This seminar has invited Prof. Alberto Quattrini Li, Assistant Professor Department of Computer Science at Dartmouth College and co-director of the Dartmouth Reality and Robotics Lab and Prof. Ioannis Rekleitis, Associate Professor in the Department of Computer Science and Engineering, University of South Carolina to provide insights on aquatic applications and marine robotics.
“Towards Resilient Low-Cost Robot Teams for Autonomous Aquatic Exploration” by Prof. Alberto Quattrini Li Why is the aquatic world still mostly unexplored despite its importance for the blue economy and the great progress in autonomous robotics? This talk delves into some of the main challenges that limit robots in such a task and solutions we designed towards resilient low-cost aquatic robot teams. First, I will talk about photometric stereo algorithms for low-cost perception that improved the situational awareness of underwater robots. Second, I will present exploration strategies that explicitly consider uncertainties and constraints allowing robots to effec9vely operate in the real world. Then, I will touch on enabling low-cost manipula9on through hardware/software co-design for underwater construction. Each part will include discussion of field experiments and lessons learned. The talk will conclude with a discussion on some of the open problems and current work to achieve the long-term goal of a ubiquitous collaborative multi-agent/multi-robot system that can support large scale aquatic applications, such as environmental monitoring or archaeological exploration.
"Marine Robotics and Underwater Exploration" by Prof. Ioannis Rekleitis The last few years, robots have moved from the pages of science fiction books into our everyday reality. Currently, robots are utilized in entertainment, scientific exploration, manufacturing, and household maintenance. While the above advances were made possible by recent improvements in sensors, actuators, and computing elements, the research of today is focused on the computational aspects of robotics. In particular, methodologies for utilizing the vast volumes of data that can be generated by a robotic mission, together with techniques that would allow a robot to respond adequately in unforeseeable circumstances are the challenges of tomorrow. This talk presents an overview of algorithmic problems related to marine robotics, with the particular focus on exploration and mapping of underwater cave. I will talk about vision-based state estimation and mapping of shipwrecks, underwater caves, and coral reefs. Results on machine learning approaches for coral classification and caveline detection will be discussed. In addition, a short overview of current projects will be discussed. The work that I will present has a strong algorithmic flavour, while it is validated in real hardware. Experimental results from several testing campaigns will be presented.