Robot k-nearest-neighbor (kNN) path planning method under incomplete perception environment
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Robot path planning technology under unknown dynamic environment has an important application value. Withal, the invention discloses a robot k-nearest-neighbor (kNN) path planning method under incomplete perception environment. The robot kNN path planning method under the incomplete perception environment comprises partially observable markov decision process (POMDP) model building, POMDP model solution and construction of an iterative learning model. Due to the fact that the iterative model is utilized, the learning capability and the adapting capability to the environment of a robot in the process of path planning are improved, and the path planning performance can be improved.