Robotics for Nuclear Sites
A new research direction at our lab is related to that of robotized inspection, monitoring and potentially maintenance of nuclear sites. Our current efforts emphasize in the direction of autonomous and comprehensive multi-modal characterization of nuclear sites. The relevant research is supported by the NRI:Collaborative Research: Multi-Modal Characterization of DOE-EM Facilities" funded by the Department of Energy. In this project, we partner with the Robotics Institute of Carnegie Mellon University and PIs Sebastian Scherer and Red Whittaker. CMU is the lead institution for this project.
It is highlighted that our work on autonomous exploration and mapping in degraded visual environments is highly relevant and to a certain extent also specific to this project. However, beyond the 3D mapping capabilities of the robot, we envisioned accurate radiation detection and fusion of these sensor readings with the 3D maps of the environment.
It is highlighted that our work on autonomous exploration and mapping in degraded visual environments is highly relevant and to a certain extent also specific to this project. However, beyond the 3D mapping capabilities of the robot, we envisioned accurate radiation detection and fusion of these sensor readings with the 3D maps of the environment.
Radiation Source Localization in GPS-denied Environments using Aerial Robots
.In this paper we present the system and methods to enable autonomous nuclear radiation source localization using aerial robots in GPS-denied environments. The presented results refer to the localization of a Cesium-137 source using a small aerial robot both with and without any prior knowledge of its environment
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Autonomous 3D and Radiation Mapping in Tunnel Environments using Aerial Robots
This video presents results on autonomous radiation mapping and source localization in tunnel environments using aerial robots.
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A Multi-Modal Mapping Unit for Autonomous Exploration and Mapping of Underground TunnelsThis video presents results on autonomous exploration and mapping of tunnel environments using the developed Multi-Modal Mapping Unit (M3U). The M3U tightly synchronized a stereo camera pair with an Inertial Measurement Unit and super-bright flashing LEDs, while it further fuses time-of-flight 3D depth sensors. It allows for GPS-denied localization and mapping visually-degraded environments.
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Autonomous Aerial Robotic Exploration and Mapping of a Railroad Tunnel in Degraded Visual Conditions This video presents indicative results of a sequence of field experiments conducted to verify and evaluate new algorithms and systems for autonomous exploration and mapping of tunnel environments using aerial robots.
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Preliminary results on Aerial Robotic Radiation DetectionThis experiment presents preliminary results towards radiation detection and mapping using aerial robots.
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A Multi-Modal Mapping Unit for Autonomous Exploration and Mapping of Underground TunnelsThis video presents results on autonomous exploration and mapping of tunnel environments using the developed Multi-Modal Mapping Unit (M3U). The M3U tightly synchronized a stereo camera pair with an Inertial Measurement Unit and super-bright flashing LEDs, while it further fuses time-of-flight 3D depth sensors. It allows for GPS-denied localization and mapping visually-degraded environments.
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Autonomous Exploration in Darkness using NIR Visual-Inertial-Depth Localization and Mapping This video presents our work on autonomous exploration and mapping of dark, visually-degraded environments. The system employs a NIR visual-inertial localization system augmented with a 3D time-of-flight depth sensor. Exploiting an uncertainty-aware receding horizon exploration and mapping planner, the robot operates autonomously in environment for which no prior knowledge is available.
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Uncertainty-aware Exploration and Mapping using Aerial Robots
This planner follows a two–step, receding horizon, belief space–based approach. At first, in an online computed tree the algorithm finds the branch that optimizes the amount of space expected to be explored. The first viewpoint is selected, but the path towards it is decided through a second planning step that aims to minimized the robots expected localization uncertainty
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Preliminary work on mapping in Visually-degraded Environments
These are preliminary results on exploration and mapping inside a tunnel with approximate dimensions of WIDTHxHEIGHTxLENGTH = 3x4x30m. The robot navigated along half of it (approximately) and our team evaluated the capability of localization and mapping using NIR camera/IMU, as well as Laser Time-of-Flight sensors.
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Visual Saliency-aware Receding Horizon Autonomous Exploration with Application to Aerial Robotics
In this video we present autonomous visual saliency-aware receding horizon exploration using aerial robots. The presented results refer to the exploration of two environments with different salient objects, namely a room with paintings and a mannequin, as well as a machine shop that includes salient objects such as warning signs and a fire extinguisher.
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Our contributions in the field can be found in the following papers:
- Christos Papachristos, Kostas Alexis, "Autonomous Detection and Classification of Change using Aerial Robots", IEEE Aerospace Conference, 2017, Yellowstone Conference Center, Big Sky, Montana, March 4-11, 2017
- Christos Papachristos, Shehryar Khattak, Kostas Alexis, "Uncertainty-aware Receding Horizon Exploration and Mapping using Aerial Robots", IEEE International Conference on Robotics and Automation (ICRA), May 29-June 3, 2017, Singapore
- C. Papachristos, S. Khattak, K. Alexis, "Autonomous Exploration of Visually-Degraded Environments using Aerial Robots", International Conference on Unmanned Aircraft Systems (ICUAS), 2017
- F. Mascarich, T. Wilson, T. Dang, S. Khattak, C. Papachristos, K. Alexis, "Towards Robotically Supported Decommissioning of Nuclear Sites." arXiv preprint arXiv:1705.06401 (2017).
- F. Mascarich, S. Khattak, C. Papachristos, K. Alexis, "A Multi-Modal Mapping Unit for Autonomous Exploration and Mapping of Underground Tunnels", IEEE Aerospace Conference (AeroConf) 2016, Yellowstone Conference, Big Sky, Montana, March 3-10, 2018
- Frank Mascarich, Taylor Wilson, Christos Papachristos, and Kostas Alexis, "Radiation Source Localization in GPS-denied Environments using Aerial Robots", IEEE International Conference on Robotics and Automation (ICRA), May 21-25, 2018, Brisbane, Australia
- F. Mascarich, T. Wilson, Shehryar Khattak, T. Dang, and K. Alexis, "Autonomous 3D and Radiation Mapping in Tunnel Environments Using Aerial Robots", Waste Management Symposia 2018, March 18-22, Phoenix, USA
Open Source Contributions:
- Uncertainty-aware Receding Horizon Exploration and Mapping Planner (RHEM): https://github.com/unr-arl/rhem_planner