マニピュレータの自己認識のための小型LiDAR：センサ特性評価と初期位置推定実験
Tiny LiDARs for Manipulator Self-Awareness: Sensor Characterization and Initial Localization Experiments
小型ToFセンサ（VL53L5CX）から得られる粗い点群を用いて、ロボット作業空間内の対象物を位置推定する手法を提案し、センサモデルを確率論的に構築してパーティクルフィルタで評価した。
著者: Giammarco Caroleo, Alessandro Albini, Daniele De Martini, Timothy D. Barfoot, Perla Maiolino
分類: cs.RO
原文アブストラクト
For several tasks, ranging from manipulation to inspection, it is beneficial for robots to localize a target object in their surroundings. In this paper, we propose an approach that utilizes coarse point clouds obtained from miniaturized VL53L5CX Time-of-Flight (ToF) sensors (tiny LiDARs) to localize a target object in the robot's workspace. We first conduct an experimental campaign to calibrate the dependency of sensor readings on relative range and orientation to targets. We then propose a probabilistic sensor model, which we validate in an object pose estimation task using a Particle Filter (PF). The results show that the proposed sensor model improves the performance of the localization of the target object with respect to two baselines: one that assumes measurements are free from uncertainty and one in which the confidence is provided by the sensor datasheet.
