One of the Hound goals was the low cost and a short development time. To achieve this it was decided not to design a chassis and work on top of a RC car chassis. This reduced the development time and avoided all the prototyping extra costs.
We used not only the mechanical components but also the driving electronics like the electronic speed controller (ESC) and steering Servo. This meant that we had to work with a Ackerman style steering which has is advantages like an easier driving algorithm but also some disadvantages like the short turn ratio usual to this type of steering.
Chassis top view
Another main mechanical component is the camera arm which will be discussed in mechanics Part II. The arm was 3D designed from scratch in order to elevate the camera and be as effective as possible by maintaining the 2 servos in the base.
Since the main part of Hound was the ability to see, the camera had to had at least 2DOF of movement, so a pan/tilt system was installed in the arm so that the user could see various angles in front of the vehicle. Was used 2 standard hobby servos.
Pan Tilt Close up
The base between the electronics and the chassis was made using a 3.3mm acrylic reinforced with 2mm aluminum bars to prevent flex while moving.
In part II we will discuss the Arm, chassis cover and the pro/con of choosing a Crawler chassis.
Upload the example sketch TinyStabilizer from the tiny LSM303 Library
Connect the attiny and the LSM303DLHC as described in the wiring section
Connect the Servos signal to the attiny if using different power supplies remember to have a common ground
Power up servos and Attiny
Move the breadboard to see the servos “compensate” the movement
The data itself from the accelerometer is very noisy, and don’t allow a smooth operation of the servos, so the best way to “clean” this data is to pass a low pass filter with a very low alpha (0.2 in this case)
The different outputs can be seen in the below graphic took with our DT Serial Chart , as you can see the “yellow” line has a much smoother curve in contrast with the raw data from the blue line.
Raw Data vs Filtered Data
We will soon make a post about how to get the data on the chart with our software.