Advancing robotics, a sweet spot for neuromorphic computing, the work at the Computational Brain (ComBra) Lab has recently received the attention of the media, including Engadget, HPCwire, Bit-Tech, CBRonline, Robot Report, Robotics Business Review and Unite AI. The news is spread in several countries including China, Germany, Italy, Brazil, UK and Korea, echoing the results to be presented at the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019), this November.
The paper describes the first end-to-end neuromorphic algorithm that is inspired by the brain's network to solve a foundational problem in real-time control of robots. The work hints that neuromorphic computing can scale to address real-world problems, by comparing to highly developed methods while offering unparalleled energy efficiency (here, two orders of magnitude less energy is needed, compared to a mainstream method for simultaneous localization and mapping of a mobile robot.)
The other two authors of the paper are:
1) Guangzhi Tang, a PhD student at ComBra Lab who has completed his MSc Thesis in the same Lab; and
2) Arpit Shah, a MSc student who conducted his Thesis at ComBra Lab. Aprit was awarded the Publications Award by the CS Department.
