scholarly journals Tsukuba Challenge 2019: Task Settings and Experimental Results

2020 ◽  
Vol 32 (6) ◽  
pp. 1104-1111
Author(s):  
Yoshitaka Hara ◽  
Tetsuo Tomizawa ◽  
Hisashi Date ◽  
Yoji Kuroda ◽  
Takashi Tsubouchi ◽  
...  
Keyword(s):  
Mobile Robots ◽  
Real World ◽  
Autonomous Navigation ◽  
Experimental Results ◽  
The City

This paper overviews Tsukuba Challenge 2019. The Tsukuba Challenge is an experiment for autonomous navigation of mobile robots on public walkways. Navigation tasks through pedestrian paths in the city are given. Participating teams develop their own robot hardware and software. We describe the aim of the task settings and the analysis of the experimental results for all the teams. We studied the records of real-world experiments of Tsukuba Challenge 2019.

scholarly journals A hand-drawn map-based navigation method for mobile robots using objectness measure

2019 ◽  
Vol 16 (3) ◽  
pp. 172988141984633 ◽  
Author(s):  
Jie Niu ◽  
Kun Qian
Keyword(s):  
Mobile Robots ◽  
Autonomous Navigation ◽  
Saliency Map ◽  
Experimental Results ◽  
Environment Map ◽  
Environmental Cognition ◽  
Candidate Regions ◽  
Cognitive Environment ◽  
Candidate Object ◽  
Navigation Method

Correct cognition of the environment is the premise of mobile robots to realize autonomous navigation control tasks. The inconsistency caused by time-varying environmental information is a bottleneck for the development and application of cognitive environment technologies. In this article, we propose an environmental cognition method that uses a hand-drawn map. Firstly, we use the single skeleton refinement and fuzzy c-means algorithms to segment the image. Then, we select candidate regions combining the saliency map. At the same time, we use the superpixels straddling method to filter the windows. The final candidate object regions are obtained based on a fusion of saliency segmentation and superpixels clustering. Based on the above objectness estimation results, we use a human–computer interaction method to construct an inaccurate hand-drawn environment map for navigation. The experimental results from PASCAL VOC2007 validate the efficacy of the proposed objectness measure method, where our result of 41.2% on mean average precision is the best of the tested methods. Furthermore, the experimental results of robot navigation in the actual scene also verified the effectiveness of the proposed approach.

Open Experiment of Autonomous Navigation of Mobile Robots in the City: Tsukuba Challenge 2014 and the Results

2015 ◽  
Vol 27 (4) ◽  
pp. 318-326 ◽  
Author(s):  
Shin'ichi Yuta ◽  
◽  
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Autonomous Navigation ◽  
Mobile Robotics ◽  
Autonomous Mobile Robot ◽  
City Environment ◽  
The City ◽  
Autonomous Mobile Robotics

<div class=""abs_img""> <img src=""[disp_template_path]/JRM/abst-image/00270004/01.jpg"" width=""300"" /> Autonomous mobile robot in RWRC 2014</div> The Tsukuba Challenge, an open experiment for autonomous mobile robotics researchers, lets mobile robots travel in a real – and populated – city environment. Following the challenge in 2013, the mobile robots must navigate autonomously to their destination while, as the task of Tsukuba Challenge 2014, looking for and finding specific persons sitting in the environment. Total 48 teams (54 robots) seeking success in this complex challenge. </span>

Tsukuba Challenge: Open Experiments for Autonomous Navigation of Mobile Robots in the City – Activities and Results of the First and Second Stages –

2018 ◽  
Vol 30 (4) ◽  
pp. 504-512 ◽  
Author(s):  
Shin’ichi Yuta ◽  
◽  
Keyword(s):  
Mobile Robots ◽  
Basic Concept ◽  
Autonomous Navigation ◽  
Mobile Robotics ◽  
The Self ◽  
Second Stage ◽  
History Of ◽  
The Given ◽  
The City ◽  
Autonomous Mobile Robotics

The Tsukuba Challenge is an open experiment for autonomous mobile robotics researchers who want to build small mobile robots capable of autonomously moving through real and populated pedestrian environments. The Tsukuba Challenge started in 2007 and has been run every year since then. Each year, the self-contained mobile robots of participated team are tasked with autonomously navigating more than 1 km of a given pedestrian pathway through the city. As of 2017, the final year of the second stage, a total of over 500 teams have taken a part in this challenge, by trying to develop their own robot hardware and software to complete the given task. In this paper, the basic concept and the history of Tsukuba Challenge are first explained, and then what has and has not achieved is discussed.

