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My research activity covers the fields of autonomous mobile robotics and multiagent systems. In particular, one of the main research thrusts involves the study, development, and assessment of techniques for autonomous decision-making in the exploration problem, where one or more robots are employed to discover features of environments—e.g., obstacles, water quality. The testing of our algorithms focus directly upon real robots, such as ground robots and/or marine robots. The long-term goal is to design ubiquitous collaborative multirobot systems operating in real world environments to enable applications, such as environmental monitoring and mapping.
M. Roznere and A. Quattrini Li, "Underwater monocular depth estimation using single-beam echo sounder," in Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS), 2020.
M. Jeong and A. Quattrini Li, "Risk Vector-based Near miss and Real-time Obstacle Avoidance for Autonomous Surface Vehicles," in Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS), 2020.
A. Quattrini Li, P. K. Penumarthi, J. Banfi, N. Basilico, J. O’Kane, I. Rekleitis, S. Nelakuditi, and F. Amigoni, "Multi-robot Online Sensing Strategies for the Construction of Communication Maps," Autonomous Robots,1–21. 2019.
J. Banfi, A. Quattrini Li, I. Rekleitis, F. Amigoni, and N. Basilico, “Strategies for coordinated multirobot exploration with recurrent connectivity constraints,” Autonomous Robots, vol. 42, pp. 875–894, 2018.