scholarly journals An FPGA Based Energy Efficient DS-SLAM Accelerator for Mobile Robots in Dynamic Environment

2021 ◽  
Vol 11 (4) ◽  
pp. 1828
Author(s):  
Yakun Wu ◽  
Li Luo ◽  
Shujuan Yin ◽  
Mengqi Yu ◽  
Fei Qiao ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Mobile Robots ◽  
Semantic Information ◽  
Dynamic Environment ◽  
High Energy ◽  
Significant Loss ◽  
Frame Rate ◽  
Energy Efficiency Improvement ◽  
Localization And Mapping ◽  
Slam Algorithm

The Simultaneous Localization and Mapping (SLAM) algorithm is a hotspot in robot application research with the ability to help mobile robots solve the most fundamental problems of “localization” and “mapping”. The visual semantic SLAM algorithm fused with semantic information enables robots to understand the surrounding environment better, thus dealing with complexity and variability of real application scenarios. DS-SLAM (Semantic SLAM towards Dynamic Environment), one of the representative works in visual semantic SLAM, enhances the robustness in the dynamic scene through semantic information. However, the introduction of deep learning increases the complexity of the system, which makes it a considerable challenge to achieve the real-time semantic SLAM system on the low-power embedded platform. In this paper, we realized the high energy-efficiency DS-SLAM algorithm on the Field Programmable Gate Array (FPGA) based heterogeneous platform through the optimization co-design of software and hardware with the help of OpenCL (Open Computing Language) development flow. Compared with Intel i7 CPU on the TUM dataset, our accelerator achieves up to 13× frame rate improvement, and up to 18× energy efficiency improvement, without significant loss in accuracy.

scholarly journals Visual Simultaneous Localization and Mapping (vSLAM) of Driverless Car in GPS-Denied Areas

2021 ◽  
Vol 12 (1) ◽  
pp. 49
Author(s):  
Abira Kanwal ◽  
Zunaira Anjum ◽  
Wasif Muhammad
Keyword(s):  
Science Fiction ◽  
Urban Areas ◽  
Visual Information ◽  
Dynamic Environment ◽  
Simultaneous Localization And Mapping ◽  
Video Camera ◽  
Input Image ◽  
Localization And Mapping ◽  
Health Related ◽  
Slam Algorithm

A simultaneous localization and mapping (SLAM) algorithm allows a mobile robot or a driverless car to determine its location in an unknown and dynamic environment where it is placed, and simultaneously allows it to build a consistent map of that environment. Driverless cars are becoming an emerging reality from science fiction, but there is still too much required for the development of technological breakthroughs for their control, guidance, safety, and health related issues. One existing problem which is required to be addressed is SLAM of driverless car in GPS denied-areas, i.e., congested urban areas with large buildings where GPS signals are weak as a result of congested infrastructure. Due to poor reception of GPS signals in these areas, there is an immense need to localize and route driverless car using onboard sensory modalities, e.g., LIDAR, RADAR, etc., without being dependent on GPS information for its navigation and control. The driverless car SLAM using LIDAR and RADAR involves costly sensors, which appears to be a limitation of this approach. To overcome these limitations, in this article we propose a visual information-based SLAM (vSLAM) algorithm for GPS-denied areas using a cheap video camera. As a front-end process, features-based monocular visual odometry (VO) on grayscale input image frames is performed. Random Sample Consensus (RANSAC) refinement and global pose estimation is performed as a back-end process. The results obtained from the proposed approach demonstrate 95% accuracy with a maximum mean error of 4.98.

