Submitted version of the thesis - Airlab, the Artificial Intelligence ...

74 Chapter 7. Conclusions and Future Work
is advised to check the colors before each run, since the illumination of the
environment can change the color interpretation. We defined two different
configurations for each color, one for the sunny day, the other for the cloudy
day, both are working at our testing environment.
In order to solve the problems related to vision, color selection script,
a custom white balance and an auto exposure is used to improve the behavior
of the system affected by low cost vision. The problems arisen from
the motor control is solved by limiting the minimum and maximum PWM
values of the motors and by introducing the fuzzy-like control to introduce
different limits for the different distances to target. The use of these tunings
and optimizations enabled us to select low cost components, which are
performing enough well to develop a robot framework that will be used as
a basis to implementing different robogames.
As for the future developments, we plan two additions. The first one it
is the development of a dock station and implementation of the autonomous
charging behavior. The circuit to measure the battery level is already operational.
The software to check the battery level and then go to the dock
station must be implemented.
The second addition is the mice boards that we are going to use as
odometers. Experiments have been made to modify the previous work done
at AIRLab, using the mice as an odometry device. We have not been able
to design the working prototype, and the control circuit that calculates the
position information from the mice yet. Previously, the position information
was calculated with a PIC and a PC. The new design will work on the
ARM microprocessor, and the interface between the camera board and mice
should be designed and implemented.
The third addition is the self adaptation of the robot to battery charge
level. Using the output of battery monitoring circuit, the battery level can
be measured. These measurements are going to used in the implementation
to detect the battery level and change the speed multipliers to keep the
robot in the same speed, even if the battery level is going low. Also, the
robot is going to adapt itself to make the decision of going to the docking
station for reaching, when a low battery status detected.
Implementation of the future developments will result to have a better
control in motion mechanism and introduce more autonomous robot behav-