To develop a neuro-inspired model (deep learning in convolution networks) of spoken language understanding for modulating actions. Humans often use short warnings to communicate a threatening situation to another human. If robots are to interact with humans in safe open spaces they will have to be able to listen to those warnings that humans naturally generate and adapt their behaviour accordingly.
The result will be an auditory-guided robot which can protect its body or change its current behaviour based on auditory warnings. We will study how the auditory input (e.g. sound, word) can trigger actions from simple actions toward action sequences and will develop an architecture for a robot that learns safe movements guided by auditory cues based on previously learned experiences.
Zamani, M.A., Magg, S., Weber, C., and Wermter, S. (2017, August).
Deep Reinforcement Learning using Symbolic Representation for Performing Spoken Language Instructions.
In 2nd Workshop on Behavior Adaptation, Interaction and Learning for Assistive Robotics (BAILAR) on Robot and Human Interactive Communication (RO-MAN), 2017 26th IEEE International Symposium on.
Short Curriculum Vitae
|since May 2016|| Research Associate (SECURE Project) of Knowledge Technology Research Group, |
Department of Computer Science, University of Hamburg, Germany.
Project: European Training Network: Safety Enables Cooperation in Uncertain Robotic Environments (SECURE)
|Aug. 2015|| M.Sc. in Computer Science 2012-2015, Ozyegin University, Istanbul, Turkey., |
M.Sc. Thesis: Simultaneous Human-Robot Learning for Efficient Robot Skill Synthesis,
Supervisor: Associate Prof. Erhan Oztop.
|Sep. 2012- Aug. 2015||Research Assistant, Robotics Lab, Ozyegin University, from September 2012 up to August 2015 (Research supported by European Community's Seventh Framework Programme FP7, Converge).|
|July 2009-August 2012|| Research Assistant, System and Machine Research Lab., University of Tehran, Tehran, Iran. |
Supervisors: Dr. Alireza Fereidunian, Prof. Hamid Lesani and Prof. Caro Lucas.
|July 2009|| B.Sc. in Electrical Engineering (Control Engineering), School of ECE, University of Tehran, Tehran, Iran. |
B.Sc. Thesis: Design an Expert System for Adaptive Autonomy in Smart Grids,
Supervisors: Professor Hamid Lesani and Prof. Caro Lucas.
University of Hamburg
Department of Informatics
Vogt Koelln Str. 30
22527 Hamburg, Germany
|Phone:||+49 40 428 83 2446|
|Fax:||+49 40 428 83 2515|
|Email:||zamani at informatik [dot] uni-hamburg [dot] de|