Staircase Detection, Characterization and Approach Pipeline for Search and Rescue Robots

Currently, most rescue robots are mainly teleoperated and integrate some level of autonomy to reduce the operator’s workload, allowing them to focus on the primary mission tasks. One of the main causes of mission failure are human errors and increasing the robot’s autonomy can increase the probabili...

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Autores principales:	José Armando Sánchez-Rojas, José Aníbal Arias-Aguilar, Hiroshi Takemura, Alberto Elías Petrilli-Barceló
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	object detection point cloud segmentation ROS fuzzy control system Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/a50392ef13b448a4818881d766b3ec9e
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id	oai:doaj.org-article:a50392ef13b448a4818881d766b3ec9e
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spelling	oai:doaj.org-article:a50392ef13b448a4818881d766b3ec9e2021-11-25T16:36:57ZStaircase Detection, Characterization and Approach Pipeline for Search and Rescue Robots10.3390/app1122107362076-3417https://doaj.org/article/a50392ef13b448a4818881d766b3ec9e2021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/22/10736https://doaj.org/toc/2076-3417Currently, most rescue robots are mainly teleoperated and integrate some level of autonomy to reduce the operator’s workload, allowing them to focus on the primary mission tasks. One of the main causes of mission failure are human errors and increasing the robot’s autonomy can increase the probability of success. For this reason, in this work, a stair detection and characterization pipeline is presented. The pipeline is tested on a differential drive robot using the ROS middleware, YOLOv4-tiny and a region growing based clustering algorithm. The pipeline’s staircase detector was implemented using the Neural Compute Engines (NCEs) of the OpenCV AI Kit with Depth (OAK-D) RGB-D camera, which allowed the implementation using the robot’s computer without a GPU and, thus, could be implemented in similar robots to increase autonomy. Furthermore, by using this pipeline we were able to implement a Fuzzy controller that allows the robot to align itself, autonomously, with the staircase. Our work can be used in different robots running the ROS middleware and can increase autonomy, allowing the operator to focus on the primary mission tasks. Furthermore, due to the design of the pipeline, it can be used with different types of RGB-D cameras, including those that generate noisy point clouds from low disparity depth images.José Armando Sánchez-RojasJosé Aníbal Arias-AguilarHiroshi TakemuraAlberto Elías Petrilli-BarcelóMDPI AGarticleobject detectionpoint cloud segmentationROSfuzzy control systemTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10736, p 10736 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	object detection point cloud segmentation ROS fuzzy control system Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	object detection point cloud segmentation ROS fuzzy control system Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 José Armando Sánchez-Rojas José Aníbal Arias-Aguilar Hiroshi Takemura Alberto Elías Petrilli-Barceló Staircase Detection, Characterization and Approach Pipeline for Search and Rescue Robots
description	Currently, most rescue robots are mainly teleoperated and integrate some level of autonomy to reduce the operator’s workload, allowing them to focus on the primary mission tasks. One of the main causes of mission failure are human errors and increasing the robot’s autonomy can increase the probability of success. For this reason, in this work, a stair detection and characterization pipeline is presented. The pipeline is tested on a differential drive robot using the ROS middleware, YOLOv4-tiny and a region growing based clustering algorithm. The pipeline’s staircase detector was implemented using the Neural Compute Engines (NCEs) of the OpenCV AI Kit with Depth (OAK-D) RGB-D camera, which allowed the implementation using the robot’s computer without a GPU and, thus, could be implemented in similar robots to increase autonomy. Furthermore, by using this pipeline we were able to implement a Fuzzy controller that allows the robot to align itself, autonomously, with the staircase. Our work can be used in different robots running the ROS middleware and can increase autonomy, allowing the operator to focus on the primary mission tasks. Furthermore, due to the design of the pipeline, it can be used with different types of RGB-D cameras, including those that generate noisy point clouds from low disparity depth images.
format	article
author	José Armando Sánchez-Rojas José Aníbal Arias-Aguilar Hiroshi Takemura Alberto Elías Petrilli-Barceló
author_facet	José Armando Sánchez-Rojas José Aníbal Arias-Aguilar Hiroshi Takemura Alberto Elías Petrilli-Barceló
author_sort	José Armando Sánchez-Rojas
title	Staircase Detection, Characterization and Approach Pipeline for Search and Rescue Robots
title_short	Staircase Detection, Characterization and Approach Pipeline for Search and Rescue Robots
title_full	Staircase Detection, Characterization and Approach Pipeline for Search and Rescue Robots
title_fullStr	Staircase Detection, Characterization and Approach Pipeline for Search and Rescue Robots
title_full_unstemmed	Staircase Detection, Characterization and Approach Pipeline for Search and Rescue Robots
title_sort	staircase detection, characterization and approach pipeline for search and rescue robots
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/a50392ef13b448a4818881d766b3ec9e
work_keys_str_mv	AT josearmandosanchezrojas staircasedetectioncharacterizationandapproachpipelineforsearchandrescuerobots AT joseanibalariasaguilar staircasedetectioncharacterizationandapproachpipelineforsearchandrescuerobots AT hiroshitakemura staircasedetectioncharacterizationandapproachpipelineforsearchandrescuerobots AT albertoeliaspetrillibarcelo staircasedetectioncharacterizationandapproachpipelineforsearchandrescuerobots
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Staircase Detection, Characterization and Approach Pipeline for Search and Rescue Robots

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