scholarly journals An RSSI-Based Localization, Path Planning and Computer Vision-Based Decision Making Robotic System

Electronics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1326
Author(s):  
Jatin Upadhyay ◽  
Abhishek Rawat ◽  
Dipankar Deb ◽  
Vlad Muresan ◽  
Mihaela-Ligia Unguresan

A robotic navigation system operates flawlessly under an adequate GPS signal range, whereas indoor navigation systems use the simultaneous localization and mapping system or other vision-based localization systems. The sensor used in indoor navigation systems is not suitable for low power and small scale robotic systems. The wireless area network transmitting devices have fixed transmission power, and the receivers get the different values of signal strength based on their surrounding environments. In the proposed method, the received signal strength index (RSSI) values of three fixed transmitter units are measured every 1.6 m in mesh format and analyzed by the classifiers, and robot position can be mapped in the indoor area. After navigation, the robot analyzes objects and detects and recognize human faces with the help of object recognition and facial recognition-based classification methods respectively. This robot detects the intruder with the current position in an indoor environment.

Author(s):  
A. Masiero ◽  
H. Perakis ◽  
J. Gabela ◽  
C. Toth ◽  
V. Gikas ◽  
...  

Abstract. The increasing demand for reliable indoor navigation systems is leading the research community to investigate various approaches to obtain effective solutions usable with mobile devices. Among the recently proposed strategies, Ultra-Wide Band (UWB) positioning systems are worth to be mentioned because of their good performance in a wide range of operating conditions. However, such performance can be significantly degraded by large UWB range errors; mostly, due to non-line-of-sight (NLOS) measurements. This paper considers the integration of UWB with vision to support navigation and mapping applications. In particular, this work compares positioning results obtained with a simultaneous localization and mapping (SLAM) algorithm, exploiting a standard and a Time-of-Flight (ToF) camera, with those obtained with UWB, and then with the integration of UWB and vision. For the latter, a deep learning-based recognition approach was developed to detect UWB devices in camera frames. Such information is both introduced in the navigation algorithm and used to detect NLOS UWB measurements. The integration of this information allowed a 20% positioning error reduction in this case study.


Author(s):  
Ekaterina Sukhareva ◽  
Tatiana Tomchinskaya ◽  
Ilya Serov

The article discusses the use of SLAM (simultaneous localization and mapping) technology, with the help of which it is possible to build Indoor navigation systems using augmented reality technology, including on mobile platforms. The article also provides an overview of the positive and negative aspects of the SLAM technology its principle of operation for positioning a navigator using augmented reality in a university building within the framework of a student project are reviewed. The already implemented projects on similar topics, but using other technologies are considered their features are described. An example of the implementation of an indoor positioning system in a university using SLAM is given.


2018 ◽  
Vol 15 (3) ◽  
pp. 172988141878017 ◽  
Author(s):  
Hui Zhang ◽  
Xieyuanli Chen ◽  
Huimin Lu ◽  
Junhao Xiao

In this article, we propose a distributed and collaborative monocular simultaneous localization and mapping system for the multi-robot system in large-scale environments, where monocular vision is the only exteroceptive sensor. Each robot estimates its pose and reconstructs the environment simultaneously using the same monocular simultaneous localization and mapping algorithm. Meanwhile, they share the results of their incremental maps by streaming keyframes through the robot operating system messages and the wireless network. Subsequently, each robot in the group can obtain the global map with high efficiency. To build the collaborative simultaneous localization and mapping architecture, two novel approaches are proposed. One is a robust relocalization method based on active loop closure, and the other is a vision-based multi-robot relative pose estimating and map merging method. The former is used to solve the problem of tracking failures when robots carry out long-term monocular simultaneous localization and mapping in large-scale environments, while the latter uses the appearance-based place recognition method to determine multi-robot relative poses and build the large-scale global map by merging each robot’s local map. Both KITTI data set and our own data set acquired by a handheld camera are used to evaluate the proposed system. Experimental results show that the proposed distributed multi-robot collaborative monocular simultaneous localization and mapping system can be used in both indoor small-scale and outdoor large-scale environments.


