scholarly journals An Extensible Positioning System for Locating Mobile Robots in Unfamiliar Environments

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 4025 ◽  
Author(s):  
Xiaosu Xu ◽  
Xinghua Liu ◽  
Beichen Zhao ◽  
Bo Yang
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Clock Synchronization ◽  
Original System ◽  
Ultra Wideband ◽  
Recursive Least Squares ◽  
Measurement Unit ◽  
Positioning System ◽  
Localization And Mapping ◽  
Initial Attitude

In this paper, an extensible positioning system for mobile robots is proposed. The system includes a stereo camera module, inertial measurement unit (IMU) and an ultra-wideband (UWB) network which includes five anchors, one of which is with the unknown position. The anchors in the positioning system are without requirements of communication between UWB anchors and without requirements of clock synchronization of the anchors. By locating the mobile robot using the original system, and then estimating the position of a new anchor using the ranging between the mobile robot and the new anchor, the system can be extended after adding the new anchor into the original system. In an unfamiliar environment (such as fire and other rescue sites), it is able to locate the mobile robot after extending itself. To add the new anchor into the positioning system, a recursive least squares (RLS) approach is used to estimate the position of the new anchor. A maximum correntropy Kalman filter (MCKF) which is based on the maximum correntropy criterion (MCC) is used to fuse data from the UWB network and IMU. The initial attitude of the mobile robot relative to the navigation frame is calculated though comparing position vectors given by a visual simultaneous localization and mapping (SLAM) system and the UWB system respectively. As shown in the experiment section, the root mean square error (RMSE) of the positioning result given by the proposed positioning system with all anchors is 0.130 m. In the unfamiliar environment, the RMSE is 0.131 m which is close to the RMSE (0.137 m) given by the original system with a difference of 0.006 m. Besides, the RMSE based on Euler distance of the new anchor is 0.061 m.

The Correcting Approach of Gyroscope-Free Inertial Navigation Based on the Applicable Topological Map

2019 ◽  
Vol 19 (2) ◽  
Author(s):  
Mehdi Dehghani ◽  
Hamed Kharrati ◽  
Hadi Seyedarabi ◽  
Mahdi Baradarannia
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Inertial Sensors ◽  
Low Cost ◽  
Measurement Unit ◽  
Sensor Calibration ◽  
Topological Map ◽  
Stereo Cameras ◽  
Long Time ◽  
Navigation Errors

The accumulated error and noise sensitivity are the two common problems of ordinary inertial sensors. An accurate gyroscope is too expensive, which is not normally applicable in low-cost missions of mobile robots. Since the accelerometers are rather cheaper than similar types of gyroscopes, using redundant accelerometers could be considered as an alternative. This mechanism is called gyroscope-free navigation. The article deals with autonomous mobile robot (AMR) navigation based on gyroscope-free method. In this research, the navigation errors of the gyroscope-free method in long-time missions are demonstrated. To compensate the position error, the aid information of low-cost stereo cameras and a topological map of the workspace are employed in the navigation system. After precise sensor calibration, an amendment algorithm is presented to fuse the measurement of gyroscope-free inertial measurement unit (GFIMU) and stereo camera observations. The advantages and comparisons of vision aid navigation and gyroscope-free navigation of mobile robots will be also discussed. The experimental results show the increasing accuracy in vision-aid navigation of mobile robot.

Using Global Appearance Descriptors to Solve Topological Visual SLAM

2019 ◽  
pp. 1127-1140
Author(s):  
Lorenzo Fernández Rojo ◽  
Luis Paya ◽  
Francisco Amoros ◽  
Oscar Reinoso
Keyword(s):  
Computer Vision ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Simultaneous Localization And Mapping ◽  
Visual Slam ◽  
Sources Of Information ◽  
Topological Approach ◽  
Unknown Environment ◽  
Localization And Mapping ◽  
Omnidirectional Images

Mobile robots have extended to many different environments, where they have to move autonomously to fulfill an assigned task. With this aim, it is necessary that the robot builds a model of the environment and estimates its position using this model. These two problems are often faced simultaneously. This process is known as SLAM (simultaneous localization and mapping) and is very common since when a robot begins moving in a previously unknown environment it must start generating a model from the scratch while it estimates its position simultaneously. This chapter is focused on the use of computer vision to solve this problem. The main objective is to develop and test an algorithm to solve the SLAM problem using two sources of information: (1) the global appearance of omnidirectional images captured by a camera mounted on the mobile robot and (2) the robot internal odometry. A hybrid metric-topological approach is proposed to solve the SLAM problem.

