ROS Japan UG #34 LT大会 で飛び込みLTした資料です.
https://rosjp.connpass.com/event/161041/
ROS 2のDashing/Eloquentで QoS (Quality of Service) 周りのAPIがそれぞれ破壊的に更新されててツラかったので,そのTIPS・知見を共有させていただきました.
20210225_ロボティクス勉強会_パーティクルフィルタのMAP推定の高速手法「FAST-MAP」を作ってみたMori Ken
Particle filters (PFs) are used for the discrete approximation of dynamic and non-Gaussian probability distributions using numerous particles. Maximum a posteriori (MAP) estimation, which is a point estimation method to extract a unique state value from the probability distributions formed by a PF, functions appropriately against multimodal distributions. However, MAP entails an enormous calculation cost. Therefore, we propose a method to perform MAP estimation with a low calculation cost by compressing the information configured by PF, using adaptive vector quantization. For MAP estimation with 900 particles, the proposed method reduced the computational cost by approximately 96% compared to the conventional method and maintained the same estimation accuracy during the simulation.
ROS Japan UG #34 LT大会 で飛び込みLTした資料です.
https://rosjp.connpass.com/event/161041/
ROS 2のDashing/Eloquentで QoS (Quality of Service) 周りのAPIがそれぞれ破壊的に更新されててツラかったので,そのTIPS・知見を共有させていただきました.
Similar to 08 第6.6節-第6.9節 Roomba用ROS1ドライバのROS2移行(2/2) (7)
20210225_ロボティクス勉強会_パーティクルフィルタのMAP推定の高速手法「FAST-MAP」を作ってみたMori Ken
Particle filters (PFs) are used for the discrete approximation of dynamic and non-Gaussian probability distributions using numerous particles. Maximum a posteriori (MAP) estimation, which is a point estimation method to extract a unique state value from the probability distributions formed by a PF, functions appropriately against multimodal distributions. However, MAP entails an enormous calculation cost. Therefore, we propose a method to perform MAP estimation with a low calculation cost by compressing the information configured by PF, using adaptive vector quantization. For MAP estimation with 900 particles, the proposed method reduced the computational cost by approximately 96% compared to the conventional method and maintained the same estimation accuracy during the simulation.