Sim-to-Real Transfer of Deep Reinforcement Learning Agents for Online Coverage Path Planning

Sim-to-Real Transfer of Deep Reinforcement Learning Agents for Online Coverage Path Planning

Coverage path planning (CPP) is the problem of finding a path that covers the entire free space of a confined area, with applications ranging from robotic lawn mowing to search-and-rescue. While for known environments, offline methods can find provably complete paths, and in some cases optimal solut...

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Bibliographic Details
Main Authors: Arvi Jonnarth, Ola Johansson, Jie Zhao, Michael Felsberg
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Coverage path planning
end-to-end learning
exploration
online
real-time
reinforcement learning
Online Access:https://ieeexplore.ieee.org/document/11039829/
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