ROS-PyBullet Interface: A Framework for Reliable Contact Simulation and Human-Robot Interaction

Christopher E. Mower; Theodoros Stouraitis; Joao Moura; Christian Rauch; Lei Yan; Nazanin Zamani Behabadi; Michael Gienger; Tom Vercauteren; Christos  Bergeles; Sethu Vijayakumar

ROS-PyBullet Interface: A Framework for Reliable Contact Simulation and Human-Robot Interaction

Christopher E. Mower, Theodoros Stouraitis, Joao Moura, Christian Rauch, Lei Yan, Nazanin Zamani Behabadi, Michael Gienger, Tom Vercauteren, Christos Bergeles, Sethu Vijayakumar

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract / Description of output

Reliable contact simulation plays a key role in the development of (semi-)autonomous robots, especially when dealing with contact-rich manipulation scenarios, an active robotics research topic. Besides simulation, components such as sensing, perception, data collection, robot hardware control, human interfaces, etc. are all key enablers towards applying machine learning algorithms or model-based approaches in real world systems. However, there is a lack of software connecting reliable contact simulation with the larger robotics ecosystem (i.e. ROS, Orocos), for a more seamless application of novel approaches, found in the literature, to existing robotic hardware. In this paper, we present the ROS-PyBullet Interface, a framework that provides a bridge between the reliable contact/impact simulator PyBullet and the Robot Operating System (ROS). Furthermore, we provide additional utilities for facilitating Human-Robot Interaction (HRI) in the simulated environment. We also present several use-cases that highlight the capabilities and usefulness of our framework. Our code base is open source and can be found at github.com/ros-pybullet/ros pybullet interface.

Original language	English
Title of host publication	Proceedings of the 6th Conference on Robot Learning
Editors	Karen Liu, Dana Kulic, Jeff Ichnowski
Publisher	PMLR
Pages	1-10
Volume	205
Publication status	Published - 8 Mar 2023
Event	The Conference on Robot Learning 2022 - Auckland, New Zealand Duration: 14 Dec 2022 → 18 Dec 2022 Conference number: 6 https://corl2022.org/

Publication series

Name	Proceedings of Machine Learning Research
Publisher	PMLR
Volume	205
ISSN (Electronic)	2640-3498

Conference

Conference	The Conference on Robot Learning 2022
Abbreviated title	CoRL 2022
Country/Territory	New Zealand
City	Auckland
Period	14/12/22 → 18/12/22
Internet address	https://corl2022.org/

Access to Document

ROS-PyBullet Interface_MOWER_DOA10092022_VOR_CC-BYFinal published version, 6.05 MBLicence: Creative Commons: Attribution (CC-BY)

https://proceedings.mlr.press/v205/xiong23a.htmlLicence: Creative Commons: Attribution (CC-BY)

Co-bots and Exoskeletons for Assisted Living with Ergonomic Measures
Vijayakumar, S.
EU other
1/02/21 → 31/12/22
Project: Research
HARMONY: Enhancing Healthcare with Assistive Robotic Mobile Manipulation
Vijayakumar, S., Ivan, V., Khadem, M. & Li, Z.
EU government bodies
1/01/21 → 30/06/24
Project: Research
Turing AI research Programme
Vijayakumar, S.
UK-based charities
1/09/18 → 31/08/23
Project: Research

Cite this

Mower, C. E., Stouraitis, T., Moura, J., Rauch, C., Yan, L., Zamani Behabadi, N., Gienger, M., Vercauteren, T., Bergeles, C., & Vijayakumar, S. (2023). ROS-PyBullet Interface: A Framework for Reliable Contact Simulation and Human-Robot Interaction. In K. Liu, D. Kulic, & J. Ichnowski (Eds.), Proceedings of the 6th Conference on Robot Learning (Vol. 205, pp. 1-10). (Proceedings of Machine Learning Research; Vol. 205). PMLR. https://proceedings.mlr.press/v205/xiong23a.html

@inproceedings{914ec07534e94b8294966d383032b22f,

title = "ROS-PyBullet Interface: A Framework for Reliable Contact Simulation and Human-Robot Interaction",

abstract = "Reliable contact simulation plays a key role in the development of (semi-)autonomous robots, especially when dealing with contact-rich manipulation scenarios, an active robotics research topic. Besides simulation, components such as sensing, perception, data collection, robot hardware control, human interfaces, etc. are all key enablers towards applying machine learning algorithms or model-based approaches in real world systems. However, there is a lack of software connecting reliable contact simulation with the larger robotics ecosystem (i.e. ROS, Orocos), for a more seamless application of novel approaches, found in the literature, to existing robotic hardware. In this paper, we present the ROS-PyBullet Interface, a framework that provides a bridge between the reliable contact/impact simulator PyBullet and the Robot Operating System (ROS). Furthermore, we provide additional utilities for facilitating Human-Robot Interaction (HRI) in the simulated environment. We also present several use-cases that highlight the capabilities and usefulness of our framework. Our code base is open source and can be found at github.com/ros-pybullet/ros pybullet interface.",

author = "Mower, {Christopher E.} and Theodoros Stouraitis and Joao Moura and Christian Rauch and Lei Yan and {Zamani Behabadi}, Nazanin and Michael Gienger and Tom Vercauteren and Christos Bergeles and Sethu Vijayakumar",

