The Researchers from Massachusetts Institute of Technology’s Computer Science and Artificial Intelligence Laboratory (CSAIL), the National University of Singapore, and the Singapore-MIT Alliance for Research and Technology (SMART) come together to design an autonomous mobility scooter and related software. For the help of mobility-impaired lineman, researchers build a new system of the self-driving scooter. This new system helps them to come down in the hall or the lobby of a building or pick up a taxi on the public roads.
“It’s extraordinary to me because it’s a project that the team conducted in about two months,” said Daniela Rus, Professor of Electrical Engineering and Computer Science at MIT.
Many layers of software included in the researchers’ system — low-level control algorithms this empowers the vehicle to respond instantly to changes in its environment, such as a pedestrian darting across its path; route-planning algorithms; localization algorithms that the vehicle uses to determine its location on a map; map-building algorithms that it uses to construct the map in the first place; a scheduling algorithm that allocates fleet resources; and an online booking system that allows users to schedule rides.
Researchers already used this sensor configuration and software in trials of autonomous cars and golf carts. “If you have a uniform system where all the algorithms are the same, the complexity is much lower than if you have a heterogeneous system where each vehicle does something different,” Rus said. “That’s useful for verifying that this multilayer complexity is correct,” Rus added.
At the IEEE International Conference on Intelligent Transportation Systems in Rio de Janeiro, Brazil, researchers give a detailed analysis of their scooter systems design and trails result.
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