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Most Influential AAAI 2007 Paper · 2026-03 edition

Theta*: Any-Angle Path Planning On Grids

Alex Nash; Kenny Daniel; Sven Koenig; Ariel Felner

Venue
AAAI Conference on Artificial Intelligence (AAAI) 2007
Recognition
Most Influential AAAI 2007 Paper (Rank No. 2)
Edition
2026-03
Impact factor
7
Certificate ID
e30579fedc1c6dbe

Abstract

Grids with blocked and unblocked cells are often used to represent terrain in computer games and robotics. However, paths formed by grid edges can be sub-optimal and unrealistic looking, since the possible headings are artificially constrained. We present Theta*, a variant of A*, that propagates information along grid edges without constraining the paths to grid edges. Theta* is simple, fast and finds short and realistic looking paths. We compare Theta* against both Field D*, the only other variant of A* that propagates information along grid edges without constraining the paths to grid edges, and A* with post-smoothed paths. Although neither path planning method is guaranteed to find shortest paths, we show experimentally that Theta* finds shorter and more realistic looking paths than either of these existing techniques.

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