Feel the Point Clouds: Traversability Prediction and Tactile Terrain Detection Information for an Improved Human-Robot Interaction

Raimund Edlinger; Andreas Nüchter

doi:10.1109/RO-MAN57019.2023.10309349

Feel the Point Clouds: Traversability Prediction and Tactile Terrain Detection Information for an Improved Human-Robot Interaction

Raimund Edlinger
, Andreas Nüchter

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

The field of human-robot interaction has been rapidly advancing in recent years, as robots are increasingly being integrated into various aspects of human life. However, for robots to effectively collaborate with humans, it is crucial that they have a deep understanding of the environment in which they operate. In particular, the ability to predict traversability and detect tactile information is crucial for enhancing the safety and efficiency of human-robot interactions.
To address this challenge, this paper proposes a method called "Feel the Point Clouds" that use point clouds to predict traversability and detect tactile terrain information for a tracked rescue robot. This information can be used to adjust the robot's behavior and movements in real-time, allowing it to interact with the environment in a more intuitive and safe manner.
The experimental results of the proposed method are evaluated in various scenarios and demonstrate its effectiveness in improving human-robot interaction and visualization for a more accurate and intuitive understanding of the environment.

Original language	English
Title of host publication	2023 32nd IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2023
Place of Publication	Busan, Korea, Republic of
Publisher	IEEE
Pages	1121-1128
Number of pages	8
ISBN (Electronic)	979-8-3503-3670-2
ISBN (Print)	979-8-3503-3671-9
DOIs	https://doi.org/10.1109/RO-MAN57019.2023.10309349
Publication status	Published - 13 Nov 2023

Publication series

Name	IEEE International Workshop on Robot and Human Communication, RO-MAN
ISSN (Print)	1944-9445
ISSN (Electronic)	1944-9437

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

HRI
Rescue Robot
Point Clouds
terrain prediction
Tactile feedback

Access to Document

10.1109/RO-MAN57019.2023.10309349Licence: Unspecified

Cite this

Edlinger, R., & Nüchter, A. (2023). Feel the Point Clouds: Traversability Prediction and Tactile Terrain Detection Information for an Improved Human-Robot Interaction. In 2023 32nd IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2023 (pp. 1121-1128). (IEEE International Workshop on Robot and Human Communication, RO-MAN). IEEE. https://doi.org/10.1109/RO-MAN57019.2023.10309349

Edlinger, Raimund ; Nüchter, Andreas. / Feel the Point Clouds: Traversability Prediction and Tactile Terrain Detection Information for an Improved Human-Robot Interaction. 2023 32nd IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2023. Busan, Korea, Republic of : IEEE, 2023. pp. 1121-1128 (IEEE International Workshop on Robot and Human Communication, RO-MAN).

@inproceedings{b7b620fa3da24c1fb9398f5da512a6d3,

title = "Feel the Point Clouds: Traversability Prediction and Tactile Terrain Detection Information for an Improved Human-Robot Interaction",

abstract = "The field of human-robot interaction has been rapidly advancing in recent years, as robots are increasingly being integrated into various aspects of human life. However, for robots to effectively collaborate with humans, it is crucial that they have a deep understanding of the environment in which they operate. In particular, the ability to predict traversability and detect tactile information is crucial for enhancing the safety and efficiency of human-robot interactions. To address this challenge, this paper proposes a method called {"}Feel the Point Clouds{"} that use point clouds to predict traversability and detect tactile terrain information for a tracked rescue robot. This information can be used to adjust the robot's behavior and movements in real-time, allowing it to interact with the environment in a more intuitive and safe manner. The experimental results of the proposed method are evaluated in various scenarios and demonstrate its effectiveness in improving human-robot interaction and visualization for a more accurate and intuitive understanding of the environment.",

keywords = "HRI, Rescue Robot, Point Clouds, terrain prediction, Tactile feedback",

author = "Raimund Edlinger and Andreas N{\"u}chter",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.",

year = "2023",

month = nov,

day = "13",

doi = "10.1109/RO-MAN57019.2023.10309349",

language = "English",

isbn = "979-8-3503-3671-9",

series = "IEEE International Workshop on Robot and Human Communication, RO-MAN",

publisher = "IEEE",

pages = "1121--1128",

booktitle = "2023 32nd IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2023",

