A Study on Different User Interfaces for Teaching Virtual Borders to Mobile Robots

Sprute, Dennis; Tönnies, Klaus D.; König, Matthias

doi:10.1007/s12369-018-0506-3

Cited by 19 publications

(16 citation statements)

References 35 publications

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“…there are strong inaccuracies between the user-defined restriction areas as a result of an interaction process and the restriction areas to be intended for restriction by a human. This is caused by a correspondence problem between points on the map and in the environment [45]. In order to address this shortcoming, Sprute et al introduced a framework for interactive teaching of virtual borders based on robot guidance [43].…”

Section: Mobile Robot Workpace Restrictionmentioning

confidence: 99%

“…This is caused by the requirement concerning a direct line of sight between human and robot and limited on-board feedback capabilities. A comprehensive user study dealing with different HRI methods for teaching virtual borders revealed augmented reality as the most powerful interface for the given task [45]. However, this approach requires specialized hardware, i.e.…”

Section: Mobile Robot Workpace Restrictionmentioning

confidence: 99%

“…it changes the mobile robot's navigational behavior, and flexible, i.e. a human can specify arbitrary virtual borders [45]. For this reason, we also employ the algorithm in this work to allow users the definition of restriction areas.…”

Section: Virtual Bordersmentioning

confidence: 99%

“…Current interaction methods are either based on visual displays or mediator-based pointing gestures, e.g. using a laser pointer as pointing device [45]. Especially, the latter one is a natural and intuitive method of non-verbal communication making it applicable by non-expert users [46].…”

Section: Introductionmentioning

confidence: 99%

“…We hypothesize that the additional components of a smart home environment can improve the interaction time and user experience compared to a solution without support of a smart environment because additional sensors and actuators increase the perception and interaction capabilities. Moreover, we hypothesize that other user requirements, such as accuracy and completeness of the interaction method [45], will not be negatively affected.…”

Section: Introductionmentioning

confidence: 99%

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Interactive restriction of a mobile robot’s workspace in a smart home environment

Sprute

Tönnies

König

2019

AIS

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Virtual borders are employed to allow humans the interactive and flexible restriction of their mobile robots' workspaces in human-centered environments, e.g. to exclude privacy zones from the workspace or to indicate certain areas for working. They have been successfully specified in interaction processes using methods from human-robot interaction. However, these methods often lack an expressive feedback system, are restricted to robot's on-board interaction capabilities and require a direct line of sight between human and robot. This negatively affects the user experience and interaction time. Therefore, we investigate the effect of a smart environment on the teaching of virtual borders with the objective to enhance the perceptual and interaction capabilities of a robot. For this purpose, we propose a novel interaction method based on a laser pointer, that leverages a smart home environment in the interaction process. This interaction method comprises an architecture for a smart home environment designed to support the interaction process, the cooperation of human, robot and smart environment in the interaction process, a cooperative perception including stationary and mobile cameras to perceive laser spots and an algorithm to extract virtual borders from multiple camera observations. The results of an experimental evaluation support our hypotheses that our novel interaction method features a significantly shorter interaction time and a better user experience compared to an approach without support of a smart environment. Moreover, the interaction method does not negatively affect other user requirements concerning completeness and accuracy.

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Section: Mobile Robot Workpace Restrictionmentioning

confidence: 99%

Section: Mobile Robot Workpace Restrictionmentioning

confidence: 99%

Section: Virtual Bordersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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