Development of Autonomous Mobile Robot Based on Accurate Map in the Tsukuba Challenge 2014

2015 ◽  
Vol 27 (4) ◽  
pp. 346-355 ◽  
Author(s):  
Junji Eguchi ◽  
◽  
Koichi Ozaki
Keyword(s):  
Mobile Robots ◽  
Global Positioning System ◽  
Autonomous Navigation ◽  
Control Method ◽  
Autonomous Mobile Robots ◽  
Graphical Interface ◽  
Velocity Control ◽  
Laser Scanners ◽  
Global Positioning ◽  
Navigation Method

<div class=""abs_img""> <img src=""[disp_template_path]/JRM/abst-image/00270004/04.jpg"" width=""300"" /> Navigation method for mobile robots</div> We describe a navigation method for autonomous mobile robots and detail knowledge obtained through Tsukuba Challenge 2014 trial runs. The challenge requires robots to navigate autonomously 1.4 km in an urban area and to search for five persons in three areas. Accurate maps are important tools in localization on complex courses in autonomous outdoor navigation. We constructed an occupancy grid map using laser scanners, gyro-assisted odometry and a differential global positioning system (DGPS). In this study, we use maps as a graphical interface. Namely, by using maps, we give environmental information, untravelable low objects such as curb stones, and areas in nonsearches for “target” persons. For the purpose of increasing the map reusability, we developed a waypoint editor, which can modify waypoints on maps to fit a course to a situation. We also developed a velocity control method that the robot uses to follow pedestrians and other robot by keeping safety distance on the course. As a result, our robot took part five of seven official trial runs to get to the goal. This indicates that the autonomous navigation method was stable in the Tsukuba Challenge 2014 urban environment. </span>

scholarly journals Interval Type-2 Neural Fuzzy Controller-Based Navigation of Cooperative Load-Carrying Mobile Robots in Unknown Environments

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4181 ◽  
Author(s):  
Chun-Hui Lin ◽  
Shyh-Hau Wang ◽  
Cheng-Jian Lin
Keyword(s):  
Mobile Robots ◽  
Control Method ◽  
Fuzzy Controller ◽  
Bee Colony ◽  
Load Carrying ◽  
Navigation Control ◽  
Interval Type ◽  
Navigation Method ◽  
Neural Fuzzy

In this paper, a navigation method is proposed for cooperative load-carrying mobile robots. The behavior mode manager is used efficaciously in the navigation control method to switch between two behavior modes, wall-following mode (WFM) and goal-oriented mode (GOM), according to various environmental conditions. Additionally, an interval type-2 neural fuzzy controller based on dynamic group artificial bee colony (DGABC) is proposed in this paper. Reinforcement learning was used to develop the WFM adaptively. First, a single robot is trained to learn the WFM. Then, this control method is implemented for cooperative load-carrying mobile robots. In WFM learning, the proposed DGABC performs better than the original artificial bee colony algorithm and other improved algorithms. Furthermore, the results of cooperative load-carrying navigation control tests demonstrate that the proposed cooperative load-carrying method and the navigation method can enable the robots to carry the task item to the goal and complete the navigation mission efficiently.

scholarly journals An autonomous navigational system using GPS and computer vision for futuristic road traffic

2022 ◽  
Vol 12 (1) ◽  
pp. 179
Author(s):  
Prabha Ramasamy ◽  
Mohan Kabadi
Keyword(s):  
Computer Vision ◽  
Global Positioning System ◽  
Navigation System ◽  
Autonomous Navigation ◽  
Road Traffic ◽  
Positioning System ◽  
Traffic System ◽  
Global Positioning ◽  
Navigational System

Navigational service is one of the most essential dependency towards any transport system and at present, there are various revolutionary approaches that has contributed towards its improvement. This paper has reviewed the global positioning system (GPS) and computer vision based navigational system and found that there is a large gap between the actual demand of navigation and what currently exists. Therefore, the proposed study discusses about a novel framework of an autonomous navigation system that uses GPS as well as computer vision considering the case study of futuristic road traffic system. An analytical model is built up where the geo-referenced data from GPS is integrated with the signals captured from the visual sensors are considered to implement this concept. The simulated outcome of the study shows that proposed study offers enhanced accuracy as well as faster processing in contrast to existing approaches.

scholarly journals Position and Posture Measurements Using Laser Projection Markers for Infrastructure Inspection

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 807
Author(s):  
Tohru Sasaki ◽  
Ryo Shioya ◽  
Toshitaka Sakai ◽  
Shunki Kinoshita ◽  
Takahito Nojiri ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Global Positioning System ◽  
Measurement Errors ◽  
Image Sensor ◽  
Target Structure ◽  
Inspection Method ◽  
Global Positioning ◽  
Conventional Structure ◽  
Infrastructure Inspection

