There are several techniques to determine the position of a robot in space. For example, odometry is particularly used with systems that move with the help of wheels. This consists, from a known position, in measuring the movement of each wheel in order to estimate the final position.
It’s often combined with other techniques because odometry alone isn’t very accurate. Obviously this technique is not usable on walking robots.
SLAM is a set of techniques that allow a robot to perform a mapping of its environment and to find its way in it. This mapping can be done in different ways: using a RGB camera, a 3D camera or a LIDAR. Here we will focus on the use of LIDAR. But first, what is it? LIDAR is a device (see the picture above) that emits a laser and calculates the time light takes to come back in order to estimate the distance of surrounding obstacles. 360 LIDAR is generally used, it turns on itself, returning measurements including distance and angle. …
The address bar of the browser has a very important role. Apart from allowing to enter a URL, it helps with the domain name and the SSL certificate to make sure on which website you are. When a security flaw hits the address bar, it’s considered a critical vulnerability.
The vulnerability I’m about to talk is not new. There have already been many proof of concept but despite the various warnings it is still present.
Here is an example of behavior on Chrome Android (and many others browsers) used to save a little space on the screen:
We see very well that the address bar is masked by scrolling down and reappears as soon as we scroll up. In fact it reappears in many circumstances: when you have to enter something in a form, when you go to another website… And this is precisely to avoid any URL spoofing. Unfortunately this doesn’t really protect the user. …
With Gridsome you can fetch data from external APIs or local files and store it in a local database. Then with GraphQL you can query, filter this data and use it in your components.
I’m gonna give you an example with a local JSON file:
It’s pretty similar to the way you load data from external APIs, except you don’t need to use Axios or to do any HTTP request. Instead, you just load your JSON file on Gridsome build and put the data in a contentType object.
Once your contentType is populated, you can easily query it through GraphQL in any vue component.
And what if you want to filter your posts in a specific way? Just add a filter argument to your query:
That’s all, it’s pretty simple but powerful!