Multi-modal Proactive Approaching of Humans for Human-Robot Cooperative Tasks

Naik, Lakshadeep; Palinko, Oskar; Bodenhagen, Leon; Krüger, Norbert

doi:10.1109/ro-man50785.2021.9515475

Cited by 4 publications

(2 citation statements)

References 27 publications

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“…The cost map generally helps in navigation by separating dynamic obstacles from static ones. A typical dynamic obstacle can be defined for a person who walks across the robot's path [9]- [16]. Predicting patterns of pedestrians and reflecting them in the cost map can help further reduce the deadlocks between the robots and humans.…”

Section: Related Workmentioning

confidence: 99%

Layered-Cost-Map-Based Traffic Management for Multiple AMRs via a DDS

Jeong

Inhwan³

et al. 2022

Applied Sciences

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A traffic management system can be used to control multiple automated mobile robots (AMRs) effectively. This paper proposes traffic management for multiple AMRs based on a layered cost map in ROS 2 for multiple purposes. Using the layered cost map, the new concepts of a prohibition filter, lane filter, fleet layer, and region filter are proposed and implemented. The prohibition filter can help a user set an area that would prohibit an AMR from trespassing. The lane filter can help set one-way directions based on an angle image. The fleet layer can help AMRs share their locations via the traffic management server. The region filter requests for or receives an exclusive area, which can be occupied by only one AMR from the traffic management server. Multiple AMRs communicate via a data distribution service (DDS), which is shared by topics in the same DDS domain. The traffic management server in the domain sends or receives topics to each of the AMRs. The experiments of AMRs under the proposed traffic management show the effectiveness of our approach.

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Section: Related Workmentioning

confidence: 99%

Layered-Cost-Map-Based Traffic Management for Multiple AMRs via a DDS

Jeong

Inhwan³

et al. 2022

Applied Sciences

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“…In the second scenario where no planning is possible due to the density of people in the area, the SMOOTH-robot moves around in a pseudo-random fashion and switches to the interaction mode as soon as it notices any person in its camera view (Naik et al, 2021). In this case, special attention needs to be paid not to address the same people multiple times.…”

Section: Beverage Deliverymentioning

confidence: 99%

The SMOOTH-Robot: A Modular, Interactive Service Robot

Krüger

Fischer²,

Manoonpong

et al. 2021

Front. Robot. AI

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The SMOOTH-robot is a mobile robot that—due to its modularity—combines a relatively low price with the possibility to be used for a large variety of tasks in a wide range of domains. In this article, we demonstrate the potential of the SMOOTH-robot through three use cases, two of which were performed in elderly care homes. The robot is designed so that it can either make itself ready or be quickly changed by staff to perform different tasks. We carefully considered important design parameters such as the appearance, intended and unintended interactions with users, and the technical complexity, in order to achieve high acceptability and a sufficient degree of utilization of the robot. Three demonstrated use cases indicate that such a robot could contribute to an improved work environment, having the potential to free resources of care staff which could be allocated to actual care-giving tasks. Moreover, the SMOOTH-robot can be used in many other domains, as we will also exemplify in this article.

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