NSF RET Site on Robotics & Big Data for Smart Cities @autonomousrobotslab

Uploaded December 2018 | Updated September 2026, 3 weeks ago

This video serves to introduce our NSF supported "RET Site: Cross-disciplinary Research Experiences on Smart Cities for Nevada Teachers: Integrating Big Data into Robotics".

We invite teachers of Nevada to express their interest to participate and contact us at:

Prof. Dr. Kostas Alexis: kalexis@unr.edu
Prof. Dr. Lei Yang: leiy@unr.edu

Project Website: https://www.unr.edu/bigdatarobotics
Stipend: $10,000

NSF RET Site on Robotics & Big Data for Smart Cities

$Online Refractive Camera Model Calibration in Visual Inertial Odometry$

DARPA SubT Urban Circuit: Collision-tolerant Exploration of Staircases using Aerial Robots

IROS2022 Talk: Risk-Aware Motion Planning for Collision-Tolerant Aerial Robots s.t. Uncertainty

Uncertainty-aware Receding Horizon Exploration and Mapping using Aerial Robots

Graph-based Exploration of Narrow Subterranean Settings

Forceful Aerial Manipulation based on an Aerial Robotic Chain: Hybrid Modeling and Control

$ICRA2022 Talk Autonomous Teamed Exploration of Subterranean Environments with Legged & Aerial Robots ICRA 2022 Talk on our paper: Mihir Kulkarni, Mihir Rahul Dharmadhikari, Marco Tranzatto, Samuel Zimmermann, Victor Reijgwart, Paolo De Petris, Huan Nguyen, Nikhil Vijay Khedekar, Christos Papachristos, Lionel Ott, Roland Siegwart, Marco Hutter, Kostas Alexis, Autonomous Teamed Exploration of Subterranean Environments using Legged and Aerial Robots, IEEE International Conference on Robotics and Automation (ICRA), May 23-27, 2022, Philadelphia (PA), USA Abstract: This paper presents a novel strategy for autonomous teamed exploration of subterranean environments using legged and aerial robots. Tailored to the fact that subterranean settings, such as cave networks and underground mines, often involve complex, large-scale and multi-branched topologies, while wireless communication within them can be particularly challenging, this work is structured around the synergy of an onboard exploration path planner that allows for resilient long-term autonomy, and a multi-robot coordination framework. The onboard path planner is unified across legged and flying robots and enables navigation in environments with steep slopes, and diverse geometries. When a communication link is available, each robot of the team shares submaps to a centralized location where a multi-robot coordination framework identifies global frontiers of the exploration space to inform each system about where it should re-position to best continue its mission. The strategy is verified through a field deployment inside an underground mine in Switzerland using a legged and a flying robot collectively exploring for $45textrm{ min}$, as well as a longer simulation study with three systems. GBPlanner 2 Open-Source release: https://github.com/ntnu-arl/gbplanner_ros$

Degerminator - Experimentation on Robotic Area Disinfection based on UV Germicidal Light

Semantics-aware Exploration and Inspection Path Planning

The Unified Autonomy Stack: Toward a Blueprint for Generalizable Robot Autonomy

Aerial Contact-based Inspection Path Planning and Control

Kostas Alexis |

NSF RET Site on Robotics & Big Data for Smart Cities