A robotic experiment toward understanding human gas-source localization strategies

Abstract

Abstract-This paper describes an experiment for gas-source localization with a human-teleoperated mobile robot devised to gather data on how humans search for odor-sources. To that end, more than 150 repetitions of the search process are recorded for 69 test subjects, under 4 sensor configurations (including electronic nose, anemometer and video camera) and 4 scenarios (i.e. with different wind-flow conditions and gas-source position). The experiment has been carried out with a ROS-based simulator that allows driving the robot while recording data of interest (e.g. driving commands, robot localization, sensor measurements, groundtruth, etc.) for further analyzing the human process of gas-source searching, and computational fluid dynamics (CFD) to generate realistic and repeatable test conditions. The manuscript describes the different environmental parameters and sensor combinations of the experiment, and explains the methodology under which it was executed. The obtained dataset is publicly available at

Integrating olfaction in a robotic telepresence loop

“…6). The simulated CFD data was then integrated with a standard ROS 5 robotic simulator, to provide gas and wind measurements in the virtual environment (for further details on the simulator and the experimental setup, please see [36] and [35]). It must be stressed that only the robot environment was simulated, retaining the same visitor and network environments of the proposed telepresence loop.…”

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

“…Since inferring the type of object (and the location in the environment) of the gas source that is releasing the gases that have been detected by the robot is not straightforward, we simplified the problem by introducing the human factor and its powerful reasoning capabilities to solve this challenging problem [50]. In this context, olfactory telerobotics can be seen as the augmentation of the sensing capabilities of a conventional teleoperated mobile robot to acquire information about the surrounding air (i.e., gases, wind-speed, etc.)…”

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

“…In this study we use a dataset for teleoperated GSL composed of more than 150 experiments presented in a previous work [21], which is briefly described next to make this paper self contained.…”

“…In pursuit of a fair comparison, we propose evaluating their average effectiveness and accuracy, how they affect the operator's search behaviour, and in terms of expended energy, their efficiency. The analysis is conducted on an extensive dataset composed over 150 experiments, gathered during a previous campaign [21], where users had to locate a gas source in a simulated environment with a teleoperated mobile robot. More specifically, and in accordance with the aforementioned GSL strategies, the experiments are classified in four different configurations: (i) pure chemotaxis, (ii) anemotaxis, (iii) gas mapping with chemical and wind flow data, and (iv) the latter plus visual clues (i.e.…”