Review of Vision-Based Robot Navigation Method

Rahmani, Budi; Putra, Agfianto Eko; Harjoko, Agus; Priyambodo, Tri Kuntoro

doi:10.11591/ijra.v4i4.pp254-261

Cited by 3 publications

(2 citation statements)

References 20 publications

(36 reference statements)

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“…Self-localization is an important feature in the navigation of an autonomous vehicle. Navigation is known as a process of determining a suitable and safe path between the start point and the destination point where the mobile robot will move [3]. Besides that, it also can be defined as the ability to move in any particular environment [3].…”

Section: Introductionmentioning

confidence: 99%

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Visual analytics of 3D LiDAR point clouds in robotics operating systems

Azri¹,

Abdul-Rahman²,

Hamzah³

et al. 2020

Bulletin EEI

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This paper presents visual analytics of 3D LiDAR point clouds in robotics operating system. In this study, experiment on Simultaneous Localization and Mapping (SLAM) using point cloud data derived from the Light Detection and Ranging (LiDAR) technology is conducted. We argue that one of the weaknesses of the SLAM algorithm is in the localization process of the landmarks. Existing algorithms such as Grid Mapping and Monte Carlo have limitations in dealing with 3D environment data that have led to less accurate estimation. Therefore, this research proposes the SLAM algorithm based on Real-Time Appearance-Based (RTAB) and makes use of the Red Green Blue (RGB) camera for visualisation. The algorithm was tested by using the map data that was collected and simulated on the Robot Operating System (ROS) in Linux environment. We present the results and demonstrates that the map produced by RTAB is better compared to its counterparts. In addition, the probability for the estimated location is improved which allows for better vehicle maneuverability.

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Section: Introductionmentioning

confidence: 99%

“…Navigation is known as a process of determining a suitable and safe path between the start point and the destination point where the mobile robot will move [3]. Besides that, it also can be defined as the ability to move in any particular environment [3]. The question of, "where am I currently?"…”

Section: Introductionmentioning

confidence: 99%

Visual analytics of 3D LiDAR point clouds in robotics operating systems

Azri¹,

Abdul-Rahman²,

Hamzah³

et al. 2020

Bulletin EEI

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Distance Estimation based on Color-Block: A Simple Big-O Analysis

Rahmani¹,

Aprilianto²,

Ismanto³

et al. 2017

IJECE

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This paper explains how the process of reading the data object detection results with a certain color. In this case, the object is an orange tennis ball. We use a Pixy CMUcam5 connecting to the Arduino Nano with microcontroller ATmega328-based. Then through the USB port, data from Arduino nano re-read and displayed. It's to ensure weather an orange object is detected or not. By this process, it will be exactly known how many blocks object detected, including the X and Y coordinates of the object. Finally, it will be explained the complexity of the algorithms used in the process of reading the results of the detection orange object.

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