scholarly journals Special Issue on Real World Robot Challenge in Tsukuba and Osaka

2020 ◽  
Vol 32 (6) ◽  
pp. 1103-1103
Author(s):  
Hisashi Date ◽  
Tomohito Takubo
Keyword(s):  
Mobile Robots ◽  
Real World ◽  
Autonomous Navigation ◽  
Urban Environments ◽  
Autonomous Mobile Robots ◽  
Current Status ◽  
Special Issue ◽  
Research Papers ◽  
The Real ◽  
Third Stage

The Tsukuba Challenge is an open experiment of autonomous mobile robots in the real world. In its third stage since 2018, it is now to be held on a new course that starts at the Tsukuba City Hall. New tasks that require functions expected for autonomous travel in the real world have now been added, including passing checkpoints announced a day before the event, starting two vehicles simultaneously, traveling in an unmeasured environment, and strictly observing stop lines in the course. Also, in the spirit of the Tsukuba Challenge, the Nakanoshima Challenge, an open demonstration experiment project, has been held in the city of Osaka since 2018. As the only event in which autonomous mobile robots travel in the urban area of Osaka, the Nakanoshima Challenge is expected to identify new issues peculiar to autonomous navigation in real urban environments and to find solutions to them. This special issue includes a review paper on the Tsukuba Challenge, four research papers on the results of experiments done in the Tsukuba Challenge, four research papers related to the Nakanoshima Challenge, and three development reports. This special issue provides its readers with the frontline issues and the current status of development of autonomous mobile robots in real-world environments. We hope that the innovative efforts presented in this special issue will contribute to the development of science and industry.

scholarly journals OFCOD: On the Fly Clustering Based Outlier Detection Framework

Data ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Ahmed Elmogy ◽  
Hamada Rizk ◽  
Amany M. Sarhan
Keyword(s):  
Data Mining ◽  
Image Processing ◽  
Intrusion Detection ◽  
Real Time ◽  
Outlier Detection ◽  
Real World ◽  
Medical Data ◽  
Experimental Results ◽  
Real Time Applications ◽  
Real World Datasets

In data mining, outlier detection is a major challenge as it has an important role in many applications such as medical data, image processing, fraud detection, intrusion detection, and so forth. An extensive variety of clustering based approaches have been developed to detect outliers. However they are by nature time consuming which restrict their utilization with real-time applications. Furthermore, outlier detection requests are handled one at a time, which means that each request is initiated individually with a particular set of parameters. In this paper, the first clustering based outlier detection framework, (On the Fly Clustering Based Outlier Detection (OFCOD)) is presented. OFCOD enables analysts to effectively find out outliers on time with request even within huge datasets. The proposed framework has been tested and evaluated using two real world datasets with different features and applications; one with 699 records, and another with five millions records. The experimental results show that the performance of the proposed framework outperforms other existing approaches while considering several evaluation metrics.

Review Summary Generation in Online Systems: Frameworks for Supervised and Unsupervised Scenarios

2021 ◽  
Vol 15 (3) ◽  
pp. 1-33
Author(s):  
Wenjun Jiang ◽  
Jing Chen ◽  
Xiaofei Ding ◽  
Jie Wu ◽  
Jiawei He ◽  
...  
Keyword(s):  
Decision Making ◽  
Real World ◽  
Text Summarization ◽  
Experimental Results ◽  
Product Review ◽  
Comprehensive Review ◽  
Online Systems ◽  
Real World Datasets ◽  
Different Characteristics

In online systems, including e-commerce platforms, many users resort to the reviews or comments generated by previous consumers for decision making, while their time is limited to deal with many reviews. Therefore, a review summary, which contains all important features in user-generated reviews, is expected. In this article, we study “how to generate a comprehensive review summary from a large number of user-generated reviews.” This can be implemented by text summarization, which mainly has two types of extractive and abstractive approaches. Both of these approaches can deal with both supervised and unsupervised scenarios, but the former may generate redundant and incoherent summaries, while the latter can avoid redundancy but usually can only deal with short sequences. Moreover, both approaches may neglect the sentiment information. To address the above issues, we propose comprehensive Review Summary Generation frameworks to deal with the supervised and unsupervised scenarios. We design two different preprocess models of re-ranking and selecting to identify the important sentences while keeping users’ sentiment in the original reviews. These sentences can be further used to generate review summaries with text summarization methods. Experimental results in seven real-world datasets (Idebate, Rotten Tomatoes Amazon, Yelp, and three unlabelled product review datasets in Amazon) demonstrate that our work performs well in review summary generation. Moreover, the re-ranking and selecting models show different characteristics.

