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

Area of Science:

• Robotics and Automation
• Radiation Safety Engineering
• Nuclear Engineering

Background:

• Human operators in hazardous environments minimize risk, including limiting exposure to ionizing radiation.
• Robots operating in similar environments face risks of electronic and material damage from radiation.
• Reducing robot radiation exposure enhances operational longevity and return on investment for nuclear sector stakeholders.

Purpose of the Study:

• To develop and demonstrate a radiation avoidance system for robots operating in hazardous environments.
• To minimize accumulated radiation dose for robots, thereby extending their functional lifespan.
• To enhance the safety and economic viability of robotic operations in the nuclear industry.

Main Methods:

• Implementation of layered costmaps to integrate radiation risk into robot path planning algorithms.
• Utilizing an inverse distance weighting approach for interpolating radiation observations into the robot's configuration space.
• Demonstration using an unmanned ground vehicle (UGV) with gamma radiation sensors in simulation and real-world scenarios.

Main Results:

• Successful demonstration of radiation avoidance capabilities in both simulated and real-world environments.
• Achieved reduction of total accumulated radiation dose to background levels during real-world mock inspection missions.
• Up to a tenfold reduction in simulated accumulated radiation dose was observed with the implemented system.

Conclusions:

• Layered costmaps effectively inform path planning for radiation avoidance in robotic systems.
• The developed technique significantly reduces robot exposure to ionizing radiation.
• This approach offers a practical solution for extending robot operational life and improving ROI in radiation-affected industries.