LiDARを用いた自己位置推定における潜在変数全結合型のマルコフ確率場を用いたミスマッチ検出

抄録

This paper presents a misalignment recognition method using a Markov random field with fully connected latent variables for LiDAR-based localization. The major difficulty for the misalignment recognition is that considering entire relation of sensor measurement in localization is impossible because it must be assumed that the sensor measurement is independent to one another. The presented method enables to consider the entire relation via the fully connected latent variables. This paper also presents a calculation method of localization failure probability based on the misalignment recognition. Experiments show that the presented method can exactly detect misalignment even though partial sensor measurement overlaps with a map and can exactly recognize success and failure localization results.