Development of an autonomous mobile robot platform aimed at cleaning inside the drainage groove

2018 ◽  
Vol 2018 (0) ◽  
pp. 1A1-I11
Author(s):  
Kazuto WAKIMIZU ◽  
Yasunori TAKEMURA ◽  
Atsushi SANADA ◽  
Shota CHIKUSHI ◽  
Tomoya YONEMORI ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Autonomous Mobile Robot ◽  
Robot Platform

Autonomous mobile robot platform with multi-variant task-specific end-effector and voice activation

2016 ◽  
Author(s):  
Jonathan Tapia ◽  
Eric Wineman ◽  
Patrick Benavidez ◽  
Aldo Jaimes ◽  
Ethan Cobb ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Autonomous Mobile Robot ◽  
End Effector ◽  
Robot Platform

Development for General-purpose Autonomous Mobile Robot Platform

2018 ◽  
Vol 2018 (0) ◽  
pp. 2A1-F09
Author(s):  
Daisuke YAMAMOTO ◽  
Kazunobu KONDA ◽  
Nobuyuki KISHI ◽  
Sumihito TANAKA ◽  
Kazuki TAIRA
Keyword(s):  
Mobile Robot ◽  
General Purpose ◽  
Autonomous Mobile Robot ◽  
Robot Platform

scholarly journals Phollower—The Universal Autonomous Mobile Robot for Industry and Civil Environments with COVID-19 Germicide Addon Meeting Safety Requirements

2020 ◽  
Vol 10 (21) ◽  
pp. 7682 ◽  
Author(s):  
Ján Bačík ◽  
Peter Tkáč ◽  
Ladislav Hric ◽  
Stanislav Alexovič ◽  
Karol Kyslan ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Development Process ◽  
Programmable Logic Controller ◽  
Mobile Platform ◽  
Programmable Logic ◽  
Autonomous Mobile Robot ◽  
Safety Standards ◽  
Safety Requirements ◽  
Uv C ◽  
Robot Platform

This paper describes the development of Phollower—an autonomous mobile robot intended to perform various logistical tasks in both industrial and civil environments. Phollower is equipped with the latest types of industrial components and sensors. It also employs advanced embedded navigation and localization software to create its own virtual maps and thereby to navigate autonomously within the mapped area. The whole development process has been focused on building a device that meets European safety standards. Phollower is a universal mobile platform that can be quickly expanded with specialized add-ons. A germicidal add-on for disinfection of indoor areas using UV-C light is described as a technology that helps to battle with the ongoing COVID-19 pandemic crisis. The hardware topology combined with the proposed open Programmable Logic Controller (PLC) code and open-Powerlink communication bus creates a unique and easily extendable robot platform.

SLAM Using 3D Reconstruction via a Visual RGB and RGB-D Sensory Input

2011 ◽  
Author(s):  
Helge A. Wurdemann ◽  
Evangelos Georgiou ◽  
Lei Cui ◽  
Jian S. Dai
Keyword(s):  
Mobile Robot ◽  
3D Reconstruction ◽  
Sensor Array ◽  
Microsoft Kinect ◽  
Target Point ◽  
Autonomous Mobile Robot ◽  
Localization And Mapping ◽  
Coordinate Position ◽  
The Cost ◽  
Robot Platform

This paper investigates simultaneous localization and mapping (SLAM) problem by exploiting the Microsoft Kinect™ sensor array and an autonomous mobile robot capable of self-localization. The combination of them covers the major features of SLAM including mapping, sensing, locating, and modeling. The Kinect™ sensor array provides a dual camera output of RGB, using a CMOS camera, and RGB-D, using a depth camera. The sensors will be mounted on the KCLBOT, an autonomous nonholonomic two wheel maneuverable mobile robot. The mobile robot platform has the ability to self-localize and preform navigation maneuvers to traverse to set target points using intelligent processes. The target point for this operation is a fixed coordinate position, which will be the goal for the mobile robot to reach, taking into consideration the obstacles in the environment which will be represented in a 3D spatial model. Extracting the images from the sensor after a calibration routine, a 3D reconstruction of the traversable environment is produced for the mobile robot to navigate. Using the constructed 3D model the autonomous mobile robot follows a polynomial-based nonholonomic trajectory with obstacle avoidance. The experimental results demonstrate the cost effectiveness of this off the shelf sensor array. The results show the effectiveness to produce a 3D reconstruction of an environment and the feasibility of using the Microsoft Kinect™ sensor for mapping, sensing, locating, and modeling, that enables the implementation of SLAM on this type of platform.

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