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Meeting structure

Place: ROBIN pause area, 4th floor Ole-Johan Dahls hus / gather town

12:00-12:15 Brief exchange of recent news, plans, updates, etc.

~12:20-12:40 Presentation on: Technology / Own Research / Journal review (see guidelines), time excludes discussion

Whatever content you present, remember that some of those attending have no advance knowledge about your project or work so introduce it in the beginning and stay focused on the main issues/challenges etc. Thus, make your presentation simple and understandable for as many as possible.

Dates and subjects - Autumn 2023 – Thursdays 12:00-12:45

5-20 min housekeeping/updates + 20 min talk

When What Who
10.08 Robotics at NTNU, Ålesund Assoc. Prof. Di Wu [1]
17.08 Introuction to Ege [2] Ege de Bruin
24.08 UiO Growth House [3] Ivar Bergland
31.08 Modeling centipede gaits at Tohoku university [4] Emma Stensby Norstein
07.09 Introduction to visiting PhD student Elias [5] Elias Najarro
14.09 Travel portal and reimbursement tips Jim
21.09 Introduction to IVS Ole Jakobs' PhD students
28.09 Something about soup and shrimp Frank
05.10 Casual meeting due to autumn school break Updates from attendees
12.10 Casual/no meeting due to IFI conference (for permanent staff/postdocs)
19.10 Locomotor control in centipedes Kotaro Yasui, Akio Ishiguro, Takeshi Kano, visiting from Tohoku University, Japan
26.10 Neuromorphic computing for robotics Mateusz Wasiluk
02.11 Exploring human-robot interactions through pupillometry Marieke
09.11 ZRob Learning Mojtaba
16.11 TunnRL-CC: A computational framework for smart TBM cutter changing Tom Frode
23.11 State of the Makerspace [6] Adrian
30.11 intelligent robotics news [7] Kyrre
07.12 Attending the 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) conference Jim
14.12 LLMs for robotics Shin Watanabe

Overview of earlier seminars

Examples of interesting topics for technology introduction

Feel free to add topics to the wishlist!

  • Robotics
    • Reinforcement learning for robotics
    • SLAM
    • embodied cognition
    • Swarm
  • Neural networks
    • Recursive NNs and LSTMs
    • NEAT / HyperNEAT
    • Deep NNs
  • Evolutionary algorithms and other types of optimization
    • Performance comparison of EAs (statistical tests)
    • Differential evolution
    • Diversity preservation methods
    • Novelty search, MAP-Elites and variants
    • Bayesian optimization
  • Tools
    • SLURM
    • R
    • Python as alternative to R, incl. matplotlib
    • ROS
    • Deep learning frameworks and practice
    • Unity ML agents
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