To Explore or to Exploit? Learning Humans’ Behaviour to Maximize Interactions with Them

Kulich, Miroslav; Krajník, Tomáš; PřeuăźIl, Libor; Duckett, Tom

doi:10.1007/978-3-319-47605-6_5

Cited by 6 publications

(5 citation statements)

References 23 publications

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“…Since there are multiple options how to address the service scheduling problem and verification of each option would take at least 4 weeks, we already used the temporal models learned by the robot in the deployment to create a dynamic simulation of the deployment environment. Using this simulator, we tested over 50 different scheduling strategies, service utility functions and path planning policies and we found out that a more complex utility function in combination with distance-aware path planning can double the number of potential interactions [14]. Thus, for the next deployment of the robot, implemented these improvements and we will compare them to the original scheduling method.…”

Section: Discussionmentioning

confidence: 99%

The When, Where, and How

Hanheide

Hebesberger

Krajník

2017

Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction

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Adapting to users' intentions is a key requirement for autonomous robots in general, and in care settings in particular. In this paper, a comprehensive long-term study of a mobile robot providing information services to residents, visitors, and staff of a care home is presented, with a focus on adapting to the when and where the robot should be offering its services to best accommodate the users' needs. Rather than providing a fixed schedule, the presented system takes the opportunity of long-term deployment to explore the space of possibilities of interaction while concurrently exploiting the model learned to provide better services. But in order to provide effective services to users in a care home, not only then when and where are relevant, but also the way how the information is provided and accessed. Hence, also the usability of the deployed system is studied specifically, in order to provide a most comprehensive overall assessment of a robotic info-terminal implementation in a care setting. Our results back our hypotheses, (i) that learning a spatiotemporal model of users' intentions improves efficiency and usefulness of the system, and (ii) that the specific information sought after is indeed dependent on the location the info-terminal is offered.

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Section: Discussionmentioning

confidence: 99%

The When, Where, and How

Hanheide

Hebesberger

Krajník

2017

Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction

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“…The initial body of work addressing the problem of data collection for MoDs is connected to the work of Krajnik et al (2017). The key publications are Santos et al, 2015Santos et al, , 2017 and Kulich et al (2016). All the listed publications attempt to address the problem of efficient data acquisition while streaking the balance between exploration and exploitation.…”

Section: Task Planningmentioning

confidence: 99%

Survey of maps of dynamics for mobile robots

Kucner

Magnusson

Mghames

et al. 2023

The International Journal of Robotics Research

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Robotic mapping provides spatial information for autonomous agents. Depending on the tasks they seek to enable, the maps created range from simple 2D representations of the environment geometry to complex, multilayered semantic maps. This survey article is about maps of dynamics (MoDs), which store semantic information about typical motion patterns in a given environment. Some MoDs use trajectories as input, and some can be built from short, disconnected observations of motion. Robots can use MoDs, for example, for global motion planning, improved localization, or human motion prediction. Accounting for the increasing importance of maps of dynamics, we present a comprehensive survey that organizes the knowledge accumulated in the field and identifies promising directions for future work. Specifically, we introduce field-specific vocabulary, summarize existing work according to a novel taxonomy, and describe possible applications and open research problems. We conclude that the field is mature enough, and we expect that maps of dynamics will be increasingly used to improve robot performance in real-world use cases. At the same time, the field is still in a phase of rapid development where novel contributions could significantly impact this research area.

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“…Considering the ability of a robot that uses FreMEn to recognise “when” it observed the most informative situation, the novel information-based Monte-Carlo scheduler for exploration was proposed ( Santos et al, 2016 ). Eventualy, different exploration strategies ( Krajník et al, 2015b ; Santos et al, 2017 ; Molina et al, 2019 ) and exploration–exploitation dilema ( Kulich et al, 2016 ) were studied. In the study by ( Jovan et al, 2016 ), FreMEn was redefined into the Addition Amplitude Model (AAM).…”

Section: Related Workmentioning

confidence: 99%

“…There are a lot of different opinions as to what criterion influences the acceptability of a robot in human society most ( Talebpour et al, 2015 ; Kostavelis et al, 2017 ). Besides, the acceptability need not necessarily be the only point of view that defines the quality of performing the task ( Krajník et al, 2015a ; Fentanes et al, 2015 ; Kulich et al, 2016 ).…”

Section: Generalized Natural Criterionmentioning

confidence: 99%

Toward Benchmarking of Long-Term Spatio-Temporal Maps of Pedestrian Flows for Human-Aware Navigation

et al. 2022

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Despite the advances in mobile robotics, the introduction of autonomous robots in human-populated environments is rather slow. One of the fundamental reasons is the acceptance of robots by people directly affected by a robot’s presence. Understanding human behavior and dynamics is essential for planning when and how robots should traverse busy environments without disrupting people’s natural motion and causing irritation. Research has exploited various techniques to build spatio-temporal representations of people’s presence and flows and compared their applicability to plan optimal paths in the future. Many comparisons of how dynamic map-building techniques show how one method compares on a dataset versus another, but without consistent datasets and high-quality comparison metrics, it is difficult to assess how these various methods compare as a whole and in specific tasks. This article proposes a methodology for creating high-quality criteria with interpretable results for comparing long-term spatio-temporal representations for human-aware path planning and human-aware navigation scheduling. Two criteria derived from the methodology are then applied to compare the representations built by the techniques found in the literature. The approaches are compared on a real-world, long-term dataset, and the conception is validated in a field experiment on a robotic platform deployed in a human-populated environment. Our results indicate that continuous spatio-temporal methods independently modeling spatial and temporal phenomena outperformed other modeling approaches. Our results provide a baseline for future work to compare a wide range of methods employed for long-term navigation and provide researchers with an understanding of how these various methods compare in various scenarios.

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To Explore or to Exploit? Learning Humans’ Behaviour to Maximize Interactions with Them

Cited by 6 publications

References 23 publications

The When, Where, and How

The When, Where, and How

Survey of maps of dynamics for mobile robots

Toward Benchmarking of Long-Term Spatio-Temporal Maps of Pedestrian Flows for Human-Aware Navigation

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