​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. 

For the element of VI-localization we are using ROVIO developed at ASL, ETH Zurich: https://github.com/ethz-asl/rovio 

The nightvision cameras are supported with appropriately synchronized LEDs.

This result corresponds to preliminary work in the field of autonomous exploration and mapping in visually-degraded environments.

Our full-day workshop proposal on "Autonomous Structural Monitoring and Maintenance using Aerial Robots", organized by Kostas Alexis (corresponding organizer), Markus W. Achtelik, Gianluca Antonelli, Margarita Chli, Anibal Ollero, Roland Siegwart, Kimon Valavanis was accepted as a full-day workshop at ICRA 2017. Further details will be posted on:  http://www.aerial-monitoring-maintenance-workshop.com/ 

Our paper:

• 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

just got accepted!

Our lab worked together with the Robotics Institute of of Carnegie Mellon University (Dr. Red Whitaker, Dr. Sebastian Scherer) and successfully got awarded the following project!

• NRI: Collaborative Research: Multi-Modal Characterization of DOE-EM Facilities - this National Robotics Initiative project is funded by DOE and aims to provide new autonomous robotic systems to monitor, inspection and multi-modal (Rad/Chem/3D) map nuclear facilities. 

Our lab had a day-long meeting with NSTec from the Nevada National Security Site and gave a demo of Autonomous Exploration and Mapping in Unknown GPS-denied environments. The goal is to develop advanced robotic systems capable of addressing the challenging needs of nuclear monitoring in terms of multi-modal data, visually-degraded environments, robustness and safety.