2023
DOI: 10.1016/j.robot.2023.104417
|View full text |Cite
|
Sign up to set email alerts
|

Self-reconfiguration of PARTS: A parallel reconfiguration algorithm based on surface flow

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1

Citation Types

0
4
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
3

Relationship

1
2

Authors

Journals

citations
Cited by 3 publications
(4 citation statements)
references
References 37 publications
0
4
0
Order By: Relevance
“…In previous self-reconfiguration frameworks for PARTS based on single module movement along the surface of the robot [16,17], the closing condition (see Section 3.2) was relaxed to allow kinematic loops with only three participating ATCs. Although this simplifies the reconfiguration approach, such a relaxation requires an edge elongation ratio of at least √ 3, which is not feasible with the existing hardware implementation of PARTS.…”
Section: Topological Reconfigurationmentioning
confidence: 99%
See 3 more Smart Citations
“…In previous self-reconfiguration frameworks for PARTS based on single module movement along the surface of the robot [16,17], the closing condition (see Section 3.2) was relaxed to allow kinematic loops with only three participating ATCs. Although this simplifies the reconfiguration approach, such a relaxation requires an edge elongation ratio of at least √ 3, which is not feasible with the existing hardware implementation of PARTS.…”
Section: Topological Reconfigurationmentioning
confidence: 99%
“…The reconfiguration workflow presented in Section 4.1 is employed on a sample configuration consisting of 62 ATCs. Similar to our previous work [17], the largest common topology is identified and source regions and sink regions for modules are determined. Source regions define topological locations with a surplus of ATCs, while sink regions are surface positions that need to be occupied to form the final configuration.…”
Section: Reconfiguration Examplementioning
confidence: 99%
See 2 more Smart Citations