A multi-innovation with forgetting factor based EKF-SLAM method for mobile robots

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhen Zhou ◽  
Dongqing Wang ◽  
Boyang Xu
Keyword(s):  
Mobile Robots ◽  
Strong Nonlinearity ◽  
Forgetting Factor ◽  
Extended Kalman Filtering ◽  
Estimation Errors ◽  
Content Type ◽  
Application Range ◽  
Localization And Mapping ◽  
Slam Algorithm ◽  
Filtering Effect

Purpose The purpose of this paper is to explore a multi-innovation with forgetting factor-based EKF-SLAM (FMI-EKF-SLAM) algorithm to solve the error increasing problem, caused by the Extended Kalman filtering (EKF) violating the local linear assumption in simultaneous localization and mapping (SLAM) for mobile robots because of strong nonlinearity. Design/methodology/approach A multi-innovation with forgetting factor-based EKF-SLAM (FMI-EKF-SLAM) algorithm is investigated. At each filtering step, the FMI-EKF-SLAM algorithm expands the single innovation at current step to an extended multi-innovation containing current and previous steps and introduces the forgetting factor to reduce the effect of old innovations. Findings The simulation results show that the explored FMI-EKF-SLAM method reduces the state estimation errors, obtains the ideal filtering effect and achieves higher accuracy in positioning and mapping. Originality/value The method proposed in this paper improves the positioning accuracy of SLAM and improves the EKF, so that the EKF has higher accuracy and wider application range.

scholarly journals GPS-SLAM: An Augmentation of the ORB-SLAM Algorithm

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4973 ◽  
Author(s):  
Dániel Kiss-Illés ◽  
Cristina Barrado ◽  
Esther Salamí
Keyword(s):  
Frame Rate ◽  
Measurement Unit ◽  
Additional Information ◽  
Main Work ◽  
Localization And Mapping ◽  
Global Positioning ◽  
Aerial Vehicle ◽  
Slam Algorithm ◽  
Low Frame Rate

This work presents Global Positioning System-Simultaneous Localization and Mapping (GPS-SLAM), an augmented version of Oriented FAST (Features from accelerated segment test) and Rotated BRIEF (Binary Robust Independent Elementary Features) feature detector (ORB)-SLAM using GPS and inertial data to make the algorithm capable of dealing with low frame rate datasets. In general, SLAM systems are successful in case of datasets with a high frame rate. This work was motivated by a scarce dataset where ORB-SLAM often loses track because of the lack of continuity. The main work includes the determination of the next frame’s pose based on the GPS and inertial data. The results show that this additional information makes the algorithm more robust. As many large, outdoor unmanned aerial vehicle (UAV) flights save the GPS and inertial measurement unit (IMU) data of the capturing of images, this program gives an option to use the SLAM algorithm successfully even if the dataset has a low frame rate.

Improving RGB-D SLAM in dynamic environments using semantic aided segmentation

Robotica ◽  
2021 ◽  
pp. 1-26
Author(s):  
Lhilo Kenye ◽  
Rahul Kala
Keyword(s):  
Search Algorithm ◽  
Dynamic Environment ◽  
Optimization Techniques ◽  
Working Environment ◽  
Binary Mask ◽  
Localization And Mapping ◽  
Dynamic Objects ◽  
Slam Algorithm ◽  
Indoor And Outdoor Environments ◽  
Static Background

Summary Most conventional simultaneous localization and mapping (SLAM) approaches assume the working environment to be static. In a highly dynamic environment, this assumption divulges the impediments of a SLAM algorithm that lack modules that distinctively attend to dynamic objects despite the inclusion of optimization techniques. This work exploits such environments and reduces the effects of dynamic objects in a SLAM algorithm by separating features belonging to dynamic objects and static background using a generated binary mask image. While the features belonging to the static region are used for performing SLAM, the features belonging to non-static segments are reused instead of being eliminated. The approach employs deep neural network or DNN-based object detection module to obtain bounding boxes and then generates a lower resolution binary mask image using depth-first search algorithm over the detected semantics, characterizing the segmentation of the foreground from the static background. In addition, the features belonging to dynamic objects are tracked into consecutive frames to obtain better masking consistency. The proposed approach is tested on both publicly available dataset as well as self-collected dataset, which includes both indoor and outdoor environments. The experimental results show that the removal of features belonging to dynamic objects for a SLAM algorithm can significantly improve the overall output in a dynamic scene.

