Litcius/Paper detail

Efficient Coverage Path Planning for Mobile Disinfecting Robots Using Graph-Based Representation of Environment

B. Nasirian, Mehran Mehrandezh, Farrokh Janabi‐Sharifi

2021Frontiers in Robotics and AI49 citationsDOIOpen Access PDF

Abstract

The effective disinfection of hospitals is paramount in lowering the COVID-19 transmission risk to both patients and medical personnel. Autonomous mobile robots can perform the surface disinfection task in a timely and cost-effective manner, while preventing the direct contact of disinfecting agents with humans. This paper proposes an end-to-end coverage path planning technique that generates a continuous and uninterrupted collision-free path for a mobile robot to cover an area of interest. The aim of this work is to decrease the disinfection task completion time and cost by finding an optimal coverage path using a new graph-based representation of the environment. The results are compared with other existing state-of-the-art coverage path planning approaches. It is shown that the proposed approach generates a path with shorter total travelled distance (fewer number of overlaps) and smaller number of turns.

Topics & Concepts

Computer scienceMotion planningPath (computing)Mobile robotGraphRobotRepresentation (politics)Task (project management)Any-angle path planningReal-time computingArtificial intelligenceComputer networkTheoretical computer scienceLawPoliticsPolitical scienceManagementEconomicsRobotic Path Planning AlgorithmsRobotics and Sensor-Based LocalizationModular Robots and Swarm Intelligence