We moved to NTNU! For a period we will maintain activities at UNR too.
New mail e-mail address: firstname.lastname@example.org
Welcome to the website of the Autonomous Robots Lab of the Norwegian University of Science and Technology (NTNU), Department of Engineering Cybernetics. Our team's mission is to create resilient autonomous robotic systems capable of long-term operation in complex, and degraded environments.
Our dedication is to create robotic systems that will present the locomotion, perception and intelligence properties that will allow them to deal with any environment, under any possible conditions, and perform all kinds of interactions necessary to carry out useful tasks. We are therefore building a research team that integrates, and advances a diversity of skills. We are inspired by the visionaries of robotics and we are trying our best towards meaningful contributions that can break new ground and enable new robotic abilities in relation with application domains useful to our societies.
We welcome visitors to explore our research and education pages as well as students from all engineering and science disciplines to contact us and discuss research opportunities.
Below are brief explanations of some indicative ongoing projects in our lab:
- DARPA Subterranean Challenge - Team CERBERUS: CERBERUS (CollaborativE walking & flying RoBots for autonomous ExploRation in Underground Settings) aims to respond to the needs and goals set by the DARPA SubT Challenge. The SubT Challenge plans to develop novel approaches to rapidly map, explore and search underground environments in time-sensitive operations critical for the civilian and military domains alike. CERBERUS is a product of the collaboration between University of Nevada, Reno, ETH Zurich, Sierra Nevada Corporation, University of California, Berkeley, and Flyability.
- RI: Small: Learning Resilient Autonomous Flight Behaviors by Exploiting Collision-tolerance - this NSF grant emphasizes on survivable autonomous navigation of collision-tolerant flying robots exploiting both rigid and compliant designs as well as hybrid systems-based reinforcement learning methods.
- 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. It is the product of the collaboration of our lab at UNR and the Robotics Institute of Carnegie Mellon University.
- Mine Inspection Robotics: The research to be conducted in this project relates to the ability of autonomous aerial robots to explore, survey, map and monitor underground mines. The relevant environments are dark, GPS-denied and can be particularly narrow. Beyond the associated research contributions, emphasis is put on field demonstration in collaboration with members of the Mining Industry.
- Intelligent Mobility: This project from the Nevada Knowledge Fund takes place in collaboration with transportation industry leaders (e.g. Proterra) and refers to research on autonomous driving and smart cities. It takes place in collaboration with the Nevada Center for Applied Research (NCAR).
- Active Perception: This fundamental research direction corresponds to a focal point of our lab and aims to enable roobts with the cognizant ability to understand their localization and mapping limitations, while performing autonomous navigation, exploration and mapping in challenging, possibily visually-degraded, dynamic environments.
- Improving UAV Vehicle Safety: Algorithms for Computer Vision Based Detect and Avoid and Failure-Resistant Control: This state-funded project aims to develop real-time collision-detection and collision-avoidance systems and strategies for aerial robots such that manned and unmanned aircraft avoidance is guaranteed and safe beyond line of sight operation is enabled.
Searching for PhDs!
The "Autonomous Robots Lab" (ARL) at the Norwegian University of Science and Technology (NTNU) is opening PhD positions in the field of advanced navigational and operational autonomy for cognizant robotic systems. Students with interest in the fields of control, perception, path planning, and multi-agent systems are welcome to apply.