Real-Time Avoidance of Ionising Radiation Using Layered Costmaps for Mobile Robots

Humans in hazardous environments take actions to reduce unnecessary risk, including limiting exposure to radioactive materials where ionising radiation can be a threat to human health. Robots can adopt the same approach of risk avoidance to minimise exposure to radiation, therefore limiting damage t...

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Bibliographic Details
Main Authors: Groves, K. (Author), Joyce, M.J (Author), Lennox, B. (Author), Tsitsimpelis, I. (Author), West, A. (Author), Wright, T. (Author)
Format: Article
Language:English
Published: Frontiers Media S.A. 2022
Subjects:
ROS
Online Access:View Fulltext in Publisher
LEADER 02186nam a2200289Ia 4500
001 10.3389-frobt.2022.862067
008 220425s2022 CNT 000 0 und d
020 |a 22969144 (ISSN) 
245 1 0 |a Real-Time Avoidance of Ionising Radiation Using Layered Costmaps for Mobile Robots 
260 0 |b Frontiers Media S.A.  |c 2022 
856 |z View Fulltext in Publisher  |u https://doi.org/10.3389/frobt.2022.862067 
520 3 |a Humans in hazardous environments take actions to reduce unnecessary risk, including limiting exposure to radioactive materials where ionising radiation can be a threat to human health. Robots can adopt the same approach of risk avoidance to minimise exposure to radiation, therefore limiting damage to electronics and materials. Reducing a robot’s exposure to radiation results in longer operational lifetime and better return on investment for nuclear sector stakeholders. This work achieves radiation avoidance through the use of layered costmaps, to inform path planning algorithms of this additional risk. Interpolation of radiation observations into the configuration space of the robot is accomplished using an inverse distance weighting approach. This technique was successfully demonstrated using an unmanned ground vehicle running the Robot Operating System equipped with compatible gamma radiation sensors, both in simulation and in real-world mock inspection missions, where the vehicle was exposed to radioactive materials in Lancaster University’s Neutron Laboratory. The addition of radiation avoidance functionality was shown to reduce total accumulated dose to background levels in real-world deployment and up to a factor of 10 in simulation. Copyright © 2022 West, Wright, Tsitsimpelis, Groves, Joyce and Lennox. 
650 0 4 |a ALARA 
650 0 4 |a ALARP 
650 0 4 |a autonomy 
650 0 4 |a field robotics 
650 0 4 |a inspection 
650 0 4 |a nuclear 
650 0 4 |a radiation 
650 0 4 |a ROS 
700 1 |a Groves, K.  |e author 
700 1 |a Joyce, M.J.  |e author 
700 1 |a Lennox, B.  |e author 
700 1 |a Tsitsimpelis, I.  |e author 
700 1 |a West, A.  |e author 
700 1 |a Wright, T.  |e author 
773 |t Frontiers in Robotics and AI