Inexpensive spatial position system for the automation of inspection with mobile robots

2014 ◽  
Vol 41 (6) ◽  
pp. 508-517 ◽  
Author(s):  
Mohammed Abdullah Al Rashed ◽  
Tariq Pervez Sattar
Keyword(s):  
Mobile Robot ◽  
Complex Geometry ◽  
Measurement Unit ◽  
Positioning System ◽  
Destructive Testing ◽  
Wireless System ◽  
Content Type ◽  
Wireless Positioning ◽  
Spatial Positioning ◽  
Pulse Echo

Purpose – The purpose of this paper is to develop a wireless positioning system. The automation of non-destructive testing (NDT) of large and complex geometry structures such as aircraft wings and fuselage is prohibitively expensive, though automation promises to improve on manual ultrasound testing. One inexpensive way to achieve automation is by using a small wall-climbing mobile robot to move a single ultrasound probe over the surface through a scanning trajectory defined by a qualified procedure. However, the problem is to guide the robot though the trajectory and know whether it has followed it accurately to confirm that the qualified procedure has been carried out. Design/methodology/approach – The approach is to use sophisticated bulk electronics developed for game playing in combination with MATLAB to develop a wireless positioning system. Findings – The paper describes the development of an inexpensive wireless system comprising an optical spatial positioning system and inertial measurement unit that relates the 3D location of an NDT probe carried by a mobile robot to a computer-aided drawing (CAD) representation of the test structure in a MATLAB environment. The probe is located to an accuracy of ± 2 mm at distances of 5 m. Research limitations/implications – Positioning range is limited to 5 m. Further development is required to increase this range. Practical implications – The wireless system is used to develop tools to guide the robot remotely to follow a desired scanning trajectory, obtain feedback about the actual trajectory executed by the robot, know exactly where an ultrasound pulse echo was captured, map identified defects on the CAD and relate them to the real test object. Originality/value – An inexpensive spatial positioning system with sufficient accuracy for automated NDT purposes.

scholarly journals Method for SLAM Based on Omnidirectional Vision: A Delayed-EKF Approach

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Rodrigo Munguía ◽  
Carlos López-Franco ◽  
Emmanuel Nuño ◽  
Adriana López-Franco
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Autonomous Navigation ◽  
Real Data ◽  
Omnidirectional Vision ◽  
Wide Field ◽  
Visual Sensor ◽  
Cluttered Environments ◽  
Localization And Mapping ◽  
Wide Field Of View

This work presents a method for implementing a visual-based simultaneous localization and mapping (SLAM) system using omnidirectional vision data, with application to autonomous mobile robots. In SLAM, a mobile robot operates in an unknown environment using only on-board sensors to simultaneously build a map of its surroundings, which it uses to track its position. The SLAM is perhaps one of the most fundamental problems to solve in robotics to build mobile robots truly autonomous. The visual sensor used in this work is an omnidirectional vision sensor; this sensor provides a wide field of view which is advantageous in a mobile robot in an autonomous navigation task. Since the visual sensor used in this work is monocular, a method to recover the depth of the features is required. To estimate the unknown depth we propose a novel stochastic triangulation technique. The system proposed in this work can be applied to indoor or cluttered environments for performing visual-based navigation when GPS signal is not available. Experiments with synthetic and real data are presented in order to validate the proposal.

scholarly journals Uji Presisi dari Nonholonomic Mobile Robot pada Rancang Bangun Sistem Navigasi

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Desmas A. Patriawan ◽  
Bagoes P. Natakusuma ◽  
Ahmad Anas Arifin ◽  
Hasan S. Maulana ◽  
Hery Irawan ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Global Positioning System ◽  
Measurement Unit ◽  
Positioning System ◽  
Nonholonomic Mobile Robot ◽  
Global Positioning

Navigasi menjadi bagian yang penting bagi kendaraan. Global positioning system (GPS) merupakan sistem navigasi yang paling banyak digunakan pada kendaraan. Namun dengan akurasi 5-10 meter membuat GPS tidak bisa diaplikasikan dalam bagian sistem kendali pada kendaraan. Penambahan sensor inertia measurement unit (IMU) diharapkan mampu menambahkan akurasi pada Gerakan kendaraan. Kendaran yang digunakan adalah robot beroda dengan sistem nonholonomic. Pada robot ini dipasang Sensor IMU, GPS dan kontroler supaya robot tersebut bisa berputar lalu melaju secara lurus dengan kordinat yang sudah ditentukan. Hasil pengujian didapatkan robot memiliki respon time sebesar 4.1 detik tanpa kontroler dan 2.1 detik dengan kontroler. Akurasi sudut dari 5  menjadi 2 .

scholarly journals On-line Optimal Ranging Sensor Deployment for Robotic Exploration

