TY - JOUR
T1 - A Comprehensive Survey on Coverage Path Planning for Mobile Robots in Dynamic Environments
AU - Jayalakshmi, K. P.
AU - Nair, Vishnu G.
AU - Sathish, Dayakshini
N1 - Publisher Copyright:
© IEEE. 2013 IEEE.
PY - 2025
Y1 - 2025
N2 - Coverage Path Planning (CPP) is a fundamental aspect of mobile robotics, enabling robots to navigate dynamic environments efficiently while ensuring thorough coverage of all areas of interest and avoiding obstacles. CPP is pivotal in diverse applications, from everyday tasks like vacuum cleaning, lawn mowing, and window cleaning to specialized operations such as demining hazardous areas, autonomous underwater imaging, and inspecting complex structures. This survey reviews recent advancements in CPP, focusing on algorithms and methodologies tailored for dynamic environments. It highlights the challenges posed by environmental variability, obstacle dynamics, and real-time computational demands. By synthesizing insights from existing research, this survey aims to guide future developments in CPP, paving the way for smarter and more adaptive robotic systems capable of handling the complexities of real-world scenarios.
AB - Coverage Path Planning (CPP) is a fundamental aspect of mobile robotics, enabling robots to navigate dynamic environments efficiently while ensuring thorough coverage of all areas of interest and avoiding obstacles. CPP is pivotal in diverse applications, from everyday tasks like vacuum cleaning, lawn mowing, and window cleaning to specialized operations such as demining hazardous areas, autonomous underwater imaging, and inspecting complex structures. This survey reviews recent advancements in CPP, focusing on algorithms and methodologies tailored for dynamic environments. It highlights the challenges posed by environmental variability, obstacle dynamics, and real-time computational demands. By synthesizing insights from existing research, this survey aims to guide future developments in CPP, paving the way for smarter and more adaptive robotic systems capable of handling the complexities of real-world scenarios.
UR - https://www.scopus.com/pages/publications/105002035251
UR - https://www.scopus.com/pages/publications/105002035251#tab=citedBy
U2 - 10.1109/ACCESS.2025.3556446
DO - 10.1109/ACCESS.2025.3556446
M3 - Review article
AN - SCOPUS:105002035251
SN - 2169-3536
VL - 13
SP - 60158
EP - 60185
JO - IEEE Access
JF - IEEE Access
ER -