}

Edlinger, R & Nüchter, A 2023, Feel the Point Clouds: Traversability Prediction and Tactile Terrain Detection Information for an Improved Human-Robot Interaction. in 2023 32nd IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2023. IEEE International Workshop on Robot and Human Communication, RO-MAN, IEEE, Busan, Korea, Republic of, pp. 1121-1128. https://doi.org/10.1109/RO-MAN57019.2023.10309349

Feel the Point Clouds: Traversability Prediction and Tactile Terrain Detection Information for an Improved Human-Robot Interaction. / Edlinger, Raimund; Nüchter, Andreas.
2023 32nd IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2023. Busan, Korea, Republic of: IEEE, 2023. p. 1121-1128 (IEEE International Workshop on Robot and Human Communication, RO-MAN).

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

TY - GEN

T1 - Feel the Point Clouds: Traversability Prediction and Tactile Terrain Detection Information for an Improved Human-Robot Interaction

AU - Edlinger, Raimund

AU - Nüchter, Andreas

PY - 2023/11/13

Y1 - 2023/11/13

N2 - The field of human-robot interaction has been rapidly advancing in recent years, as robots are increasingly being integrated into various aspects of human life. However, for robots to effectively collaborate with humans, it is crucial that they have a deep understanding of the environment in which they operate. In particular, the ability to predict traversability and detect tactile information is crucial for enhancing the safety and efficiency of human-robot interactions. To address this challenge, this paper proposes a method called "Feel the Point Clouds" that use point clouds to predict traversability and detect tactile terrain information for a tracked rescue robot. This information can be used to adjust the robot's behavior and movements in real-time, allowing it to interact with the environment in a more intuitive and safe manner. The experimental results of the proposed method are evaluated in various scenarios and demonstrate its effectiveness in improving human-robot interaction and visualization for a more accurate and intuitive understanding of the environment.

AB - The field of human-robot interaction has been rapidly advancing in recent years, as robots are increasingly being integrated into various aspects of human life. However, for robots to effectively collaborate with humans, it is crucial that they have a deep understanding of the environment in which they operate. In particular, the ability to predict traversability and detect tactile information is crucial for enhancing the safety and efficiency of human-robot interactions. To address this challenge, this paper proposes a method called "Feel the Point Clouds" that use point clouds to predict traversability and detect tactile terrain information for a tracked rescue robot. This information can be used to adjust the robot's behavior and movements in real-time, allowing it to interact with the environment in a more intuitive and safe manner. The experimental results of the proposed method are evaluated in various scenarios and demonstrate its effectiveness in improving human-robot interaction and visualization for a more accurate and intuitive understanding of the environment.

KW - HRI

KW - Rescue Robot

KW - Point Clouds

KW - terrain prediction

KW - Tactile feedback

UR - https://www.scopus.com/pages/publications/85187011488

U2 - 10.1109/RO-MAN57019.2023.10309349

DO - 10.1109/RO-MAN57019.2023.10309349

M3 - Conference contribution

SN - 979-8-3503-3671-9

T3 - IEEE International Workshop on Robot and Human Communication, RO-MAN

SP - 1121

EP - 1128

BT - 2023 32nd IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2023

PB - IEEE

CY - Busan, Korea, Republic of

ER -

Edlinger R, Nüchter A. Feel the Point Clouds: Traversability Prediction and Tactile Terrain Detection Information for an Improved Human-Robot Interaction. In 2023 32nd IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2023. Busan, Korea, Republic of: IEEE. 2023. p. 1121-1128. (IEEE International Workshop on Robot and Human Communication, RO-MAN). doi: 10.1109/RO-MAN57019.2023.10309349

Feel the Point Clouds: Traversability Prediction and Tactile Terrain Detection Information for an Improved Human-Robot Interaction

Abstract

Publication series

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this