2021 ◽  
Author(s):  
Luca Santoro ◽  
Davide Brunelli ◽  
daniele fontanelli
Keyword(s):  
Genetic Algorithm ◽  
Mobile Robots ◽  
Mobile Agents ◽  
Ultra Wideband ◽  
Sensor Deployment ◽  
Positioning System ◽  
Mobile System ◽  
Robotic Exploration ◽  
On Line ◽  
Geometric Dilution Of Precision

<div>Navigation in an unknown environment without any preexisting positioning infrastructure has always been hard for mobile robots. This paper presents a self-deployable ultra wideband UWB infrastructure by mobile agents, that permits a dynamic placement and runtime extension of UWB anchors infrastructure while the robot explores the new environment. We provide a detailed analysis of the uncertainty of the positioning system while the UWB infrastructure grows. Moreover, we developed a genetic algorithm that minimizes the deployment of new anchors, saving energy and resources on the mobile robot and maximizing the time of the mission. Although the presented approach is general for any class of mobile system, we run simulations and experiments with indoor drones. Results demonstrate that maximum positioning uncertainty is always controlled under the user's threshold, using the Geometric Dilution of Precision (GDoP).</div>

scholarly journals On-line Optimal Ranging Sensor Deployment for Robotic Exploration

2021 ◽  
Author(s):  
Luca Santoro ◽  
Davide Brunelli ◽  
daniele fontanelli
Keyword(s):  
Genetic Algorithm ◽  
Mobile Robots ◽  
Mobile Agents ◽  
Ultra Wideband ◽  
Sensor Deployment ◽  
Positioning System ◽  
Mobile System ◽  
Robotic Exploration ◽  
On Line ◽  
Geometric Dilution Of Precision

<div>Navigation in an unknown environment without any preexisting positioning infrastructure has always been hard for mobile robots. This paper presents a self-deployable ultra wideband UWB infrastructure by mobile agents, that permits a dynamic placement and runtime extension of UWB anchors infrastructure while the robot explores the new environment. We provide a detailed analysis of the uncertainty of the positioning system while the UWB infrastructure grows. Moreover, we developed a genetic algorithm that minimizes the deployment of new anchors, saving energy and resources on the mobile robot and maximizing the time of the mission. Although the presented approach is general for any class of mobile system, we run simulations and experiments with indoor drones. Results demonstrate that maximum positioning uncertainty is always controlled under the user's threshold, using the Geometric Dilution of Precision (GDoP).</div>

scholarly journals Rapid Development of a Mobile Robot for the Nakanoshima Challenge Using a Robot for Intelligent Environments

2020 ◽  
Vol 32 (6) ◽  
pp. 1211-1218
Author(s):  
Tomohiro Umetani ◽  
◽  
Yuya Kondo ◽  
Takuma Tokuda
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Rapid Development ◽  
Field Tests ◽  
Intelligent Environments ◽  
Mobile Platforms ◽  
Robot System ◽  
Location Data ◽  
Localization And Mapping ◽  
Outdoor Environments

Automated mobile platforms are commonly used to provide services for people in an intelligent environment. Data on the physical position of personal electronic devices or mobile robots are important for information services and robotic applications. Therefore, automated mobile robots are required to reconstruct location data in surveillance tasks. This paper describes the development of an autonomous mobile robot to achieve tasks in intelligent environments. In particular, the robot constructed route maps in outdoor environments using laser imaging detection and ranging (LiDAR), and RGB-D sensors via simultaneous localization and mapping. The mobile robot system was developed based on a robot operating system (ROS), reusing existing software. The robot participated in the Nakanoshima Challenge, which is an experimental demonstration test of mobile robots in Osaka, Japan. The results of the experiments and outdoor field tests demonstrate the feasibility of the proposed robot system.

Maps for Mobile Robots

2013 ◽  
pp. 254-297
Keyword(s):  
Mobile Robot ◽  
Mathematical Models ◽  
Mobile Robots ◽  
Sensory Data ◽  
The Third ◽  
Localization And Mapping ◽  
Intrinsic Feature

This is the first chapter of the third section. It describes the kinds of mathematical models usable by a mobile robot to represent its spatial reality, and the reasons by which some of them are more useful than others, depending on the task to be carried out. The most common metric, topological, and hybrid map representations are described from an introductory viewpoint, emphasizing their limitations and advantages for the localization and mapping problems. It then addresses the problem of how to update or build a map from the robot raw sensory data, assuming known robot positions, a situation that becomes an intrinsic feature of some SLAM filters. Since the process greatly depends on the kind of map and sensors, the most common combinations of both are shown.

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