scholarly journals LEO: Liquid Exploration Online

2020 ◽  
Vol 2 (1) ◽  
pp. 58-80
Author(s):  
Frank Hoeller
Keyword(s):  
Path Planning ◽  
State Of The Art ◽  
Simulation Experiments ◽  
Coverage Path Planning ◽  
Current State ◽  
Extensive Evaluation ◽  
Novel Approach ◽  
Local Navigation ◽  
Local Decision ◽  
Real Robot

This article introduces a novel approach to the online complete- coverage path planning (CCPP) problem that is specically tailored to the needs of skid-steer tracked robots. In contrast to most of the current state-of-the-art algorithms for this task, the proposed algorithm reduces the number of turning maneuvers, which are responsible for a large part of the robot's energy consumption. Nevertheless, the approach still keeps the total distance traveled at a competitive level. The algorithm operates on a grid-based environment representation and uses a 3x3 prioritization matrix for local navigation decisions. This matrix prioritizes cardinal di- rections leading to a preference for straight motions. In case no progress can be achieved based on a local decision, global path planning is used to choose a path to the closest known unvisited cell, thereby guaranteeing completeness of the approach. In an extensive evaluation using simulation experiments, we show that the new algorithm indeed generates competi- tively short paths with largely reduced turning costs, compared to other state-of-the-art CCPP algorithms. We also illustrate its performance on a real robot.

scholarly journals R-DFS: A Coverage Path Planning Approach Based on Region Optimal Decomposition

2021 ◽  
Vol 13 (8) ◽  
pp. 1525
Author(s):  
Gang Tang ◽  
Congqiang Tang ◽  
Hao Zhou ◽  
Christophe Claramunt ◽  
Shaoyang Men
Keyword(s):  
Path Planning ◽  
Google Earth ◽  
Simulation Experiments ◽  
Minimum Width ◽  
Coverage Path Planning ◽  
Optimal Paths ◽  
Planning Approach ◽  
Polygonal Area ◽  
Aerial Vehicle ◽  
Working Distance

Most Coverage Path Planning (CPP) strategies based on the minimum width of a concave polygonal area are very likely to generate non-optimal paths with many turns. This paper introduces a CPP method based on a Region Optimal Decomposition (ROD) that overcomes this limitation when applied to the path planning of an Unmanned Aerial Vehicle (UAV) in a port environment. The principle of the approach is to first apply a ROD to a Google Earth image of a port and combining the resulting sub-regions by an improved Depth-First-Search (DFS) algorithm. Finally, a genetic algorithm determines the traversal order of all sub-regions. The simulation experiments show that the combination of ROD and improved DFS algorithm can reduce the number of turns by 4.34%, increase the coverage rate by more than 10%, and shorten the non-working distance by about 29.91%. Overall, the whole approach provides a sound solution for the CPP and operations of UAVs in port environments.

scholarly journals Knocking on IPs: Identifying HTTPS Websites for Zero-Rated Traffic

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Mariano Di Martino ◽  
Peter Quax ◽  
Wim Lamotte
Keyword(s):  
Experimental Analysis ◽  
Service Providers ◽  
State Of The Art ◽  
Domain Name ◽  
Internet Service ◽  
Ip Address ◽  
Identification Methods ◽  
Current State ◽  
Novel Approach ◽  
Current Zero

Zero-rating is a technique where internet service providers (ISPs) allow consumers to utilize a specific website without charging their internet data plan. Implementing zero-rating requires an accurate website identification method that is also efficient and reliable to be applied on live network traffic. In this paper, we examine existing website identification methods with the objective of applying zero-rating. Furthermore, we demonstrate the ineffectiveness of these methods against modern encryption protocols such as Encrypted SNI and DNS over HTTPS and therefore show that ISPs are not able to maintain the current zero-rating approaches in the forthcoming future. To address this concern, we present “Open-Knock,” a novel approach that is capable of accurately identifying a zero-rated website, thwarts free-riding attacks, and is sustainable on the increasingly encrypted web. In addition, our approach does not require plaintext protocols or preprocessed fingerprints upfront. Finally, our experimental analysis unveils that we are able to convert each IP address to the correct domain name for each website in the Tranco top 6000 websites list with an accuracy of 50.5% and therefore outperform the current state-of-the-art approaches.

