scholarly journals TERRESTRIAL MOBILE MAPPING BASED ON A MICROWAVE RADAR SENSOR. APPLICATION TO THE LOCALIZATION OF MOBILE ROBOTS

2021 ◽  
Vol V-1-2021 ◽  
pp. 73-80
Author(s):  
R. Rouveure ◽  
P. Faure ◽  
M.-O. Monod
Keyword(s):  
Global Positioning System ◽  
Mobile Robotics ◽  
Ease Of Use ◽  
Mobile Mapping ◽  
Microwave Radar ◽  
Localization And Mapping ◽  
Global Positioning ◽  
Outdoor Environments ◽  
Slam Algorithm ◽  
Radar Map

Abstract. Mobile robotics applications in outdoor environments now use intensively Global Positioning System (GPS). For localization or navigation operations, GPS has become an essential tool due to its ease of use, its precision, and its worldwide accessibility. The increase of autonomy level in mobile robotics implies a robust centimeter-level positioning, but the presence of natural (trees, mountains) or man-made obstacles (buildings) can degrade or prevent GPS signals reception. We present in this paper a solution for robots localization based on PELICAN microwave radar. PELICAN radar provides each second a panoramic image of the surrounding environment. These images are concatenated through a Simultaneous Localization And Mapping (SLAM) algorithm in order to build global maps of the traveled environments. The proposed solution computes the position and orientation of the robot through a real-time 3D matching between the current radar image and a pre-existing radar map constructed during an exploratory phase.

scholarly journals The Rosario dataset: Multisensor data for localization and mapping in agricultural environments

2019 ◽  
Vol 38 (6) ◽  
pp. 633-641 ◽  
Author(s):  
Taihú Pire ◽  
Martín Mujica ◽  
Javier Civera ◽  
Ernesto Kofman
Keyword(s):  
Global Positioning System ◽  
Mobile Robotics ◽  
Sensor Data ◽  
Measurement Unit ◽  
Direct Sunlight ◽  
Localization And Mapping ◽  
Global Positioning ◽  
Gps Rtk ◽  
Autonomous Mobile Robotics ◽  
Multisensor Data

In this paper we present the Rosario dataset, a collection of sensor data for autonomous mobile robotics in agricultural scenes. The dataset is motivated by the lack of realistic sensor readings gathered by a mobile robot in such environments. It consists of six sequences recorded in soybean fields showing real and challenging cases: highly repetitive scenes, reflection, and burned images caused by direct sunlight and rough terrain among others. The dataset was conceived in order to provide a benchmark and contribute to the agricultural simultaneous localization and mapping (SLAM)/odometry and sensor fusion research. It contains synchronized readings of several sensors: wheel odometry, inertial measurement unit (IMU), stereo camera, and a Global Positioning System real-time kinematics (GPS-RTK) system. The dataset is publicly available from http://www.cifasis-conicet.gov.ar/robot/ .

scholarly journals An Optimized Tightly-Coupled VIO Design on the Basis of the Fused Point and Line Features for Patrol Robot Navigation

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2004 ◽  
Author(s):  
Linlin Xia ◽  
Qingyu Meng ◽  
Deru Chi ◽  
Bo Meng ◽  
Hanrui Yang
Keyword(s):  
Global Positioning System ◽  
Inertial Measurement Unit ◽  
Feature Matching ◽  
Robot Navigation ◽  
Measurement Unit ◽  
State Estimator ◽  
Localization And Mapping ◽  
Global Positioning ◽  
Tightly Coupled ◽  
Association State

The development and maturation of simultaneous localization and mapping (SLAM) in robotics opens the door to the application of a visual inertial odometry (VIO) to the robot navigation system. For a patrol robot with no available Global Positioning System (GPS) support, the embedded VIO components, which are generally composed of an Inertial Measurement Unit (IMU) and a camera, fuse the inertial recursion with SLAM calculation tasks, and enable the robot to estimate its location within a map. The highlights of the optimized VIO design lie in the simplified VIO initialization strategy as well as the fused point and line feature-matching based method for efficient pose estimates in the front-end. With a tightly-coupled VIO anatomy, the system state is explicitly expressed in a vector and further estimated by the state estimator. The consequent problems associated with the data association, state optimization, sliding window and timestamp alignment in the back-end are discussed in detail. The dataset tests and real substation scene tests are conducted, and the experimental results indicate that the proposed VIO can realize the accurate pose estimation with a favorable initializing efficiency and eminent map representations as expected in concerned environments. The proposed VIO design can therefore be recognized as a preferred tool reference for a class of visual and inertial SLAM application domains preceded by no external location reference support hypothesis.

Comparison of Radius-Estimating Techniques for Horizontal Curves

2005 ◽  
Vol 1918 (1) ◽  
pp. 76-83 ◽  
Author(s):  
Paul J. Carlson ◽  
Mark Burris ◽  
Kit Black ◽  
Elisabeth R. Rose
Keyword(s):  
Global Positioning System ◽  
Ease Of Use ◽  
Horizontal Curve ◽  
Rural Highways ◽  
Horizontal Curves ◽  
Long Run ◽  
Wide Range ◽  
Global Positioning ◽  
Advisory Speed ◽  
Transportation Agencies

Techniques to obtain horizontal curve radii were identified and tested in a controlled experimental study. Ten techniques were identified and pilot tested. Eight of those initial 10 were then used to measure 18 horizontal curves on two-lane rural highways in Texas to evaluate fully their accuracy, precision, cost, ease of use, and safety. Statistically, all eight techniques produced equivalent accuracies, but they displayed a wide range in their precision. The costs varied as a function of the number of times each technique would be used in the field, with those techniques with high initial costs becoming more cost-competitive over the long run with many uses. Ease of use was gauged on the basis of the experience gained during this research. Safety was measured on the basis of whether a technique required personnel on the roadway or roadside or whether it allowed personnel to work from an office or inside a vehicle. The recommendations were based on the expected needs of three different groups that use radii information: transportation agencies, accident investigators, and transportation researchers. Within transportation agencies, engineers and planners in the office will probably benefit most from the plan sheet method, whereas field personnel will probably benefit most from using either the advisory speed or a Global Positioning System (GPS) method. Those who estimate only occasionally, such as accident investigators, will benefit most from the compass method. Finally, researchers or others who may have difficulty accessing plan sheets but still require accurate data will benefit from using a GPS.

