Teknologiseminar

Fra Robin

Revisjon per 18. mai 2021 kl. 19:52 av Matsh (Diskusjon | bidrag)
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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.

~12:20-12:35 Presentation on: Technology / Own Research / Journal review (see guidelines), time excludes discussion

Dates and subjects - Spring 2021 – Thursdays 12:00-12:45

5-20 min housekeeping/updates + 15 min talk (casual meetings = round-table)

When What Who
21.01 Who is Diana? What will she do here? Diana
28.01 Casual meeting └[∵┌]└[ ∵ ]┘[┐∵]┘
04.02 The ROBIN API (Slides can be found here) Vegard
11.02 Introduction to the Predictive and Intuitive Robot Companion (PIRC) project Jim – Presentation
18.02 Casual meeting (With short presentation from Andrija) └[∵┌]└[ ∵ ]┘[┐∵]┘
25.02 Do your dance moves seem too robotic? You might be one of Benedikte's trained networks. Benedikte
04.03 Making Sense of Randomness? An Information-based analysis of iEEG Julian
11.03 Casual meeting └[∵┌]└[ ∵ ]┘[┐∵]┘
18.03 Jørgen's trial lecture Jørgen
25.03 Journal review. Journal: Frontiers in Robotics and AI: Evolutionary Robotics Emma
01.04 Easter holiday ˭̡̞(◞⁎˃ᆺ˂)◞*✰
08.04 Multimodal Elderly Care Systems (MECS) dataset Farzan
15.04 Mike
22.04 Casual meeting ฅ/ᐠ。ᆽ。ᐟ \
29.04 Autonomous Robotic Inspection Planning Kai
06.05 Update by participants
13.05 National holiday ˭̡̞(◞⁎˃ᆺ˂)◞*✰
20.05 genLib - our local CAD/generative design library Mats
27.05 Measure while drilling for automated decisions in rock tunnelling Tom
03.06 Casual meeting └[∵┌]└[ ∵ ]┘[┐∵]┘
10.06 Kyrre
17.06 Ole Jacob
24.06 Casual meeting └[∵┌]└[ ∵ ]┘[┐∵]┘
To be continued in August (remove this note to confirm)

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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