Self-Navigating Robotic Assistant for Long-term Wide Area Floor Contamination Monitoring - 18213
- University of Texas, Austin, Nuclear Robotics Group 10100 Burnet Road Bldg 160 Rm 1.108 MC R8600, Austin TX 78758 (United States)
For Routine Contamination Testing (RCT) of an operational nuclear facility or one undergoing Decontamination and Decommissioning (D and D), workers utilize specified travel corridors (enclosed hallways or areas designated with tape or rope in open spaces) to minimize the risk of spreading contamination. Radiation health technicians must continually monitor these areas for contamination to minimize worker dose and prevent its spread to uncontrolled areas. For many sites, it is impractical for the technician to adequately survey such areas. The Nuclear Robotics Group (NRG) at UT Austin has developed a self-navigating robotic platform equipped with radiation detectors to augment the technician to improve both survey coverage and frequency. While maintaining a controlled velocity and floor-to-sensor distance, the system takes radiation measurements to identify and/or localize contamination sources. Readings above background levels are reported to a remote workstation to allow technicians to then respond accordingly. The completion of these mundane tasks by a robot allows the trained technicians to focus instead on operational tasks, D and D, or responding to alarms. The robot generates a map using a Lidar range sensor with established Simultaneous Localization and Mapping (SLAM) techniques. Range data is then compared to previously generated maps for robot localization and autonomous navigation. To maximize coverage, the robot executes a Complete Coverage Path Planning (CCPP) algorithm using a static map that is discretized into cells to assure comprehensive yet efficient coverage. As the system executes the generated plan, it builds a radiation map of the area for the technician to validate and verify the results. If contamination is detected, the robot will minimize the spread of contamination by stopping, sounding an alarm, and alerting the remote technician. The proposed system allows for long-term deployment with minimal human intervention. It is robust to both highly dynamic obstacles (i.e. personnel) and low dynamic changes (i.e. temporally stored cart) in the environment. This is accomplished through continuous spatiotemporal updating of the static map, and the utilization of a supervisory controller that allows the system to reliably respond to unexpected events or states (i.e. low battery, closed door, etc.). While the supervisory controller can respond to temporary complications, the system also recognizes the environment can change slowly over time necessitating that the CCPP automatically be updated to account for observed 'permanent' changes to the environment. To do this, the robot uses intermediate probabilistic data to make intelligent planning decisions offline while still maintaining local reactive obstacle avoidance and safety features. The self-updating of the map allows the robot to run longer without the need to remake the map, leading to more consistent monitoring data and less maintenance from the human technician. This paper will review the current system hardware, the CCPP algorithm, the supervisory controller, the probabilistic algorithm for identifying permanent changes, and recent experiments at UT Austin to experimentally validate the reported sensor coverage. (authors)
- Research Organization:
- WM Symposia, Inc., PO Box 27646, 85285-7646 Tempe, AZ (United States)
- OSTI ID:
- 22975385
- Report Number(s):
- INIS-US-20-WM-18213; TRN: US21V0199015427
- Resource Relation:
- Conference: WM2018: 44. Annual Waste Management Conference, Phoenix, AZ (United States), 18-22 Mar 2018; Other Information: Country of input: France; 46 refs.; Available online at: https://www.xcdsystem.com/wmsym/2018/index.html
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY
ALGORITHMS
AUTOMATION
COMPUTERIZED SIMULATION
DECOMMISSIONING
DECONTAMINATION
DOSE LIMITS
OPTICAL RADAR
PROBABILISTIC ESTIMATION
RADIATION DETECTORS
RADIATION HAZARDS
RADIATION MONITORING
RADIATION PROTECTION
REMOTE CONTROL
REMOTE SENSING
ROBOTS
SURFACE CONTAMINATION
TEXAS