Comparison of Visual SLAM Algorithms ORB-SLAM2, RTAB-Map and SPTAM in Internal and External Environments with ROS

Jesus, Kesse Jonatas de; Kobs, Henry Julio; Cukla, Anselmo Rafael; Cuadros, Marco Antonio de Souza Leite; Gamarra, Daniel Fernando Tello

doi:10.1109/lars/sbr/wre54079.2021.9605432

Cited by 14 publications

(3 citation statements)

References 10 publications

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“…Nonetheless, it is still an actively researched problem in robotics, so much so that the robotics research community is only now working towards designing benchmarks and mechanisms to compare different SLAM implementations. In recent years, there has been particularly intense research into VSLAM (visual SLAM) [71]. Specifically, the focus is on using primarily visual (camera) sensors to allow robots to track and keep local maps of their relative positions also in indoor environments (where GPS-based navigation fails).…”

Section: Simultaneous Localization and Mappingmentioning

confidence: 99%

The Cloud-to-Edge-to-IoT Continuum as an Enabler for Search and Rescue Operations

et al. 2023

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When a natural or human disaster occurs, time is critical and often of vital importance. Data from the incident area containing the information to guide search and rescue (SAR) operations and improve intervention effectiveness should be collected as quickly as possible and with the highest accuracy possible. Nowadays, rescuers are assisted by different robots able to fly, climb or crawl, and with different sensors and wireless communication means. However, the heterogeneity of devices and data together with the strong low-delay requirements cause these technologies not yet to be used at their highest potential. Cloud and Edge technologies have shown the capability to offer support to the Internet of Things (IoT), complementing it with additional resources and functionalities. Nonetheless, building a continuum from the IoT to the edge and to the cloud is still an open challenge. SAR operations would benefit strongly from such a continuum. Distributed applications and advanced resource orchestration solutions over the continuum in combination with proper software stacks reaching out to the edge of the network may enhance the response time and effective intervention for SAR operation. The challenges for SAR operations, the technologies, and solutions for the cloud-to-edge-to-IoT continuum will be discussed in this paper.

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Section: Simultaneous Localization and Mappingmentioning

confidence: 99%

The Cloud-to-Edge-to-IoT Continuum as an Enabler for Search and Rescue Operations

et al. 2023

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“…Through the experiments it was possible to observe that the RTAB-Map overcomes the Kintinuous technique, with RMSE of 0.0555. [6] compares three SLAM-based algorithms: RTAB-Map, ORB-SLAM2 and SPTAM. Simulations were performed indoors and outdoors, where RTAB-Map demonstrated more accurate estimates outdoors with stereo cameras, reaching an error rate of 4.54%.…”

Section: Related Workmentioning

confidence: 99%

Kinect V2 vs Intel RealSense D435: A Comparative Study on 3D Mapping

Nascimento,

Melo,

Gil

et al. 2023

Anais Do XVIII Workshop De Visão Computacional (WVC 2023)

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The generation of accurate 3D maps is essential for an efficient autonomous navigation. With precise mapping, robots can plan optimal paths, avoiding obstacles and efficiently reaching their destinations. For this purpose, the use of RGB-D cameras, which capture color images and depth information of the environment, is common. This paper presents a comparative study of 3D maps generated by the Kinect V2 and RealSense D435 sensors, which were properly configured in a manipulator robot for controlled data acquisition, considering different environments and capture conditions. The RTAB-Map algorithm was used to process the data acquired by the sensors and generate the 3D maps. This analysis allows identifying which sensors are more suitable for each type of environment, as well as their limitations and advantages. Thus, this comparison helps select the best camera for each application and provides valuable insights for the development of more accurate and efficient applications.

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“…A lidar sensor (specifically, the Velodyne VLP 16) was utilized to scan and map the surrounding area [59,60]. This sensor allowed for the creation of a two-dimensional dynamic map that identifies and marks any obstacles that are present [61]. To ensure accurate positioning, a GNSS-RTK receiver (STONEX S990A RTK) was incorporated into the UGVs.…”

mentioning

confidence: 99%

Integrated Route-Planning System for Agricultural Robots

Asiminari,

Moysiadis,

Kateris

et al. 2024

AgriEngineering

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Within the transition from precision agriculture (task-specific approach) to smart farming (system-specific approach) there is a need to build and evaluate robotic systems that are part of an overall integrated system under a continuous two-way connection and interaction. This paper presented an initial step in creating an integrated system for agri-robotics, enabling two-way communication between an unmanned ground vehicle (UGV) and a farm management information system (FMIS) under the general scope of smart farming implementation. In this initial step, the primary task of route-planning for the agricultural vehicles, as a prerequisite for the execution of any field operation, was selected as a use-case for building and evaluating this integration. The system that was developed involves advanced route-planning algorithms within the cloud-based FMIS, a comprehensive algorithmic package compatible with agricultural vehicles utilizing the Robot Operating System (ROS), and a communicational and computational unit (CCU) interconnecting the FMIS algorithms, the corresponding user interface, and the vehicles. Its analytical module provides valuable information about UGVs’ performance metrics, specifically performance indicators of working distance, non-working distance, overlapped area, and field-traversing efficiency. The system was demonstrated via the implementation of two robotic vehicles in route-execution tasks in various operational configurations, field features, and cropping systems (open field, row crops, orchards). The case studies showed variability in the operational performance of the field traversal efficiency to be between 79.2% and 93%, while, when implementing the optimal route-planning functionality of the system, there was an improvement of up to 9.5% in the field efficiency. The demonstrated results indicate that the user can obtain better control over field operations by making alterations to ensure optimum field performance, and the user can have complete supervision of the operation.

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Comparison of Visual SLAM Algorithms ORB-SLAM2, RTAB-Map and SPTAM in Internal and External Environments with ROS

Cited by 14 publications

References 10 publications

The Cloud-to-Edge-to-IoT Continuum as an Enabler for Search and Rescue Operations

The Cloud-to-Edge-to-IoT Continuum as an Enabler for Search and Rescue Operations

Kinect V2 vs Intel RealSense D435: A Comparative Study on 3D Mapping

Integrated Route-Planning System for Agricultural Robots

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