[Tweets]

21/05/2018 6:37pm
RT @rodneyabrooks: Hard truths about how hard AI is going to be. Disappointing for the alarmists, perhaps. [LINK]
17/05/2018 12:43pm
A detailed look at 87 citations reported by #GoogleScholar reveals that only 13% of the papers have applied the cit… [LINK]
15/05/2018 7:10pm
RT @elonmusk: @TalkTesla @Techmeme @timkhiggins According to NHTSA, there was an automotive fatality every 86M miles in 2017 (~40,000 death…

[Blog :: Jan - Dec 2018]

Citations count fails to measure the impact of research

Added on 17/05/2018

Academic career progress is often judged by so-called "h-index", that measures how much your research is being cited. I recently had a detailed look at what exactly the citations, specifically those reported by Google Scholar, amount to. Only a relatively small fraction of the reported citations corresponded to research being applied or reproduced in a meaningful way.

V-REP, Gazebo or ARGoS? A robot simulators comparison

Multi-agent systems Robots C++ AI Added on 17/01/2018 :: 7 comments

Let’s have a look at three commonly used open-source simulators for robotics: V-REP, Gazebo and ARGoS, to find out which one suits your project the best.

pyCreeper

The main purpose of pyCreeper is to wrap tens of lines of python code, required to produce graphs that look good for a publication, into functions. It takes away your need to understand various quirks of matplotlib and gives you back ready-to-use and well-documented code.

Citations count fails to measure the impact of research

Academic career progress is often judged by so-called "h-index", that measures how much your research is being cited. I recently had a detailed look at what exactly the citations, specifically those reported by Google Scholar, amount to. Only a relatively small fraction of the reported citations corresponded to research being applied or reproduced in a meaningful way.

V-REP, Gazebo or ARGoS? A robot simulators comparison

Let’s have a look at three commonly used open-source simulators for robotics: V-REP, Gazebo and ARGoS, to find out which one suits your project the best.

Designing Effective Roadmaps for Robotics Innovation

Automated factories, autonomous delivery drones, self-driving cars: these and similar technologies will soon touch every aspect of our lives. An engaging discussion about how these technologies are regulated and innovated took place at the IROS 2017 conference.

The Information-Cost-Reward framework for understanding robot swarm foraging

The Information-Cost-Reward (ICR) framework relates the way in which robots obtain and share information about where work needs to be done to the swarm’s ability to exploit that information in order to perform work efficiently in the context of a particular task and environment.