Integrating olfaction in a robotic telepresence loop

Monroy, Javier; Melendez-Fernandez, Francisco; Gongora, Andres; González-Jiménez, Javier

doi:10.1109/roman.2017.8172427

Cited by 4 publications

(2 citation statements)

References 37 publications

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“…To demonstrate this claim, two parallel approaches were considered: on the one hand, we relied on human intervention by means of a teleoperated mobile platform [48], delegating the inference of the most likely source location to the human tele-operator, and, on the other hand, we developed a fully autonomous system able to infer the most likely source location based on the sensory data available on the robot and high-level semantic reasoning [49]. Both approaches are detailed in the following sections and were assessed through experiments with the Giraff mobile robot.…”

Section: Exploiting High-level Olfactory and Visual Semantic Informentioning

confidence: 99%

Olfaction, Vision, and Semantics for Mobile Robots. Results of the IRO Project

Monroy

Ruiz-Sarmiento

Moreno

et al. 2019

Sensors

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Olfaction is a valuable source of information about the environment that has not been sufficiently exploited in mobile robotics yet. Certainly, odor information can contribute to other sensing modalities, e.g., vision, to accomplish high-level robot activities, such as task planning or execution in human environments. This paper organizes and puts together the developments and experiences on combining olfaction and vision into robotics applications, as the result of our five-years long project IRO: Improvement of the sensory and autonomous capability of Robots through Olfaction. Particularly, it investigates mechanisms to exploit odor information (usually coming in the form of the type of volatile and its concentration) in problems such as object recognition and scene–activity understanding. A distinctive aspect of this research is the special attention paid to the role of semantics within the robot perception and decision-making processes. The obtained results have improved the robot capabilities in terms of efficiency, autonomy, and usefulness, as reported in our publications.

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Section: Exploiting High-level Olfactory and Visual Semantic Informentioning

confidence: 99%

Olfaction, Vision, and Semantics for Mobile Robots. Results of the IRO Project

Monroy

Ruiz-Sarmiento

Moreno

et al. 2019

Sensors

Self Cite

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“…1). Users controlled the mobile platform via a web-based interface [22], [23], declaring the gas source by terminating the experiment at the desired location.…”

Section: Acquisition Of the Experimental Datamentioning

confidence: 99%

Gas source localization strategies for teleoperated mobile robots. An experimental analysis

Gongora

Monroy

González-Jiménez

2017

2017 European Conference on Mobile Robots (ECMR)

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Gas source localization (GSL) is one of the most important and direct applications of a gas sensitive mobile robot, and consists in searching for one or multiple volatile emission sources with a mobile robot that has improved sensing capabilities (i.e. olfaction, wind flow, etc.). This work adresses GSL by employing a teleoperated mobile robot, and focuses on which search strategy is the most suitable for this teleoperated approach. Four different search strategies, namely chemotaxis, anemotaxis, gas-mapping, and visual-aided search, are analyzed and evaluated according to a set of proposed indicators (e.g. accuracy, efficiency, success rate, etc.) to determine the most suitable one for a human-teleoperated mobile robot. Experimental validation is carried out employing a large dataset composed of over 150 trials where volunteer operators had to locate a gas-leak in a virtual environment under various and realistic environmental conditions (i.e. different wind flow patterns and gas source locations). We report different findings, from which we highlight that, against intuition, visual-aided search is not always the best strategy, but depends on the environmental conditions and the operator's ability to understand how gas distributes.This work has been funded by the Governments of Spain and Andalusia, and the European Regional Development Fund under project TEP530.

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Teledrive: An Embodied AI Based Telepresence System

Banerjee,

Paul,

Roychoudhury

et al. 2024

J Intell Robot Syst

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This article presents ‘Teledrive’, a telepresence robotic system with embodied AI features that empowers an operator to navigate the telerobot in any unknown remote place with minimal human intervention. We conceive Teledrive in the context of democratizing remote ‘care-giving’ for elderly citizens as well as for isolated patients, affected by contagious diseases. In particular, this paper focuses on the problem of navigating to a rough target area (like ‘bedroom’ or ‘kitchen’) rather than pre-specified point destinations. This ushers in a unique ‘AreaGoal’ based navigation feature, which has not been explored in depth in the contemporary solutions. Further, we describe an edge computing-based software system built on a WebRTC-based communication framework to realize the aforementioned scheme through an easy-to-use speech-based human-robot interaction. Moreover, to enhance the ease of operation for the remote caregiver, we incorporate a ‘person following’ feature, whereby a robot follows a person on the move in its premises as directed by the operator. Moreover, the system presented is loosely coupled with specific robot hardware, unlike the existing solutions. We have evaluated the efficacy of the proposed system through baseline experiments, user study, and real-life deployment.

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Integrating olfaction in a robotic telepresence loop

Cited by 4 publications

References 37 publications

Olfaction, Vision, and Semantics for Mobile Robots. Results of the IRO Project

Olfaction, Vision, and Semantics for Mobile Robots. Results of the IRO Project

Gas source localization strategies for teleoperated mobile robots. An experimental analysis

Teledrive: An Embodied AI Based Telepresence System

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