Welcome to Rocketman Development!

My mind-challenging games are found on many online sites recording tens of millions of plays worldwide. Whether it's conception, design, collaboration, problem-solving or programming, Rocketman Development is up for the challenge. Specializing in AS3, Flash, Python, Physics, Math, and AI.

Periodically, I blog about some interesting technical challenges and provide methods to address them that you might find useful. The Rocketman Blog begins below.

Thanks for visiting and please return to learn new techniques and find links to my latest games. If you would like to collaborate, Contact Me.

Using Ray Casting with Shapes

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Back in July, we looked at how to use Ray Casting for collision detection. We also learned how to use the Separation of Axis Theorem. I recently had a request for a way to use the Shapes we created here with the Ray Casting method. First, lets do a quick review of the shape classes. The SAT Shape [...]
Untitled

Detecting Collisions with SAT

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Today we will finally be detecting a collision with SAT. We know how SAT works, we’ve built classes to work with SAT, now we can use all of this to detect a real, live collision! Using the classes we created last time, this is quite simple. First create a shape: var shape1:Polygon = [...]
Untitled

Using the Separation of Axis Theorem

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A few months ago, I posted on the separation of axis theorem. You can learn all about SAT and how it works here. What that post failed to do was use the SAT. We will explore using SAT for collision detection in this post. In the post on SAT, we created the code to detect collisions, however use of [...]

Steering Behaviors and A* Source

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Some of you have asked for the entire steering behavior source as well as the A* source. Here is the zip with all the classes. In there is the vehicle class with all the code for the behaviors. For more information on each behavior, you can go here. The Vehicle class found in [...]

A* and Pathfollowing Steering Behavior

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In the last three posts, we explored the how A* works, then we put A-star into code, then we looked at different heuristics for A*. Now we will combine A* pathfinding with the path following steering behavior. We have already done most of the work to do this. But we’ll do a quick review in case you [...]
The Manhattan Heuristic produces this path.

A* Heuristics

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In the first post on A*, we explored the theory behind A*. Then we took A-star and put it into code. Now we will look at different heuristics for A* and how they affect the path. The Manhattan Method This is the heuristic function we used in our implementation of A*. The Manhattan method will get [...]
AStarFinal

Putting A* into Code

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In yesterday’s post on the basics of A star, we explored the theory behind A*. Today we will take that theory and put it into code. Because A-star uses a grid made up of cells, we need some classes to store that data. First the cell class: These public variables are the key variables that a cell [...]
AStarFinal

A* Pathfinding Basics

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A* (A-star) is an algorithm used for pathfinding. Pathfinding is where a computer computes the shortest (or best) path from a start point to an end point through a grid or nodes. We will be using a grid to find a path. The green cell is the start point and the red cell is the end point. The [...]
Leader Following Click to watch

Steering Behaviors: Leader Following

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The next post steering behaviors series is unaligned collision avoidance. We will be using the Vector2D.as and Vehicle.as classes for this. You will need these classes for the this post. This post is based on Craig Reynold’s article Steering Behaviors For Autonomous Characters. Leader Following is [...]
Flocking

Steering Behaviors: Flocking

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The next post steering behaviors series is unaligned collision avoidance. We will be using the Vector2D.as and Vehicle.as classes for this. You will need these classes for the this post. This post is based on Craig Reynold’s article Steering Behaviors For Autonomous Characters. Flocking is [...]
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