Difference between revisions of "Mean Targeting"
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== Linear Mean == | == Linear Mean == | ||
| − | Given the enemy's current position and their position <code>t</code> ticks in the past, assume the enemy will continue to move with the same direction and average speed deduced from these scans. The | + | Given the enemy's current position and their position <code>t</code> ticks in the past, assume the enemy will continue to move with the same direction and average speed deduced from these scans. The pseudocode would look like this: |
* Take a present scan position and an older scan position, <code>t</code> ticks in the past. Ignore actual heading and velocity. | * Take a present scan position and an older scan position, <code>t</code> ticks in the past. Ignore actual heading and velocity. | ||
* Find the angle from from the old scan to the new one. This is the mean heading. | * Find the angle from from the old scan to the new one. This is the mean heading. | ||
* Find the distance between the two points and divide by <code>t</code>. This is the mean velocity. | * Find the distance between the two points and divide by <code>t</code>. This is the mean velocity. | ||
| − | * Use these values as input to a [[ | + | * Use these values as input to a [[linear targeting]] algorithm. |
== Circular Mean == | == Circular Mean == | ||
| − | Given a collection of <code>x</code> recent scans of the enemy, calculate his average velocity and turn rate and assume that he will continue to move with those values. The | + | Given a collection of <code>x</code> recent scans of the enemy, calculate his average velocity and turn rate and assume that he will continue to move with those values. The pseudocode would look like this: |
* Iterate over the group of scans, summing the <code>x - 1</code> heading changes and <code>x</code> velocities. | * Iterate over the group of scans, summing the <code>x - 1</code> heading changes and <code>x</code> velocities. | ||
* Divide the sum of heading changes by <code>x - 1</code> to find the mean heading change. | * Divide the sum of heading changes by <code>x - 1</code> to find the mean heading change. | ||
* Divide the sum of velocities by <code>x</code> to find the mean velocity. | * Divide the sum of velocities by <code>x</code> to find the mean velocity. | ||
| − | * Use these values as input to a [[ | + | * Use these values as input to a [[circular targeting]] algorithm. |
[[Category:Simple Targeting Strategies]] | [[Category:Simple Targeting Strategies]] | ||
[[Category:Targeting]] | [[Category:Targeting]] | ||
Revision as of 17:39, 13 November 2007
A style of targeting that averages the data from a few recent scans to use as input to its prediction algorithm.
Linear Mean
Given the enemy's current position and their position t ticks in the past, assume the enemy will continue to move with the same direction and average speed deduced from these scans. The pseudocode would look like this:
- Take a present scan position and an older scan position,
tticks in the past. Ignore actual heading and velocity. - Find the angle from from the old scan to the new one. This is the mean heading.
- Find the distance between the two points and divide by
t. This is the mean velocity. - Use these values as input to a linear targeting algorithm.
Circular Mean
Given a collection of x recent scans of the enemy, calculate his average velocity and turn rate and assume that he will continue to move with those values. The pseudocode would look like this:
- Iterate over the group of scans, summing the
x - 1heading changes andxvelocities. - Divide the sum of heading changes by
x - 1to find the mean heading change. - Divide the sum of velocities by
xto find the mean velocity. - Use these values as input to a circular targeting algorithm.