In-Between Mobile Maps and Media: Movement

2016 ◽  
Vol 18 (4) ◽  
pp. 320-335 ◽  
Author(s):  
Clancy Wilmott
Keyword(s):  
Global Positioning System ◽  
Positioning System ◽  
Mobile Mapping ◽  
Spatial Experience ◽  
Global Positioning ◽  
Reductive Process ◽  
Geocoded Data ◽  
The Relationship ◽  
Mobile Maps ◽  
Firsthand Experience

This article moves beyond the textuality of the map to focus on the way in which mobile mapping is constructed discursively, semiotically, and experientially. It centers on the autoethnographic and reflective experience of the researcher analyzing video and Global Positioning System (GPS) recordings of walking interviews, during which the interviewees conversed about, and engaged in, mobile mapping practices. This reductive process can be considered in light of its re-presentation to the researcher for analytical purposes—a ghostly abstraction of a past spatial experience. The article considers the manifold hauntings stirred in the process of abstraction and the creation of multiple layers of experience: that of the firsthand experience of the walking interview and that of the secondhand analysis of the video and geocoded data. The discrepancy between firsthand movement and secondhand analysis underscores questions about the relationship between mobile maps, representation, and movement and about those epistemologies and ontologies that haunt the interstices between individual records.

scholarly journals Seamless Guidance System Combining GPS, BLE Beacon, and NFC Technologies

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Rung-Shiang Cheng ◽  
Wei-Jun Hong ◽  
Jheng-Syun Wang ◽  
Kawuu W. Lin
Keyword(s):  
Global Positioning System ◽  
Near Field ◽  
Smart Phone ◽  
Location Based Services ◽  
Guidance System ◽  
Campus Environment ◽  
Accurate Localization ◽  
Global Positioning ◽  
Graphic Information ◽  
Outdoor Environments

Users rely increasingly on Location-Based Services (LBS) and automated navigation/guidance systems nowadays. However, while such services are easily implemented in outdoor environments using Global Positioning System (GPS) technology, a requirement still exists for accurate localization and guidance schemes in indoor settings. Accordingly, the present study proposes a system based on GPS, Bluetooth Low Energy (BLE) beacons, and Near Field Communication (NFC) technology. Through establishing graphic information and the design of algorithm, this study develops a guidance system for indoors and outdoors on smart phones, wishing to give user perfect smart life through this system. The proposed system is implemented on a smart phone and evaluated on a student campus environment. The experimental results confirm the ability of the proposed app to switch automatically from an outdoor mode to an indoor mode and to guide the user to requested target destination via the shortest possible route.

EMERGENCY EVACUATION SIMULATION VISUALIZED BY MOBILE MAPPING SYSTEM

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
Osamu Tsujihara ◽  
Hideyuki Ito ◽  
Terumasa Okamoto
Keyword(s):  
Global Positioning System ◽  
Emergency Evacuation ◽  
Positioning System ◽  
Mobile Mapping ◽  
Evacuation Simulation ◽  
Camera Angle ◽  
Mapping System ◽  
Global Positioning ◽  
Mobile Mapping System ◽  
Serial Images

Recently, studies on evacuation simulations have drawn up scenarios of evacuation under various situations. In this study, a system is proposed to show the results of evacuation simulations for disasters such as tsunamis and fires, with maps and serial images taken by MMS (Mobile Mapping System). The all-around view camera, angle meter, and GPS (Global Positioning System) antenna are mounted on a moving object, such as a car, in MMS. The serially-taken images can be related to GIS (Geographic Information System). Users can not only virtually experience the evacuation but also find the dangerous places by observing the 360-degree surrounding image.

SLAM-based maneuverability strategy for unmanned car-like vehicles

Robotica ◽  
2013 ◽  
Vol 31 (6) ◽  
pp. 905-921 ◽  
Author(s):  
Fernando A. Auat Cheein
Keyword(s):  
Sampling Technique ◽  
Monte Carlo Sampling ◽  
Unmanned Vehicles ◽  
Localization And Mapping ◽  
Outdoor Environments ◽  
Planning Algorithm ◽  
Bounded Space ◽  
Slam Algorithm ◽  
Indoor And Outdoor Environments ◽  
Path Planning Algorithm

SUMMARYIn this work, an optimal maneuverability strategy for car-like unmanned vehicles operating in restricted environments is presented. The maneuverability strategy is based on a path planning algorithm that uses the environment information to plan a safe, feasible and optimum path for the unmanned mobile robot. The environment information is obtained by means of a simultaneous localization and mapping (SLAM) algorithm. The SLAM algorithm uses the sensors' information to build a map of the surrounding environment. A Monte Carlo sampling technique is used to find an optimal and safe path within the environment based on the SLAM information. The objective of the planning is to safely reach a desired orientation in a bounded space. Theoretical demonstrations and real-time experimental results (in indoor and outdoor environments) are also presented in this work.

Sign in / Sign up

Export Citation Format

Share Document