Robust Feature Points Extraction Based on Harris and SIFT

2013 ◽  
Vol 347-350 ◽  
pp. 3500-3504
Author(s):  
Xiao Ran Guo ◽  
Shao Hui Cui ◽  
Fang Dan
Keyword(s):  
Video Sequence ◽  
State Of The Art ◽  
Image Motion ◽  
Video Sequences ◽  
Stabilization System ◽  
Feature Points ◽  
Image Stabilization ◽  
Current State ◽  
Novel Approach ◽  
Key Points

This article presents a novel approach to extract robust local feature points of video sequence in digital image stabilization system. Robust Harris-SIFT detector is proposed to select the most stable SIFT key points in the video sequence where image motion is happened due to vehicle or platform vibration. Experimental results show that the proposed scheme is robust to various transformations of video sequences, such as translation, rotation and scaling, as well as blurring. Compared with the current state-of-the-art schemes, the proposed scheme yields better performances.

scholarly journals A System for Extracting Study Design Parameters from Nutritional Genomics Abstracts

2013 ◽  
Vol 10 (2) ◽  
pp. 82-93 ◽  
Author(s):  
Cassidy Kelly ◽  
Hui Yang
Keyword(s):  
Language Processing ◽  
Study Design ◽  
State Of The Art ◽  
Design Parameters ◽  
Regular Expressions ◽  
Journal Articles ◽  
Current State ◽  
Novel Approach ◽  
Algorithmic Framework ◽  
Nutritional Genomics

Summary The extraction of study design parameters from biomedical journal articles is an important problem in natural language processing (NLP). Such parameters define the characteristics of a study, such as the duration, the number of subjects, and their profile. Here we present a system for extracting study design parameters from sentences in article abstracts. This system will be used as a component of a larger system for creating nutrigenomics networks from articles in the nutritional genomics domain. The algorithms presented consist of manually designed rules expressed either as regular expressions or in terms of sentence parse structure. A number of filters and NLP tools are also utilized within a pipelined algorithmic framework. Using this novel approach, our system performs extraction at a finer level of granularity than comparable systems, while generating results that surpass the current state of the art.

scholarly journals Deep reinforcement learning for map-less goal-driven robot navigation

2021 ◽  
Vol 18 (1) ◽  
pp. 172988142199262
Author(s):  
Matej Dobrevski ◽  
Danijel Skočaj
Keyword(s):  
Reinforcement Learning ◽  
Path Planning ◽  
Mobile Robots ◽  
Real World ◽  
Robot Navigation ◽  
Dynamic Environments ◽  
Learning Framework ◽  
Local Navigation ◽  
Real Robot ◽  
Navigation Method

Mobile robots that operate in real-world environments need to be able to safely navigate their surroundings. Obstacle avoidance and path planning are crucial capabilities for achieving autonomy of such systems. However, for new or dynamic environments, navigation methods that rely on an explicit map of the environment can be impractical or even impossible to use. We present a new local navigation method for steering the robot to global goals without relying on an explicit map of the environment. The proposed navigation model is trained in a deep reinforcement learning framework based on Advantage Actor–Critic method and is able to directly translate robot observations to movement commands. We evaluate and compare the proposed navigation method with standard map-based approaches on several navigation scenarios in simulation and demonstrate that our method is able to navigate the robot also without the map or when the map gets corrupted, while the standard approaches fail. We also show that our method can be directly transferred to a real robot.

scholarly journals Euler diagrams drawn with ellipses area-proportionally (Edeap)

