Planning for a Tight Squeeze: Navigation of Morphing Soft Robots in Congested Environments

Edward Gough; Andrew T. Conn; Jonathan Rossiter

doi:10.1109/LRA.2021.3067594

Planning for a Tight Squeeze: Navigation of Morphing Soft Robots in Congested Environments

Edward Gough^*, Andrew T. Conn, Jonathan Rossiter

^*Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

13 Citations (Scopus)

235 Downloads (Pure)

Abstract

Autonomous navigation methods can prevent robots becoming trapped between obstacles and ensure that they take the most efficient route. As mobile robots have a limited power supply, selecting the most efficient route is crucial. This letter presents a path-planning method for morphing soft robots in congested environments. The proposed method is suitable for all scales of robots and environments, from intra-organ biomedical navigation to search-and-rescue operations in cave networks. The method utilizes 3D Voronoi diagrams and Dijkstra's algorithm to calculate an optimal path that balances cost between the size and shape change of the robot and the length of the path. The Voronoi method is particularly suitable for circumferentially expanding robots because the waypoints generated lay where a device with a circular cross-section would naturally sit. The method is demonstrated by simulation in procedurally generated environments with either spherical or continuous obstacles to illustrate the effectiveness of the method for in-situ planning and as an aid to design. This letter provides a generic approach that has the potential to be easily adapted for many applications across healthcare, industry and space exploration.

Original language	English
Pages (from-to)	4752-4757
Number of pages	6
Journal	IEEE Robotics and Automation Letters
Volume	6
Issue number	3
DOIs	https://doi.org/10.1109/LRA.2021.3067594
Publication status	Published - 19 Mar 2021

Bibliographical note

Funding Information:
Manuscript received October 15, 2020; accepted February 20, 2021. Date of publication March 19, 2021; date of current version April 13, 2021. This letter was recommended for publication by Associate Editor C. Onal and Editor C. Laschi upon evaluation of the reviewers. comments. The work of Edward Gough was supported in part by the EPSRC Centre for Doctoral Training in Future Autonomous, and Robotic Systems (FARSCOPE), and in part by BT Applied Research through the EPSRC iCASE scheme. The work of Jonathan Rossiter was supported in part by through EPSRC research under Grants EP/S026096/1, EP/R02961X/1, and EP/M020460/1, and by in part by the Royal Academy of Engineering as a Chair in Emerging Technologies. The work of Andrew T. Conn was supported by EPSRC under Grant EP/R02961X/1. (Corresponding author: Edward Gough.) Edward Gough is with the FARSCOPE CDT, Bristol Robotics Laboratory, Bristol BS34 8QZ, U.K. (e-mail: [email protected]).

Publisher Copyright:
© 2016 IEEE.

Keywords

Learning for soft robots
control
modeling
motion and path planning

Access to Document

10.1109/LRA.2021.3067594Licence: Unspecified

Full-text PDF (author’s accepted manuscript)
This is the author accepted manuscript (AAM). The final published version (version of record) is available online via IEEE at https://ieeexplore.ieee.org/document/9382069 . Please refer to any applicable terms of use of the publisher.
Accepted author manuscript, 2.86 MB

Handle.net

Persistent link

Cite this

@article{6f2310004878459a83c27d2cdfbb68a3,

title = "Planning for a Tight Squeeze: Navigation of Morphing Soft Robots in Congested Environments",

abstract = "Autonomous navigation methods can prevent robots becoming trapped between obstacles and ensure that they take the most efficient route. As mobile robots have a limited power supply, selecting the most efficient route is crucial. This letter presents a path-planning method for morphing soft robots in congested environments. The proposed method is suitable for all scales of robots and environments, from intra-organ biomedical navigation to search-and-rescue operations in cave networks. The method utilizes 3D Voronoi diagrams and Dijkstra's algorithm to calculate an optimal path that balances cost between the size and shape change of the robot and the length of the path. The Voronoi method is particularly suitable for circumferentially expanding robots because the waypoints generated lay where a device with a circular cross-section would naturally sit. The method is demonstrated by simulation in procedurally generated environments with either spherical or continuous obstacles to illustrate the effectiveness of the method for in-situ planning and as an aid to design. This letter provides a generic approach that has the potential to be easily adapted for many applications across healthcare, industry and space exploration.",

keywords = "Learning for soft robots, control, modeling, motion and path planning",

