Automated Door Detection with a 3D-Sensor

Introduction to Door Opening Type Classification Based on Human Demonstration

“…Much of the literature uses a geometry-based approach to door detection without the aid of machine or deep learning. In [ 25 ], 3D sensors were used in a door detection algorithm that uses basic structural knowledge about doors and enables part extraction of doors from point clouds based on constraint region growing. Along with Gaussian probability weights, they are combined to create an overall probability measure.…”

Deep learning model for doors detection: A contribution for context-awareness recognition of patients with Parkinson’s disease

“…Door detection approaches have been extensively developed for indoor robot navigation with social, assistance or domestic applications (Banerjee et al, 2015;Borgsen et al, 2014;Chen et al, 2014;Dai et al, 2013;Derry & Argall, 2013;Fernández-Caramés et al, 2014;He & Zhu, 2017;Kakillioglu et al, 2016;Lecrosnier et al, 2021;Llopart et al, 2017;Othman & Rad, 2020;Quintana et al, 2018;Ramoa et al, 2020;Sekkal et al, 2013;Shalaby et al, 2014;Spournias et al, 2020;Tian et al, 2013;Yuan et al, 2016). Robotic wheelchairs, humanoids, or systems for aid persons with visual impairments were other target fields of research in door detection algorithms (Derry & Argall, 2013;He & Zhu, 2017;Lecrosnier et al, 2021;Llopart et al, 2017;Othman & Rad, 2020;Ramoa et al, 2020;Shalaby et al, 2014;Tian et al, 2013).…”

“…This problem was solved by using the power of transfer learning with a pre-trained model using the TF Object Detection API (Adrian Rosebrock, 2017). Doors' detection using DL has already been addressed for indoor robot navigation with social, assistance or domestic applications, as more detailed in section 2 (Banerjee, Long, Du, Polido, Feng, Atkeson, Gennert, & Padir, 2015;Borgsen, Schöpfer, Ziegler, & Wachsmuth, 2014;Chen, Qu, Zhou, Weng, Wang, & Fu, 2014;Dai et al, 2013;Derry & Argall, 2013;Fernández-Caramés, Moreno, Curto, Rodríguez-Aragón, & Serrano, 2014;He & Zhu, 2017;Kakillioglu, Ozcan, & Velipasalar, 2016;Lecrosnier et al, 2021;Llopart, Ravn, & Andersen, 2017;Othman & Rad, 2020;Quintana, Prieto, Adán, & Bosché, 2018;Ramoa, Alexandre, & Mogo, 2020;Sekkal, Pasteau, Babel, Brun, & Leplumey, 2013;Shalaby, Salem, Khamis, & Melgani, 2014;Spournias, Antonopoulos, Keramidas, Voros, & Stojanovic, 2020;Tian, Yang, Yi, & Arditi, 2013;Yuan, Hashim, Zaki, & Huddin, 2016). However, these studies did not address PD problem, a contribution introduced by this work.…”

Real-time 2D–3D door detection and state classification on a low-power device

“…There are already a vast number of studies that used door detection and classification for robot navigation tasks as moving between rooms, robotic handle grasping and others. Some have used sonar sensors with visual information, [7,8], others used only colour and shape information, [9], or just 3D shape information, [10], some have used simple feature extractors, [11,12] and others have used more modern methods like CNN (convolutional neural networks), [13] and the use of 3D information, [14][15][16][17][18][19].…”

“…In [16], a method is proposed that uses 3D information for door detection without using a dependent training-set detection algorithm. Initially, the point cloud containing all the scene, including the door, is prepossessed using a voxel-grid filter to reduce its density and its normal vectors are calculated.…”