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in AI and Deep Learning by (50.2k points)

I am implementing a simulation that requires me to have some pathfinding.

A* works fine for me when my environment does not change.

LPA* and D* Lite work fine for me when I encounter a static obstacle that is not on my original map.

However, how do I handle the situation when these obstacles are moving at a certain velocity?

Is there a variant of the LPA* or D* Lite algorithm that handles this?

OR Do I have to combine some form of steering behavior with these algorithms?

Ultimately in my simulation, I want to have my 'agent' move from a start point to an endpoint in an environment in which there will be obstacles that move.

1 Answer

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Listed below are some criteria that could be used for determining when a recalculation is needed:

  1. Every N steps: this guarantees that the information used to calculate the path is not more than N steps old.

  2. Whenever extra CPU time is available: this permits dynamic adjustment of path quality; as more units are deployed, or if the game is running on a slower computer, CPU usage per unit can be decreased.

  3. Whenever the unit turns a corner or passes a waypoint.

  4. Whenever the world near the unit has changed.

This article has great ideas about dynamic A*, which could be useful to you

Anytime Dynamic A*: An Anytime, Replanning Algorithm Maxim Likhachev, Dave Ferguson† Geoff Gordon†, Anthony Stentz†, and Sebastian Thrun Also this article, Randomized Kinodynamic Motion Planning with Moving Obstacles by David Hsu Robert, Kindel Jean-Claude Latombe, Stephen Rock

They should be a good start.

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