Artificial potential field neuro-fuzzy controller for autonomous navigation of mobile robots

2020 ◽  
pp. 095965182097483
Author(s):  
Mahamat Loutfi Imrane ◽  
Achille Melingui ◽  
Joseph Jean Baptiste Mvogo Ahanda ◽  
Fredéric Biya Motto ◽  
Rochdi Merzouki
Keyword(s):  
Neural Networks ◽  
Fuzzy Logic ◽  
Mobile Robots ◽  
Potential Field ◽  
Autonomous Navigation ◽  
Fuzzy Logic Controller ◽  
Artificial Potential Field ◽  
Type Reduction ◽  
Interval Type

Some autonomous navigation methods, when implemented alone, can lead to poor performance, whereas their combinations, when well thought out, can yield exceptional performances. We have demonstrated this by combining the artificial potential field and fuzzy logic methods in the framework of mobile robots’ autonomous navigation. In this article, we investigate a possible combination of three methods widely used in the autonomous navigation of mobile robots, and whose individual implementation still does not yield the expected performances. These are as follows: the artificial potential field, which is quick and easy to implement but faces local minima and robustness problems. Fuzzy logic is robust but computationally intensive. Finally, neural networks have an exceptional generalization capacity, but face data collection problems for the learning base and robustness. This article aims to exploit the advantages offered by each of these approaches to design a robust, intelligent, and computationally efficient controller. The combination of the artificial potential field and interval type-2 fuzzy logic resulted in an interval type-2 fuzzy logic controller whose advantage over the classical interval type-2 fuzzy logic controller was the small size of the rule base. However, it kept all the classical interval type-2 fuzzy logic controller characteristics, with the major disadvantage that type-reduction remains the main cause of high computation time. In this article, the type-reduction process is replaced with two layers of neural networks. The resulting controller is an interval type-2 fuzzy neural network controller with the artificial potential field controller’s outputs as auxiliary inputs. The results obtained by performing a series of experiments on a mobile platform demonstrate the proposed navigation system’s efficiency.

scholarly journals A New No Equilibrium Fractional Order Chaotic System, Dynamical Investigation, Synchronization, and Its Digital Implementation

Inventions ◽  
2021 ◽  
Vol 6 (3) ◽  
pp. 49
Author(s):  
Zain-Aldeen S. A. Rahman ◽  
Basil H. Jasim ◽  
Yasir I. A. Al-Yasir ◽  
Raed A. Abd-Alhameed ◽  
Bilal Naji Alhasnawi
Keyword(s):  
Adaptive Control ◽  
Fractional Order ◽  
Chaotic System ◽  
Real World ◽  
Experimental Results ◽  
Chaotic Attractors ◽  
State Variables ◽  
Digital Implementation ◽  
Dynamical Behaviors ◽  
Real World Applications

In this paper, a new fractional order chaotic system without equilibrium is proposed, analytically and numerically investigated, and numerically and experimentally tested. The analytical and numerical investigations were used to describe the system’s dynamical behaviors including the system equilibria, the chaotic attractors, the bifurcation diagrams, and the Lyapunov exponents. Based on the obtained dynamical behaviors, the system can excite hidden chaotic attractors since it has no equilibrium. Then, a synchronization mechanism based on the adaptive control theory was developed between two identical new systems (master and slave). The adaptive control laws are derived based on synchronization error dynamics of the state variables for the master and slave. Consequently, the update laws of the slave parameters are obtained, where the slave parameters are assumed to be uncertain and are estimated corresponding to the master parameters by the synchronization process. Furthermore, Arduino Due boards were used to implement the proposed system in order to demonstrate its practicality in real-world applications. The simulation experimental results were obtained by MATLAB and the Arduino Due boards, respectively, with a good consistency between the simulation results and the experimental results, indicating that the new fractional order chaotic system is capable of being employed in real-world applications.

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