scholarly journals Energy conservation and energy efficiency improvement in Russian agribusiness

2021 ◽  
Vol 244 ◽  
pp. 03009
Author(s):  
Liliya Akhmetshina ◽  
Kirill Grabovyy
Keyword(s):  
Energy Efficiency ◽  
Energy Conservation ◽  
Energy Saving ◽  
Agricultural Production ◽  
Energy Intensity ◽  
Agricultural Sector ◽  
High Energy ◽  
Agricultural Products ◽  
Energy Efficiency Improvement ◽  
High Level

Energy saving and increasing energy efficiency of agribusiness are aimed at producing higher quality agricultural products with minimal consumption of fuel and energy resources. At the same time, energy conservation implies a decrease in the need for energy capacities, a decrease in the energy intensity of production in general, and the introduction of energy-saving technologies. The aim of the study is to assess the state of energy efficiency in agricultural production and substantiate the need for the introduction of energy-saving technologies by agribusiness entities to ensure sustainable development and a high level of competitiveness of agricultural products. The study made it possible to identify the specific features of the energy supply of the agricultural sector and the main reasons for the high energy intensity and low energy efficiency of agricultural production. As a result of the study of promising developments in the field of energy conservation and existing energy-saving technologies, organizational and economic measures aimed at increasing energy efficiency and reducing the energy intensity of agricultural production were determined.

Additional methods to improve the energy efficiency of oil pipeline transportation

2020 ◽  
Vol 10 (5) ◽  
pp. 558-565
Author(s):  
Marat R. Lukmanov ◽  
◽  
Sergey L. Semin ◽  
Pavel V. Fedorov ◽  
◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Energy Saving ◽  
Pipeline System ◽  
Energy Costs ◽  
Improvement Program ◽  
Oil Pipeline ◽  
Energy Efficiency Improvement ◽  
Oil Transportation ◽  
Pumping Equipment ◽  
Preparatory Work

The challenges of increasing the energy efficiency of the economy as a whole and of certain production sectors in particular are a priority both in our country and abroad. As part of the energy policy of the Russian Federation to reduce the specific energy intensity of enterprises in the oil transportation system, Transneft PJSC developed and implements the energy saving and energy efficiency improvement Program. The application of energy-saving technologies allowed the company to significantly reduce operating costs and emissions of harmful substances. At the same time, further reduction of energy costs is complicated for objective reasons. The objective of this article is to present additional methods to improve the energy efficiency of oil transportation by the example of the organizational structure of Transneft. Possibilities to reduce energy costs in the organization of the operating services, planning and execution of work to eliminate defects and preparatory work for the scheduled shutdown of the pipeline, the use of pumping equipment, including pumps with variable speed drive, the use of various pipelines layouts, changing the volume of oil entering the pipeline system and increase its viscosity.

Reactions in Activated Peroxide Systems and their Influences on Bleaching Performance

2020 ◽  
Vol 17 ◽  
Author(s):  
Xiaoyan Wang ◽  
Jinmei Du ◽  
Changhai Xu
Keyword(s):  
Aqueous Solution ◽  
Hydrogen Peroxide ◽  
Energy Efficiency ◽  
Textile Industry ◽  
High Energy ◽  
Side Reactions ◽  
Competitive Reactions ◽  
High Energy Efficiency ◽  
Hydrolysis Of ◽  
Bleach Activators

Abstract:: Activated peroxide systems are formed by adding so-called bleach activators to aqueous solution of hydrogen peroxide, developed in the seventies of the last century for use in domestic laundry for their high energy efficiency and introduced at the beginning of the 21st century to the textile industry as an approach toward overcoming the extensive energy consumption in bleaching. In activated peroxide systems, bleach activators undergo perhydrolysis to generate more kinetically active peracids that enable bleaching under milder conditions while hydrolysis of bleach activators and decomposition of peracids may occur as side reactions to weaken the bleaching efficiency. This mini-review aims to summarize these competitive reactions in activated peroxide systems and their influence on bleaching performance.

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