and performance.…”

Section: Hand-gesture Recognitionmentioning

confidence: 99%

“…Such games use contextual information like gesture velocity and curvature to extract meaningful gestures from a video sequence. Bannach et al 41 addressed gesture spotting through a sliding window and bottom-up approach in a mixed-reality parking game. Schlömer et al 42 addressed accelerometer-based gesture recognition for drawing and browsing operations in a computer game.…”

Section: Applicationsmentioning

confidence: 99%

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Vision-based hand-gesture applications

et al. 2011

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Section: Hand-gesture Recognitionmentioning

confidence: 99%

Section: Applicationsmentioning

confidence: 99%

Vision-based hand-gesture applications

et al. 2011

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“…To resolve the ambiguity, Metalman asks the user for additional information by clicking on the desired cup. While a graphical user interface is appropriate for tele-operated robots, a practical humanoid may alternatively use verbal or gestural interaction [9], [12].…”

Section: Experiments 2: Pouring Taskmentioning

confidence: 99%

“…In recent years, humanoid robotics research has made important steps towards this goal by addressing problems such as locomotion [11], interaction [9] and learning [2]. Our work develops the perception and control skills necessary to perform simple manipulations (such as pouring a drink) with minimum a priori knowledge in an unstructured domestic environment, which forms the basis of important applications such as assisting the elderly and disabled.…”

Section: Introductionmentioning

confidence: 99%

Integration of robust visual perception and control for a domestic humanoid robot

Taylor

Kleeman

2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566)

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Abstract-This paper describes a complete vision-based framework that enables a humanoid robot to perform simple manipulations in a domestic environment. Our system emphasizes autonomous operation with minimal a priori knowledge in an unstructured environment, with robustness to visual distractions and calibration errors. For each new task, the robot first acquires a dense 3D image of the scene using our novel stereoscopic light stripe scanner that rejects secondary reflections and cross-talk. A data-driven analysis of the range map identifies and models simple objects using geometric primitives. Objects are reliably tracked through clutter and occlusions by exploiting multimodal cues (colour, texture and edges). Finally, manipulations are performed by controlling the end-effector using a hybrid position-based visual servoing scheme that fuses visual and kinematic measurements and compensates for calibration errors. Two domestic tasks are implemented to evaluate the performance of the framework: identifying and grasping a yellow box without any prior knowledge of the object, and pouring rice from an interactively selected cup into a bowl.

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“…Much research has already been conducted in the area of non-verbal communication between a robot and a human, such as facial expression, eye-gaze, and gesture commands [4], [9], [20], [25], [29]. However, only little research has been done in the area of developing a robotic system that is able to interact with multiple persons appropriately.…”

Section: Introductionmentioning

confidence: 99%

Towards a humanoid museum guide robot that interacts with multiple persons

Bennewitz

Faber

Joho

et al.

5th IEEE-RAS International Conference on Humanoid Robots, 2005.

102

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Abstract-The purpose of our research is to develop a humanoid museum guide robot that performs intuitive, multimodal interaction with multiple persons. In this paper, we present a robotic system that makes use of visual perception, sound source localization, and speech recognition to detect, track, and involve multiple persons into interaction. Depending on the audio-visual input, our robot shifts its attention between different persons. In order to direct the attention of its communication partners towards exhibits, our robot performs gestures with its eyes and arms. As we demonstrate in practical experiments, our robot is able to interact with multiple persons in a multimodal way and to shift its attention between different people. Furthermore, we discuss experiences made during a two-day public demonstration of our robot.

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Using gesture and speech control for commanding a robot assistant

Cited by 89 publications

References 11 publications

Vision-based hand-gesture applications

Vision-based hand-gesture applications

Integration of robust visual perception and control for a domestic humanoid robot

Towards a humanoid museum guide robot that interacts with multiple persons

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