Author(s):  
Narcis Palomeras ◽  
Sharad Nagappa ◽  
David Ribas ◽  
Nuno Gracias ◽  
Marc Carreras

Geomatics ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 148-176
Author(s):  
Maan Khedr ◽  
Naser El-Sheimy

Mobile location-based services (MLBS) are attracting attention for their potential public and personal use for a variety of applications such as location-based advertisement, smart shopping, smart cities, health applications, emergency response, and even gaming. Many of these applications rely on Inertial Navigation Systems (INS) due to the degraded GNSS services indoors. INS-based MLBS using smartphones is hindered by the quality of the MEMS sensors provided in smartphones which suffer from high noise and errors resulting in high drift in the navigation solution rapidly. Pedestrian dead reckoning (PDR) is an INS-based navigation technique that exploits human motion to reduce navigation solution errors, but the errors cannot be eliminated without aid from other techniques. The purpose of this study is to enhance and extend the short-term reliability of PDR systems for smartphones as a standalone system through an enhanced step detection algorithm, a periodic attitude correction technique, and a novel PCA-based motion direction estimation technique. Testing shows that the developed system (S-PDR) provides a reliable short-term navigation solution with a final positioning error that is up to 6 m after 3 min runtime. These results were compared to a PDR solution using an Xsens IMU which is known to be a high grade MEMS IMU and was found to be worse than S-PDR. The findings show that S-PDR can be used to aid GNSS in challenging environments and can be a viable option for short-term indoor navigation until aiding is provided by alternative means. Furthermore, the extended reliable solution of S-PDR can help reduce the operational complexity of aiding navigation systems such as RF-based indoor navigation and magnetic map matching as it reduces the frequency by which these aiding techniques are required and applied.


Author(s):  
Mohammad Istiak Hossain ◽  
Jan I. Markendahl

AbstractSmall-scale commercial rollouts of Cellular-IoT (C-IoT) networks have started globally since last year. However, among the plethora of low power wide area network (LPWAN) technologies, the cost-effectiveness of C-IoT is not certain for IoT service providers, small and greenfield operators. Today, there is no known public framework for the feasibility analysis of IoT communication technologies. Hence, this paper first presents a generic framework to assess the cost structure of cellular and non-cellular LPWAN technologies. Then, we applied the framework in eight deployment scenarios to analyze the prospect of LPWAN technologies like Sigfox, LoRaWAN, NB-IoT, LTE-M, and EC-GSM. We consider the inter-technology interference impact on LoRaWAN and Sigfox scalability. Our results validate that a large rollout with a single technology is not cost-efficient. Also, our analysis suggests the rollout possibility of an IoT communication Technology may not be linear to cost-efficiency.


2021 ◽  
Vol 17 (2) ◽  
pp. 1-22
Author(s):  
Jingao Xu ◽  
Erqun Dong ◽  
Qiang Ma ◽  
Chenshu Wu ◽  
Zheng Yang

Existing indoor navigation solutions usually require pre-deployed comprehensive location services with precise indoor maps and, more importantly, all rely on dedicatedly installed or existing infrastructure. In this article, we present Pair-Navi, an infrastructure-free indoor navigation system that circumvents all these requirements by reusing a previous traveler’s (i.e., leader) trace experience to navigate future users (i.e., followers) in a Peer-to-Peer mode. Our system leverages the advances of visual simultaneous localization and mapping ( SLAM ) on commercial smartphones. Visual SLAM systems, however, are vulnerable to environmental dynamics in the precision and robustness and involve intensive computation that prohibits real-time applications. To combat environmental changes, we propose to cull non-rigid contexts and keep only the static and rigid contents in use. To enable real-time navigation on mobiles, we decouple and reorganize the highly coupled SLAM modules for leaders and followers. We implement Pair-Navi on commodity smartphones and validate its performance in three diverse buildings and two standard datasets (TUM and KITTI). Our results show that Pair-Navi achieves an immediate navigation success rate of 98.6%, which maintains as 83.4% even after 2 weeks since the leaders’ traces were collected, outperforming the state-of-the-art solutions by >50%. Being truly infrastructure-free, Pair-Navi sheds lights on practical indoor navigations for mobile users.


Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1803
Author(s):  
Nasser Hosseinzadeh ◽  
Ahmed Al Maashri ◽  
Naser Tarhuni ◽  
Abdelsalam Elhaffar ◽  
Amer Al-Hinai

This article presents the development of a platform for real-time monitoring of multi-microgrids. A small-scale platform has been developed and implemented as a prototype, which takes data from various types of devices located at a distance from each other. The monitoring platform is interoperable, as it allows several protocols to coexist. While the developed prototype is tested on small-scale distributed energy resources (DERs), it is done in a way to extend the concept for monitoring several microgrids in real scales. Monitoring strategies were developed for DERs by making a customized two-way communication channel between the microgrids and the monitoring center using a long-range bridged wireless local area network (WLAN). In addition, an informative and easy-to-use software dashboard was developed. The dashboard shows real-time information and measurements from the DERs—providing the user with a holistic view of the status of the DERs. The proposed system is scalable, modular, facilitates the interoperability of various types of inverters, and communicates data over a secure communication channel. All these features along with its relatively low cost make the developed real-time monitoring platform very useful for online monitoring of smart microgrids.


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