Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Radiation Surveys in Active Nuclear Facilities with Heterogeneous Collaborative Mobile Robots

Mitchell Pryor, Alex Navarro, Janak Panthi, Kevin Torres, Mary Tebben, Daniel Meza, Caleb Horan, Alex Macris

TL;DR

This paper addresses the risk and incompleteness of manual radiation surveys in active nuclear facilities by proposing a heterogeneous Robot Radiation Survey System (RRSS) composed of Minibot, Magni, and Alph. The approach distributes surveying tasks across specialized robots: Minibot performs under-table mapping, Magni conducts efficient floor alpha/beta/gamma surveys with a large detector, and Alph handles elevated-surface surveys and obstacle clearing, all coordinated via a central server. Key contributions include a full-stack integration with multi-robot mapping, 3D obstacle-aware planar coverage planning, velocity optimization tied to detector performance through $C_T = L_{D} A_{d} \, \epsilon_{d}$, affordance-template-based manipulation, precision swipe control, task virtual fixtures for surface coverage, and Temoto-based fault tolerance. The work demonstrates integrated demo scenarios and outlines next steps toward robust, autonomous, night-time radiation surveys with cybersecurity and ROS2 port considerations, aiming to reduce radiation exposure and improve repeatability of contamination maps. $\mathcal{L}$

Abstract

Nuclear facilities must routinely survey their infrastructure for radiation contamination. Generally, this is done by trained professionals, wearing personal protective equipment (PPE) that swipe potentially contaminated surfaces and test the wipes under detectors. This approach leaves personnel vulnerable to radiation exposure and is not comprehensive. Robots address these inadequacies, offering a cost-effective solution with negligible downtime. We present a Robot Radiation Survey System (RRSS): a heterogeneous robot team to perform comprehensive alpha/beta/gamma radiation surveys. The RRSS system members, core capabilities, and comprehensive survey plan are addresses in this paper.

Radiation Surveys in Active Nuclear Facilities with Heterogeneous Collaborative Mobile Robots

TL;DR

This paper addresses the risk and incompleteness of manual radiation surveys in active nuclear facilities by proposing a heterogeneous Robot Radiation Survey System (RRSS) composed of Minibot, Magni, and Alph. The approach distributes surveying tasks across specialized robots: Minibot performs under-table mapping, Magni conducts efficient floor alpha/beta/gamma surveys with a large detector, and Alph handles elevated-surface surveys and obstacle clearing, all coordinated via a central server. Key contributions include a full-stack integration with multi-robot mapping, 3D obstacle-aware planar coverage planning, velocity optimization tied to detector performance through , affordance-template-based manipulation, precision swipe control, task virtual fixtures for surface coverage, and Temoto-based fault tolerance. The work demonstrates integrated demo scenarios and outlines next steps toward robust, autonomous, night-time radiation surveys with cybersecurity and ROS2 port considerations, aiming to reduce radiation exposure and improve repeatability of contamination maps.

Abstract

Nuclear facilities must routinely survey their infrastructure for radiation contamination. Generally, this is done by trained professionals, wearing personal protective equipment (PPE) that swipe potentially contaminated surfaces and test the wipes under detectors. This approach leaves personnel vulnerable to radiation exposure and is not comprehensive. Robots address these inadequacies, offering a cost-effective solution with negligible downtime. We present a Robot Radiation Survey System (RRSS): a heterogeneous robot team to perform comprehensive alpha/beta/gamma radiation surveys. The RRSS system members, core capabilities, and comprehensive survey plan are addresses in this paper.
Paper Structure (15 sections, 1 equation, 12 figures)

This paper contains 15 sections, 1 equation, 12 figures.

Table of Contents

  1. Introduction
  2. System Overview
  3. Minibot(s):
  4. Magni:
  5. Alph:
  6. System Components And Results
  7. Multi-Robot Mapping and Exploration:
  8. Planar Coverage Path Planning:
  9. Robot Velocity Optimization:
  10. Affordance Templates:
  11. Precision Manipulator Control for Contact Radiation Detection:
  12. Task Virtual Fixtures:
  13. Temoto:
  14. Integrated Demo Description
  15. Conclusion

Figures (12)

  • Figure 1: Minibot
  • Figure 2: Magni Robot
  • Figure 3: Manipulator-integrated Alph
  • Figure 4: Cylinder Decomposition of Magni Robot
  • Figure 5: Kinematic Transition Test
  • ...and 7 more figures