Register NOW for the webinar: CLICK ME
With a volume of less than 10 cm³ Milirobots are highly resource-constrained agents. It is thus challenging to strike the right balance between efficiency of operation and flexibility to adapt to new environments and tackle new tasks.
Tiny Developmental Skill Framework (TinyDSF) aims to provide a generic set of techniques for Milirobots, that minimizes the set of hardwired, innate skills and maximizes the space of environments and tasks that the Milirobot can eventually and autonomously adapt to.
This talk will present the bootstrapping of skills in TinyDSF. At the starting point, the Milirobot comes with built-in knowledge of basic physical laws and geometric relations of the 3-D space. Also, it can read signals from its sensors and can write commands to its actuators. However, it does not know the meaning of sensory information and actuator commands, nor does it know the specifics of its own body or anything about the environment. The bootstrapping process follows three steps:
(1) During Skill Search the Milirobot explores the effects of motor commands on its sensory input and learns, by exploration, elementary operations like linear and elementary motion.
(2) During Skill learning it explores and learns compound operations like moving along a rectangle or circle.
(3) Higher Order Skills comprise operations like path following, wall following, swarm following, etc. Higher-order skills can be described in abstract notation and downloaded from a knowledge database. The Milirobot learns to execute and optimize higher-order skills based on its previously acquired skills.
Axel Jantsch (Senior Member, IEEE) received the Dipl.Ing. and Ph.D. degrees in computer science from TU Wien, Vienna, Austria, in 1987 and 1992, respectively. From 1997 to 2002, he was an Associate Professor with the KTH Royal Institute of Technology, Stockholm. From 2002 to 2014, he was a Full Professor of electronic systems design at the KTH. Since 2014, he has been a Professor of systems on chips with the Institute of Computer Technology, TU Wien. He has published five books as an editor and one as the author and over 300 peer-reviewed contributions in journals, books, and conference proceedings. He has given over 100 invited presentations at conferences, universities, and companies. His current research interests include systems on chips, self-aware cyber-physical systems, and embedded machine learning.
When and how to participate
The webinar will be broadcasted live on February 28, 2023 at 8 am (PST) – 5 pm (CET) on Zoom (approx duration 1h + 30m Q&A)
UPDATE: unfortunately due to unforeseen issues the webinar will be rescheduled