## my blog my blog

##### Simulating robots with MORSE

It is quite challenging and costly to build up a robot lab, especially if you just want to conduct some experiments with sensors and a moving platform. In todays search of affordable robot platforms, I discovered MORSE, a simulation platform built on the blender game engine (www.openrobots.org/wiki/morse/). This article will show how to set it up, select an environment, add sensors and read from them.

It already has the infrastructure, several environments and pre-built robots, sensors (camera, GPS, laserscanner, IR, etc.) and actuators to play with, and it can be installed directly via apt (Ubuntu + Debian). It took me less than an hour to skim through the tutorials, set up a basic environment, add a laser-range sensor to an existing robot and visualize the results, pretty amazing! (You can find all of my project files here: https://github.com/TobiasWeis/morse-robot-simulation)

##### Groundtruth data for Computer Vision with Blender

In the video below you can see the sequence of a car driving in a city scene and braking. The layers I rendered out for groundtruth data are the rendered image with the boundingbox of the car (top left), the emission layer ( shows the brakelights when they start to emit light, top right ), the optical flow (lower left), and the depth of each pixel in the world scene ( lower right).

Render-time was about 10h on a Nvidia GeForce GTX 680, tilesize 256×256, total image-size: 960×720. In this article I will first demonstrate how to set up the depth rendering, and afterwards how to extract, save and recover the optical flow.

##### Displacement priors

What is the target of all this ? Driving in an automotive scenario with a given speed and turnrate at any moment, we want to predict the displacement of a 2D-projection (pixel) between two frames:
$p(\vec{uv}_{x,y} | speed, turnrate, camera-matrix, world-geometry)$

By using the camera-calibration, I can create artificial curves and walls as 3D point-sets and project them back to 2D. Using discretized values for speed, turnrate, streetwidth and wall-height, I can then simulate the displacement of these 3D-Points when they are projected to 2D (our image).
(Note for me: this is the backprojection-code, main-file: main_displacements.py)