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Michael Wybrow ◽  
Peter Rodgers ◽  
Fadi K. Dib
Keyword(s):  
State Of The Art ◽  
Data Sets ◽  
Microarray Experiments ◽  
Current State ◽  
Gene Ontology Database ◽  
Euler Diagrams ◽  
Twitter Data ◽  
Extensive Evaluation ◽  
Using Data ◽  
The Web

AbstractBackgroundArea-proportional Euler diagrams are frequently used to visualize data from Microarray experiments, but are also applied to a wide variety of other data from biosciences, social networks and other domains.ResultsThis paper details Edeap, a new simple, scalable method for drawing area-proportional Euler diagrams with ellipses. We use a search-based technique optimizing a multi-criteria objective function that includes measures for both area accuracy and usability, and which can be extended to further user-defined criteria. The Edeap software is available for use on the web, and the code is open source. In addition to describing our system, we present the first extensive evaluation of software for producing area-proportional Euler diagrams, comparing Edeap to the current state-of-the-art; circle-based method, venneuler, and an alternative ellipse-based method, eulerr.ConclusionsOur evaluation—using data from the Gene Ontology database via GoMiner, Twitter data from the SNAP database, and randomly generated data sets—shows an ordering for accuracy (from best to worst) of eulerr, followed by Edeap and then venneuler. In terms of runtime, the results are reversed with venneuler being the fastest, followed by Edeap and finally eulerr. Regarding scalability, eulerr cannot draw non-trivial diagrams beyond 11 sets, whereas no such limitation is present in Edeap or venneuler, both of which draw diagrams up to the tested limit of 20 sets.

scholarly journals Hybrid Spiral STC-Hedge Algebras Model in Knowledge Reasonings for Robot Coverage Path Planning and Its Applications

2019 ◽  
Vol 9 (9) ◽  
pp. 1909 ◽  
Author(s):  
Hai Van Pham ◽  
Farzin Asadi ◽  
Nurettin Abut ◽  
Ismet Kandilli
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Research Effort ◽  
Dynamic Environments ◽  
Coverage Path Planning ◽  
Knowledge Reasoning ◽  
Cleaning Robot ◽  
Novel Approach ◽  
Proposed Model ◽  
Tree Coverage

Robotics is a highly developed field in industry, and there is a large research effort in terms of humanoid robotics, including the development of multi-functional empathetic robots as human companions. An important function of a robot is to find an optimal coverage path planning, with obstacle avoidance in dynamic environments for cleaning and monitoring robotics. This paper proposes a novel approach to enable robotic path planning. The proposed approach combines robot reasoning with knowledge reasoning techniques, hedge algebra, and the Spiral Spanning Tree Coverage (STC) algorithm, for a cleaning and monitoring robot with optimal decisions. This approach is used to apply knowledge inference and hedge algebra with the Spiral STC algorithm to enable autonomous robot control in the optimal coverage path planning, with minimum obstacle avoidance. The results of experiments show that the proposed approach in the optimal robot path planning avoids tangible and intangible obstacles for the monitoring and cleaning robot. Experimental results are compared with current methods under the same conditions. The proposed model using knowledge reasoning techniques in the optimal coverage path performs better than the conventional algorithms in terms of high robot coverage and low repetition rates. Experiments are done with real robots for cleaning in dynamic environments.

scholarly journals Path planning and collision avoidance for autonomous surface vehicles II: a comparative study of algorithms

2021 ◽  
Author(s):  
Anete Vagale ◽  
Robin T. Bye ◽  
Rachid Oucheikh ◽  
Ottar L. Osen ◽  
Thor I. Fossen
Keyword(s):  
Path Planning ◽  
Comparative Study ◽  
Collision Avoidance ◽  
State Of The Art ◽  
Potential Fields ◽  
Large Set ◽  
Enabling Technology ◽  
Fast Marching ◽  
Autonomous Surface Vehicles ◽  
Current State

