1 / 8

Dave Lattanzi’s RRT Algorithm

Dave Lattanzi’s RRT Algorithm. General Concept. Use dictionaries for trees Create a randomized stack of nodes Iterate through stack “Extend” each tree towards last node Check for intersections at each step. Main Function. “Extend” Function.

lesley
Download Presentation

Dave Lattanzi’s RRT Algorithm

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Dave Lattanzi’s RRT Algorithm

  2. General Concept • Use dictionaries for trees • Create a randomized stack of nodes • Iterate through stack • “Extend” each tree towards last node • Check for intersections at each step

  3. Main Function

  4. “Extend” Function • Build a dictionary of nodes in tree and their distances to the random node • Search dictionary to get nearest node • Almost certainly not optimal • Call “step” until trapped, goal, or found path • Check for intersections after each step • Doesn’t return for intersection

  5. “Extend” Function

  6. “Step” Function • Finds all neighbors of a node & their distances to random node • Finds the neighbor with the minimum distance, passes that to Extend as new node • If the specified node is the closer than all neighbors to the random node, the tree is declared “trapped”

  7. “Step” and “FindIntersection”

  8. Conclusions: • Tight corners are an issue • Fast (usually) • Time is random • Could be optimized

More Related