Complete Coverage Path Planning for Omnidirectional Expand and Collapse Robot Panthera

Autonomous mobile robots (AMRs) face challenges in efficiently covering complex environments. To navigate narrow and expansive areas, AMRs must have two essential attributes: compact size for confined spaces and larger size with omnidirectional locomotion for broader spaces. This study utilizes omni...

Full description

Saved in:
Bibliographic Details
Main Authors: Yi, Lim, Sang, Ash Wan Yaw, Hayat, Abdullah Aamir, Tang, Qinrui, Le, Anh Vu, Elara, Mohan Rajesh
Format: Conference Proceeding
Language:English
Subjects:
Faces
Intelligent robots
Mobile robots
Navigation
Path planning
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Autonomous mobile robots (AMRs) face challenges in efficiently covering complex environments. To navigate narrow and expansive areas, AMRs must have two essential attributes: compact size for confined spaces and larger size with omnidirectional locomotion for broader spaces. This study utilizes omnidirectional expand and collapse robots (OECRs) to demonstrate efficient area coverage. OECRs can collapse to navigate through confined spaces and expand for efficient coverage in broad spaces. However, current complete coverage path planning (CCPP) methods do not account for the expanded and collapsed states of OECRs. To address this, a depth-first search (DFS) approach is proposed for OECRs' CCPP, which can adjust the robotic footprint along the CCPP path to reduce path length. The proposed DFS outperforms the state-of-the-art CCPP in terms of increased area coverage and reduced distance traveled on a selected map.
ISSN:2153-0866
DOI:10.1109/IROS55552.2023.10342525