AbstractArtificial intelligence is an enabling technology for autonomous surface vehicles, with methods such as evolutionary algorithms, artificial potential fields, fast marching methods, and many others becoming increasingly popular for solving problems such as path planning and collision avoidance. However, there currently is no unified way to evaluate the performance of different algorithms, for example with regard to safety or risk. This paper is a step in that direction and offers a comparative study of current state-of-the art path planning and collision avoidance algorithms for autonomous surface vehicles. Across 45 selected papers, we compare important performance properties of the proposed algorithms related to the vessel and the environment it is operating in. We also analyse how safety is incorporated, and what components constitute the objective function in these algorithms. Finally, we focus on comparing advantages and limitations of the 45 analysed papers. A key finding is the need for a unified platform for evaluating and comparing the performance of algorithms under a large set of possible real-world scenarios.

scholarly journals Energy-aware Coverage Path Planning for Unmanned Aerial Vehicles

2020 ◽  
Author(s):  
Tauã Cabreira ◽  
Lisane Brisolara ◽  
Paulo Ferreira Jr.
Keyword(s):  
Energy Consumption ◽  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Partial Information ◽  
State Of The Art ◽  
Energy Aware ◽  
Coverage Path Planning ◽  
Aerial Vehicles ◽  
Novel Approaches ◽  
Grid Based

Coverage Path Planning (CPP) problem is a motion planning subtopic in robotics, where it is necessary to build a path for a robot to explore every location in a given scenario. Unmanned Aerial Vehicles (UAV) have been employed in several applications related to the CPP problem. However, one of the significant limitations of UAVs is endurance, especially in multi-rotors. Minimizing energy consumption is pivotal to prolong and guarantee coverage. Thus, this work proposes energy-aware coverage path planning solutions for regular and irregular-shaped areas containing full and partial information. We consider aspects such as distance, time, turning maneuvers, and optimal speed in the UAV’s energy consumption. We propose an energy-aware spiral algorithm called E-Spiral to perform missions over regular-shaped areas. Next, we explore an energy-aware grid-based solution called EG-CPP for mapping missions over irregular-shaped areas containing no-fly zones. Finally, we present an energy-aware pheromone-based solution for patrolling missions called NC-Drone. The three novel approaches successfully address different coverage path planning scenarios, advancing the state-of-the-art in this area.

Interactions Between Ketamine and Magnesium for the Treatment of Pain: Current State of the Art

2021 ◽  
Vol 20 ◽  
Author(s):  
Katarina Savić Vujović ◽  
Sonja Vučković ◽  
Radan Stojanović ◽  
Nevena Divac ◽  
Branislava Medić ◽  
...  
Keyword(s):  
State Of The Art ◽  
New Drugs ◽  
Nmda Receptor Antagonists ◽  
Dosing Regimen ◽  
Chronological Order ◽  
The Past ◽  
Current State ◽  
Novel Approach ◽  
Dosage Administration ◽  
Novel Therapeutic

Background: Over the past three decades, NMDA-receptor antagonists have been shown to be efficient drugs for treating pain and particularly pain that is resistant to conventional analgesics. Emphasis will be on the old-new drugs, ketamine and magnesium and their combination as a novel approach for treating chronic pain. Methods: The MEDLINE database was searched via PubMed for articles which were published up to March 1, 2020 with the key words ‘ketamine’, ‘magnesium’ and ‘pain’ (in the title/abstract). Results: Studies in animals, as well as humans have shown that interactions of ketamine and magnesium can be additive, antagonistic and synergistic. These discrepancies might be due to differences in magnesium and ketamine dosage, administration times and the chronological order of drugs administration. Different kinds of pain can also be the source of divergent results. Conclusion: This review explains why studies performed with a combination of ketamine and magnesium have given inconsistent results. Because of the lack of efficacy of drugs available for pain, ketamine and magnesium in combination provide a novel therapeutic approach that needs to be standardized with a suitable dosing regimen, including the chronological order of drug administration.

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