Experiences with an Interactive Museum Tour-Guide Robot

Burgard, Wolfram; Cremers, Armin B.; Fox, Dieter; Haehnel, Dirk; Lakemeyer, Gerhard

doi:10.21236/ada352295

Cited by 200 publications

(176 citation statements)

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“…An example with ultrasonic measurements can be found in [13]. A very common map in iconic estimation is based on grids or occupation cells [8,13,41,42]. Markov probabilistic techniques for position estimation were used in [7,8,20].…”

Section: Iconic Position Estimation Using a Metric Mapmentioning

confidence: 99%

“…If the LN is a location cluster, the robot has been found and the confidence intervals of the position could be calculated by the estimation of the probability density function (pdf) of the position and orientation conditioned to exteroceptive variables using Equations (8) and (9). For example, for the component x of the position the following pdf should be estimated pdf xr vi = N µ xr , v xr .…”

Section: > Exc Locmentioning

confidence: 99%

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A Neural-based Model for Fast Continuous and Global Robot Location

Miralles

Sanz-Bobi

2006

J Intell Robot Syst

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One of the problems in the field of mobile robotics is the estimation of the robot position in an environment. This paper proposes a model for estimating a confidence interval of the robot position in order to compare it with the estimation made by a dead-reckoning system. Both estimations are fused using heuristic rules. The positioning model is very valuable in estimating the current robot position with or without knowledge about the previous positions. Furthermore, it is possible to define the degree of knowledge of the robot previous position, making it possible to adapt the estimation by varying this knowledge degree. This model is based on a onepass neural network which adapts itself in real time and learns about the relationship between the measurements from sensors and the robot position.

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Section: Iconic Position Estimation Using a Metric Mapmentioning

confidence: 99%

Section: > Exc Locmentioning

confidence: 99%

A Neural-based Model for Fast Continuous and Global Robot Location

Miralles

Sanz-Bobi

2006

J Intell Robot Syst

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show abstract

“…Mobile robots intervene in our daily life and provide services (e.g., guidance, assistance [1,2]) or even leisure activities (e.g., providing company, dancing [3,4]). This intrusion of mobile robots into citizens' day-to-day lives must take people into account, whilst seeking social compliance.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Classical and Interactive Multi-Robot Exploration Strategies in Populated Environments

Kaldé¹,

Simonin²,

Charpillet³

2015

Acta Polytech

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Multi-robot exploration consists in coordinating robots for mapping an unknown environment. It raises several issues concerning task allocation, robot control, path planning and communication. We study exploration in populated environments, in which pedestrian flows can severely impact performances. However, humans have adaptive skills for taking advantage of these flows while moving. Therefore, in order to exploit these human abilities, we propose a novel exploration strategy that explicitly allows for human-robot interactions. Our model for exploration in populated environments combines the classical frontier-based strategy with our interactive approach. We implement interactions where robots can locally choose a human guide to follow and define a parametric heuristic to balance interaction and frontier assignments. Finally, we evaluate to which extent human presence impacts our exploration model in terms of coverage ratio, travelled distance and elapsed time to completion.

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“…Field trials have been conducted with robots in museums, expositions, schools, train stations, and other places [1,12,14,22,24]. Institutions such as hospitals have also begun to use mobile robots [17], and projects such as DustBot and URUS [19] have begun exploring the ways robots can operate alongside humans in urban environments.…”

Section: Introductionmentioning

confidence: 99%

Field trial for simultaneous teleoperation of mobile social robots

Glas¹,

Kanda²,

Ishiguro

et al. 2009

Proceedings of the 4th ACM/IEEE International Conference on Human Robot Interaction

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Simultaneous teleoperation of mobile, social robots presents unique challenges, combining the real-time demands of conversation with the prioritized scheduling of navigational tasks. We have developed a system in which a single operator can effectively control four mobile robots performing both conversation and navigation. We compare the teleoperation requirements for mobile, social robots with those of traditional robot systems, and we identify metrics for evaluating task difficulty and operator performance for teleoperation of mobile social robots. As a proof of concept, we present an integrated priority model combining real-time conversational demands and non-real-time navigational demands for operator attention, and in a pioneering study, we apply the model and metrics in a demonstration of our multi-robot system through real-world field trials in a shopping arcade.

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Experiences with an Interactive Museum Tour-Guide Robot

Cited by 200 publications

References 0 publications

A Neural-based Model for Fast Continuous and Global Robot Location

A Neural-based Model for Fast Continuous and Global Robot Location

Comparison of Classical and Interactive Multi-Robot Exploration Strategies in Populated Environments

Field trial for simultaneous teleoperation of mobile social robots

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