Instructions Left mouse click on the map to drop the green ball
Add/remove obstacles by pressing <SPACE>
Move the obstacle using the <g> key
<w> increase sphere of influence of an obstacle
<s> decrease sphere of influence of an obstacle
Potential Field Obstacle Avoidance Robots need to be able to avoid obstacles and one such method is Potential Fields. Potential Fields Obstacle Avoidance is an adaptation of the movement of charged particles into the field of robotics where obstacles generate a ‘rejecting’ field and the goal generates an ‘attractive’ field. When these two fields are added together you get a field, indicating the robot’s motion at that specific position on the map.
Let us assume the following: You want a robot that will fetch something from somewhere or should take something to someplace. In order for this mobile robot to know if it reached the goal, or to plan a path to the goal, it needs to know where it is.
This ‘knowing where it is’ is known as localization. One method used for localization is Particle Filters (Monte Carlo Localization) and this simulation implements particle filter localization.
The simulation consists of RED particles, a GREEN robot and BLUE landmarks (add landmarks by LEFT clicking on the map). By moving the robot around using the w,a,d keys you will see how the particles cluster around the robot, essentially showing where the robot is. (NOTE: If you do not add any landmarks the robot will not be able to localize.)
A line of best fit is a line that is the best approximation of a given set of data. This line can be linear, exponential, logarithmic, polynomial, a power average or a moving average and will depend on the type of data you have and the purpose of the approximated line. Your dataset can even be in 3 dimensions.
I’m only going to look at 2D data (ordered pairs) and the Least Square Method to find a straight line () that best fit the given data points.
Attendance is part of any learning environment. If you do not attend the lectures or practical sessions, your chances of failure increases.
For years I took attendance either by making a class list available for the students to sign or by calling out each student’s name. But this was only part of the process! The other part involved entering the attendance onto either a spreadsheet or web based system in order to gather some statistics. For small classes this might not be an issue, but for large classes… It becomes a mess!!
Since I love automation, I decided to design a bio-metric attendance solution using a fingerprint scanner, an Arduino Mega and an ITDB3.2 inch TFT LCD.
As it is with most institutions, employees have office numbers situated in some or other passage. In order to see someone specific, you go to the administrator/secretary to find out if said person is around or you walk aimlessly up and down the passage hoping to find someone that can at least point you in the right direction.
I’ve been busy with a new project where I use the 3.2″ TFT Touch screen from ITEAD Studio. While testing the application I noticed that the back-light’s brightness change every time I push a button on the screen. AHAA!! – Bad connection! So I started pressing on the edges of the screen, to find out where this is coming from…