This simple demo has been built during Udacity's CS373 "Programming A Robotic Car" class. It illustrates two algorithms:

1. A-star for building a path to a goal location.
2. A path smoothing algorithm.

You can set the goal point by double-tapping the screen, and - although somewhat difficult - you can also manipulate the maze (putting new blocks or removing existing ones) by touching the screen or sliding your finger across the screen.

Details:

Parameters:

You can play with many parameters in the settings. The following is a simple description of each one:

• Vertical/Horizontal/Diagonal cost: These motion costs will influence the final path. In particular, they influence the path-cost function (known as the g-value or g-function), which is the cost of going from the robot's current position to another position.
• Weigth data/smooth: These parameters are used in the path smoothing algorithm.

A* Note:

• The g value is incremental, meaning that if we're moving from point a to point b, then the g-value of b equals the g-value of a plus the cost of moving from a to b in a particular direction (i.e. vertical, horizontal or diagonal).
• The hueristic function between two points a and b equals the euclidean distance between a and b.

Path smoothing note:

For more details on this algorithm, please see Udacity's CS373 course, unit 5, sections 1 through 6.

Screenshot: