Radiation Avoidance using Layered Costmaps
Posted on 2022-02-08 - 19:47 authored by Andrew West
Dose rate data collected both in simulation, and in real-world deployments for instruments mounted to an Unmanned Ground Vehicle (UGV), which demonstrate the use of layered costmaps to allow robots to avoid ionising radiation. Point radiation intensity observations are interpolated into a 2D representation of the radiation field, which the robot path planning and navigation functionality can use to avoid areas of increased risk.
Real-world deployment was undertaken at the Lancaster University Neutron Laboratory, using a Clearpath Jackal UGV, equipped with a CeBr3 detector with a mixed field analyser. The robot was exposed to gamma/neutron from a Cf-252 source. In simulation, a Clearpath Jackal UGV representation was exposed to gamma emissions provided by a radiation source plugin for Gazebo.
When radiation awareness is enabled, the robot is capable of reducing its accumulated ionising radiation dose, both for known and unknown environments, and as part of autonomous activities such as exploration.
Data was collected as part of the TORONE project and the RAIN hub.
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West, Andrew (2022). Radiation Avoidance using Layered Costmaps. University of Manchester. Collection. https://doi.org/10.48420/c.5801636.v1
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FUNDING
TORONE - TOtal characterisation for Remote Observation in Nuclear Environments
Engineering and Physical Sciences Research Council
Robotics and Artificial Intelligence for Nuclear (RAIN)
Department for Business, Energy and Industrial Strategy