note = "This research is supported by The Alan Turing Institute, United Kingdom and has received funding from the European Union{\textquoteright}s Horizon 2020 research and innovation programme under grant agreement No 101017008, Enhancing Healthcare with Assistive Robotic Mobile Manipulation (HARMONY). This work was supported by core funding from the Wellcome/EPSRC [WT203148/Z/16/Z; NS/A000049/1]. This project has received funding from the European Union{\textquoteright}s Horizon 2020 research and innovation programme under grant agreement No 101016985 (FAROS project). This research is supported by Kawada Robotics Corporation and the Honda Research Institute Europe.; The Conference on Robot Learning 2022 , CoRL 2022 ; Conference date: 14-12-2022 Through 18-12-2022",

year = "2023",

month = mar,

day = "8",

language = "English",

volume = "205",

series = "Proceedings of Machine Learning Research",

publisher = "PMLR",

pages = "1--10",

editor = "Karen Liu and Dana Kulic and Jeff Ichnowski",

booktitle = "Proceedings of the 6th Conference on Robot Learning",

url = "https://corl2022.org/",

}

Mower, CE, Stouraitis, T, Moura, J, Rauch, C, Yan, L, Zamani Behabadi, N, Gienger, M, Vercauteren, T, Bergeles, C & Vijayakumar, S 2023, ROS-PyBullet Interface: A Framework for Reliable Contact Simulation and Human-Robot Interaction. in K Liu, D Kulic & J Ichnowski (eds), Proceedings of the 6th Conference on Robot Learning. vol. 205, Proceedings of Machine Learning Research, vol. 205, PMLR, pp. 1-10, The Conference on Robot Learning 2022 , Auckland, New Zealand, 14/12/22. <https://proceedings.mlr.press/v205/xiong23a.html>

ROS-PyBullet Interface: A Framework for Reliable Contact Simulation and Human-Robot Interaction. / Mower, Christopher E.; Stouraitis, Theodoros; Moura, Joao et al.
Proceedings of the 6th Conference on Robot Learning. ed. / Karen Liu; Dana Kulic; Jeff Ichnowski. Vol. 205 PMLR, 2023. p. 1-10 (Proceedings of Machine Learning Research; Vol. 205).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - ROS-PyBullet Interface: A Framework for Reliable Contact Simulation and Human-Robot Interaction

AU - Mower, Christopher E.

AU - Stouraitis, Theodoros

AU - Moura, Joao

AU - Rauch, Christian

AU - Yan, Lei

AU - Zamani Behabadi, Nazanin

AU - Gienger, Michael

AU - Vercauteren, Tom

AU - Bergeles, Christos

AU - Vijayakumar, Sethu

N1 - Conference code: 6

PY - 2023/3/8

Y1 - 2023/3/8

N2 - Reliable contact simulation plays a key role in the development of (semi-)autonomous robots, especially when dealing with contact-rich manipulation scenarios, an active robotics research topic. Besides simulation, components such as sensing, perception, data collection, robot hardware control, human interfaces, etc. are all key enablers towards applying machine learning algorithms or model-based approaches in real world systems. However, there is a lack of software connecting reliable contact simulation with the larger robotics ecosystem (i.e. ROS, Orocos), for a more seamless application of novel approaches, found in the literature, to existing robotic hardware. In this paper, we present the ROS-PyBullet Interface, a framework that provides a bridge between the reliable contact/impact simulator PyBullet and the Robot Operating System (ROS). Furthermore, we provide additional utilities for facilitating Human-Robot Interaction (HRI) in the simulated environment. We also present several use-cases that highlight the capabilities and usefulness of our framework. Our code base is open source and can be found at github.com/ros-pybullet/ros pybullet interface.

AB - Reliable contact simulation plays a key role in the development of (semi-)autonomous robots, especially when dealing with contact-rich manipulation scenarios, an active robotics research topic. Besides simulation, components such as sensing, perception, data collection, robot hardware control, human interfaces, etc. are all key enablers towards applying machine learning algorithms or model-based approaches in real world systems. However, there is a lack of software connecting reliable contact simulation with the larger robotics ecosystem (i.e. ROS, Orocos), for a more seamless application of novel approaches, found in the literature, to existing robotic hardware. In this paper, we present the ROS-PyBullet Interface, a framework that provides a bridge between the reliable contact/impact simulator PyBullet and the Robot Operating System (ROS). Furthermore, we provide additional utilities for facilitating Human-Robot Interaction (HRI) in the simulated environment. We also present several use-cases that highlight the capabilities and usefulness of our framework. Our code base is open source and can be found at github.com/ros-pybullet/ros pybullet interface.

M3 - Conference contribution

VL - 205

T3 - Proceedings of Machine Learning Research

SP - 1

EP - 10

BT - Proceedings of the 6th Conference on Robot Learning

A2 - Liu, Karen

A2 - Kulic, Dana

A2 - Ichnowski, Jeff

PB - PMLR

T2 - The Conference on Robot Learning 2022

Y2 - 14 December 2022 through 18 December 2022

ER -

ROS-PyBullet Interface: A Framework for Reliable Contact Simulation and Human-Robot Interaction

Abstract / Description of output

Publication series

Conference

Access to Document

Fingerprint

Projects

Co-bots and Exoskeletons for Assisted Living with Ergonomic Measures

HARMONY: Enhancing Healthcare with Assistive Robotic Mobile Manipulation

Turing AI research Programme

Cite this