Andrea F. Daniele

Some of my open-source contributions were selected for archival in the Arctic World Archive (AWA), an archival facility designed to preserve data for 1,000 years.
A total of 186 reels of film were stored in a steel-walled container, inside a sealed chamber, within a decommissioned coal mine, buried deep into the permafrost of the Svalbard archipelago, in Norway. Internationally recognized as a demilitarized zone, Svalbard is the world’s northernmost town and one of the most remote and geopolitically stable human habitations on Earth.

I worked on the development of "SHARC: SHared Autonomy for Remote Collaboration" at the Woods Hole Oceanographic Institution. SHARC is a multi‑modal interface that enables remote scientists to perform high‑level tasks using an underwater manipulator, while deferring low‑level control to the robot. We successfully deployed and tested SHARC during the OECI Technology Demonstration: Nereid Under Ice (NUI) Vehicle + Mesobot expedition aboard E/V Nautilus.

I co-organized the first hardware based massive online open course (MOOC) in AI and robotics, free on edX. Aimed at teaching autonomy hands-on by making robots that can take their own decisions and accomplish broadly defined tasks. The course guides learners step-by-step from the theory, to the implementation, to the deployment in simulation as well as on real robots (Duckiebots).

Leveraging static annotations and HD maps, we created a semantically rich lane-level graph, that simulated agents can use to navigate the map. This lane graph is comprised of three layers: topological, metrical, and semantic. Topological and metrical layers were extracted from HD maps and static annotations, while the semantic layer was constructed from annotations only.

Together with my adviser Prof. Matthew Walter, Jacob Arkin, Nakul Gopalan, Prof. Thomas Howard, Jesse Thomason, and Lawson Wong, I organized the Workshop on Models and Representations for Natural Human-Robot Communication (MRHRC) at the RSS (Robotics: Science and Systems) 2018 conference.

Under the supervision of my adviser Prof. Matthew Walter, I and other colleagues showed our UR5-equipped Husky A200 robot safely playing Checkers against human opponents at the Museum of Science and Industry in Chicago for the 2018 National Robotics Week exhibit. This robot is developed in the RIPL lab at TTI-Chicago.

In Autumn 2017 I joined the international team of Duckietown (a robotics education and outreach effort) working as a Teaching Assistant for the course TTIC 31240 - Self-driving Vehicles: Models and Algorithms for Autonomy taught by Prof. Matthew Walter at TTIC. Click on the blue button to see my contributions to the project.

Under the supervision of my adviser Prof. Matthew Walter, I and other colleagues showed our Husky A200 robot at the Museum of Science and Industry in Chicago for the National Robotics Week. This robot is developed in the RIPL lab at TTI-Chicago as part of the Robotics Collaborative Technology Alliance (RCTA) research program. CBS 2’s Vince Gerasole interviewed me on that occasion.

Under the supervision of my adviser Prof. Matthew Walter, I developed a model that enables robots to generate natural language instructions that allow humans to navigate a priori unknown environments. The model first decides which information to share with the user according to their preferences, then “translates” this information into a natural language instruction.