author = "Edward Gough and Conn, {Andrew T.} and Jonathan Rossiter",

note = "Funding Information: Manuscript received October 15, 2020; accepted February 20, 2021. Date of publication March 19, 2021; date of current version April 13, 2021. This letter was recommended for publication by Associate Editor C. Onal and Editor C. Laschi upon evaluation of the reviewers. comments. The work of Edward Gough was supported in part by the EPSRC Centre for Doctoral Training in Future Autonomous, and Robotic Systems (FARSCOPE), and in part by BT Applied Research through the EPSRC iCASE scheme. The work of Jonathan Rossiter was supported in part by through EPSRC research under Grants EP/S026096/1, EP/R02961X/1, and EP/M020460/1, and by in part by the Royal Academy of Engineering as a Chair in Emerging Technologies. The work of Andrew T. Conn was supported by EPSRC under Grant EP/R02961X/1. (Corresponding author: Edward Gough.) Edward Gough is with the FARSCOPE CDT, Bristol Robotics Laboratory, Bristol BS34 8QZ, U.K. (e-mail: [email protected]). Publisher Copyright: {\textcopyright} 2016 IEEE.",

year = "2021",

month = mar,

day = "19",

doi = "10.1109/LRA.2021.3067594",

language = "English",

volume = "6",

pages = "4752--4757",

journal = "IEEE Robotics and Automation Letters",

issn = "2377-3766",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

number = "3",

}

TY - JOUR

T1 - Planning for a Tight Squeeze

T2 - Navigation of Morphing Soft Robots in Congested Environments

AU - Gough, Edward

AU - Conn, Andrew T.

AU - Rossiter, Jonathan

N1 - Funding Information: Manuscript received October 15, 2020; accepted February 20, 2021. Date of publication March 19, 2021; date of current version April 13, 2021. This letter was recommended for publication by Associate Editor C. Onal and Editor C. Laschi upon evaluation of the reviewers. comments. The work of Edward Gough was supported in part by the EPSRC Centre for Doctoral Training in Future Autonomous, and Robotic Systems (FARSCOPE), and in part by BT Applied Research through the EPSRC iCASE scheme. The work of Jonathan Rossiter was supported in part by through EPSRC research under Grants EP/S026096/1, EP/R02961X/1, and EP/M020460/1, and by in part by the Royal Academy of Engineering as a Chair in Emerging Technologies. The work of Andrew T. Conn was supported by EPSRC under Grant EP/R02961X/1. (Corresponding author: Edward Gough.) Edward Gough is with the FARSCOPE CDT, Bristol Robotics Laboratory, Bristol BS34 8QZ, U.K. (e-mail: [email protected]). Publisher Copyright: © 2016 IEEE.

PY - 2021/3/19

Y1 - 2021/3/19

N2 - Autonomous navigation methods can prevent robots becoming trapped between obstacles and ensure that they take the most efficient route. As mobile robots have a limited power supply, selecting the most efficient route is crucial. This letter presents a path-planning method for morphing soft robots in congested environments. The proposed method is suitable for all scales of robots and environments, from intra-organ biomedical navigation to search-and-rescue operations in cave networks. The method utilizes 3D Voronoi diagrams and Dijkstra's algorithm to calculate an optimal path that balances cost between the size and shape change of the robot and the length of the path. The Voronoi method is particularly suitable for circumferentially expanding robots because the waypoints generated lay where a device with a circular cross-section would naturally sit. The method is demonstrated by simulation in procedurally generated environments with either spherical or continuous obstacles to illustrate the effectiveness of the method for in-situ planning and as an aid to design. This letter provides a generic approach that has the potential to be easily adapted for many applications across healthcare, industry and space exploration.

AB - Autonomous navigation methods can prevent robots becoming trapped between obstacles and ensure that they take the most efficient route. As mobile robots have a limited power supply, selecting the most efficient route is crucial. This letter presents a path-planning method for morphing soft robots in congested environments. The proposed method is suitable for all scales of robots and environments, from intra-organ biomedical navigation to search-and-rescue operations in cave networks. The method utilizes 3D Voronoi diagrams and Dijkstra's algorithm to calculate an optimal path that balances cost between the size and shape change of the robot and the length of the path. The Voronoi method is particularly suitable for circumferentially expanding robots because the waypoints generated lay where a device with a circular cross-section would naturally sit. The method is demonstrated by simulation in procedurally generated environments with either spherical or continuous obstacles to illustrate the effectiveness of the method for in-situ planning and as an aid to design. This letter provides a generic approach that has the potential to be easily adapted for many applications across healthcare, industry and space exploration.

KW - Learning for soft robots

KW - control

KW - modeling

KW - motion and path planning

U2 - 10.1109/LRA.2021.3067594

DO - 10.1109/LRA.2021.3067594

M3 - Article (Academic Journal)

SN - 2377-3766

VL - 6

SP - 4752

EP - 4757

JO - IEEE Robotics and Automation Letters

JF - IEEE Robotics and Automation Letters

IS - 3

ER -

Planning for a Tight Squeeze: Navigation of Morphing Soft Robots in Congested Environments

Abstract

Bibliographical note

Keywords

Access to Document

Handle.net

Fingerprint

Cite this