Natural language command of an autonomous micro-air vehicle

Huang, Albert S.; Tellex, Stefanie; Bachrach, Abraham; Kollar, Thomas; Roy, Deb; Roy, Nicholas

doi:10.1109/iros.2010.5650910

Cited by 28 publications

(16 citation statements)

References 16 publications

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“…Extensive research on teleoperation of small sized aerial robots with various types of input-devices and according interactions, has been conducted in the past decade. Despite the popularity of novel interaction paradigms, like hand-gesture (Yu et al, 2017 ; Duan et al, 2018 ), body-gesture (Rognon et al, 2018 ), gaze (Yu et al, 2014 ; Erat et al, 2018 ; Yuan et al, 2019 ), and language (Huang et al, 2010 , 2019 ), more recent work still focuses on aspects of traditional joystick based teleoperation of small-sized UAVs, for example avoiding collisions during navigation (Cho et al, 2017 ). Sanders et al ( 2018 ) report that operators still prefer joystick control over indirect gaze-based steering, whereas findings of Herrmann and Schmidt ( 2018 ) indicate that a traditional input device is more efficient than their extensive and carefully designed system based on natural interactions.…”

Section: Related Workmentioning

confidence: 99%

High-Level Teleoperation System for Aerial Exploration of Indoor Environments

et al. 2019

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Exploration of challenging indoor environments is a demanding task. While automation with aerial robots seems a promising solution, fully autonomous systems still struggle with high-level cognitive tasks and intuitive decision making. To facilitate automation, we introduce a novel teleoperation system with an aerial telerobot that is capable of handling all demanding low-level tasks. Motivated by the typical structure of indoor environments, the system creates an interactive scene topology in real-time that reduces scene details and supports affordances. Thus, difficult high-level tasks can be effectively supervised by a human operator. To elaborate on the effectiveness of our system during a real-world exploration mission, we conducted a user study. Despite being limited by real-world constraints, results indicate that our system better supports operators with indoor exploration, compared to a baseline system with traditional joystick control.

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Section: Related Workmentioning

confidence: 99%

High-Level Teleoperation System for Aerial Exploration of Indoor Environments

et al. 2019

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“…A quadcopter navigated in indoor environments with human's oral guidance. (d) is social accompany [14]. A pet dog is playing balls with a human with socialized verbal communications.…”

Section: A Backgroundmentioning

confidence: 99%

A review of methodologies for natural-language-facilitated human–robot cooperation

Liu

Zhang

2019

International Journal of Advanced Robotic Systems

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Natural-language-facilitated human-robot cooperation (NLC) refers to using natural language (NL) to facilitate interactive information sharing and task executions with a common goal constraint between robots and humans. Recently, NLC research has received increasing attention. Typical NLC scenarios include robotic daily assistance, robotic health caregiving, intelligent manufacturing, autonomous navigation, and robot social accompany. However, a thorough review, that can reveal latest methodologies to use NL to facilitate human-robot cooperation, is missing. In this review, a comprehensive summary about methodologies for NLC is presented. NLC research includes three main research focuses: NL instruction understanding, NLbased execution plan generation, and knowledgeworld mapping. In-depth analyses on theoretical methods, applications, and model advantages and disadvantages are made. Based on our paper review and perspective, potential research directions of NLC are summarized. Index Terms-natural language, human-robot cooperation, NL instruction understanding, NLbased execution plan generation, knowledge-world mapping _______________________________________ Rui Liu and Xiaoli Zhang are with the Intelligent Robotics and Systems Lab (IRSL), Colorado School of Mines,

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“…The user may interact with drones through joystick controllers, touchscreens [2,6], body gestures [11,31], natural language commands [21], etc. .…”

Section: B Human-drone Interaction For Drone Navigationmentioning

confidence: 99%

XPose: Reinventing User Interaction with Flying Cameras

Lan¹,

Shridhar²,

Hsu³

et al. 2017

Robotics: Science and Systems XIII

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Abstract-XPose is a new touch-based interactive system for photo taking, designed to take advantage of the autonomous flying capability of a drone-mounted camera. It enables the user to interact with photos directly and focus on taking photos instead of piloting the drone. XPose introduces a two-stage eXplore-and-comPose approach to photo taking in static scenes. In the first stage, the user explores the "photo space" through predefined interaction modes: Orbit, Pano, and Zigzag. Under each mode, the camera visits many points of view (POVs) and takes exploratory photos through autonomous drone flying. In the second stage, the user restores a selected POV with the help of a gallery preview and uses direct manipulation gestures to refine the POV and compose a final photo. Our prototype implementation, based on a Parrot Bebop quadcopter, relies mainly on a single monocular camera and works reliably in a GPS-denied environment. A systematic user study indicates that XPose results in more successful user performances in phototaking tasks than the touchscreen joystick interface widely used in commercial drones today.

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Natural language command of an autonomous micro-air vehicle

Cited by 28 publications

References 16 publications

High-Level Teleoperation System for Aerial Exploration of Indoor Environments

High-Level Teleoperation System for Aerial Exploration of Indoor Environments

A review of methodologies for natural-language-facilitated human–robot cooperation

XPose: Reinventing User Interaction with Flying Cameras

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