DepthLiDAR: active segmentation of environment depth map into mobile sensors

• Autor(a) principal: Limeira, Marcelo A.
• Data de Publicação: 2021
• Outros Autores: Piardi, Luis, Kalempa, Vivian Cremer, Leitão, Paulo, Oliveira, Andre Schneider
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10198/24605
• topic: Virtual sensors; LIDAR; Point cloud; Active segmentation; Industry 4.0.

This paper presents a novel approach for creating virtual LiDAR scanners through the active segmentation of point clouds. The method employs top-view point cloud segmentation in virtual LiDAR sensors that can be applied to the intelligent behavior of autonomous agents. Segmentation is correlated with the visual tracking of the agent for localization in the environmentand point cloud. Virtual LiDARsensors with different characteristicsand positions can then be generated. Thismethod is referred to as the DepthLiDAR approach, and is rigorously evaluated to quantify its performance and determine its advantages and limitations. An extensive set of experiments is conducted using real and virtual LiDAR sensors to compare both approaches. The objective is to propose a novel method to incorporate spatial perception in warehouses, aiming to achieve Industry 4.0. Thus, it is tested in a low-scale warehouse to incorporate realistic features. The analysis of the experiments shows a measurement improvement of 52.24% compared to the conventional LiDAR.