1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.RO2023★ 1 cited
Efficient Solution to 3D-LiDAR-based Monte Carlo Localization with Fusion of Measurement Model Optimization via Importance Sampling
Naoki Akai
This paper presents an efficient solution to 3D-LiDAR-based Monte Carlo localization (MCL). MCL robustly works if particles are exactly sampled around the ground truth. An inertial…
cs.RO2022
SLAMER: Simultaneous Localization and Map-Assisted Environment Recognition
Naoki Akai
This paper presents a simultaneous localization and map-assisted environment recognition (SLAMER) method. Mobile robots usually have an environment map and environment information…
cs.RO2022
Reliable Monte Carlo Localization for Mobile Robots
Naoki Akai
Reliability is a key factor for realizing safety guarantee of full autonomous robot systems. In this paper, we focus on reliability in mobile robot localization. Monte Carlo locali…