Infrastructure such as roads, tunnels and bridges needs periodical inspection. The conventional structure inspection method, in which a human inspector uses a crack gauge, may lead to problems such as measurement errors and lengthy inspection times. Mobile robots and image processing have been used in the infrastructure inspection field. An image sensor or any sensor is used for measuring the state of the infrastructures. It is necessary that the mobile robot knows its own position and posture during automatic inspection. Generally, the Global Positioning System (GPS) has been used to sense the position of the mobile robot. However, GPS is not usable in places with the ceilings such as under bridges and in tunnels. Therefore, we developed a system to sense the position and posture of mobile robots. This system uses laser projection markers and cameras, and it has a very simple configuration. The camera photographs a target structure and projection laser markers, and the position and posture of the camera and mobile robot were calculated by an image application. The system makes infrastructure inspection more effective and decreases the time needed for inspection. In this paper, we examined the number of necessary laser markers, and we verified our method by experiment.

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.

Optical Flow-Based Monocular Vision/INS Integrated Navigation for Mobile Robot Indoors

2014 ◽  
Vol 538 ◽  
pp. 375-378 ◽  
Author(s):  
Xi Yuan Chen ◽  
Jing Peng Gao ◽  
Yuan Xu ◽  
Qing Hua Li
Keyword(s):  
Mobile Robot ◽  
Optical Flow ◽  
Global Positioning System ◽  
Autonomous Navigation ◽  
Image Sequences ◽  
Velocity Estimation ◽  
Monocular Vision ◽  
Integrated Navigation ◽  
Global Positioning ◽  
Flow Algorithm

This paper proposed a new algorithm for optical flow-based monocular vision (MV)/ inertial navigation system (INS) integrated navigation. In this mode, a downward-looking camera is used to get the image sequences, which is used to estimate the velocity of the mobile robot by using optical flow algorithm. INS is employed for the yaw variation. In order to evaluate the performance of the proposed method, a real indoor test has done. The result shows that the proposed method has good performance for velocity estimation. It can be applied to the autonomous navigation of mobile robots when the Global Positioning System (GPS) and code wheel is unavailable.

USV attitude estimation: an approach using quaternion in direction cosine matrix

Robotica ◽  
2014 ◽  
Vol 34 (5) ◽  
pp. 995-1009 ◽  
Author(s):  
Chiemela Onunka ◽  
Glen Bright ◽  
Riaan Stopforth
Keyword(s):  
Global Positioning System ◽  
Autonomous Navigation ◽  
Low Cost ◽  
Direction Cosine ◽  
Attitude Estimation ◽  
Measurement Unit ◽  
Advanced Technique ◽  
Navigation Data ◽  
Global Positioning ◽  
Direction Cosine Matrix

SUMMARYPositioning and navigation data for unmanned surface vehicles (USVs) are extracted using the Global Positioning System (GPS) and the Inertial Navigation System (INS) integrated with an inertial measurement unit (IMU). The integration of quaternion with direction cosine matrix (DCM) with the aim of obtaining high accuracy with complete system independence has been effectively used to supply position and attitude information for autonomous navigation of marine crafts. A DCM integrated with a quaternion provided an advanced technique for precise USV attitude estimation and position determination using low-cost sensors. This paper presents the implementation of an INS developed by the integration of DCM and quaternion.

Global Positioning System (GPS) autonomous navigation

2002 ◽  
Author(s):  
M.P. Ananda ◽  
H. Bernstein ◽  
K.E. Cunningham ◽  
W.A. Feess ◽  
E.G. Stroud
Keyword(s):  
Global Positioning System ◽  
Autonomous Navigation ◽  
Positioning System ◽  
Global Positioning

Coupling in-flight trajectory planning and flocking for multiple autonomous parafoils

2012 ◽  
Vol 226 (6) ◽  
pp. 691-720 ◽  
Author(s):  
A Rosich ◽  
P Gurfil
Keyword(s):  
Global Positioning System ◽  
Autonomous Navigation ◽  
Degrees Of Freedom ◽  
Reference Trajectory ◽  
Flight Trajectory ◽  
Multiagent Simulation ◽  
Six Degrees Of Freedom ◽  
Wide Range ◽  
Global Positioning ◽  
Simple Rules

Much effort has been invested during the past decades in design of parafoils for a wide range of payloads and in development of means for their guidance. Existing parafoils are capable of autonomous navigation using the global positioning system and other onboard sensors. The purpose of this study is to explore the advantages of coordination among multiple autonomous parafoils. Each parafoil is able to navigate to the target on its own by following a real-time-generated reference trajectory. A new method for trajectory generation is presented and behaviour-based rules are developed that control the relative motion of the descending parafoils. The set of simple rules results in an emergent behaviour known as flocking. The coupling between trajectory following and flocking is studied in a multiagent simulation. The simulation uses a realistic six-degrees-of-freedom model of a heavy cargo parafoil. The obtained results demonstrate the possibility of flocking behaviour for guided parafoils. The flocking rules ensure safe separation between the vehicles headed for the same target and allow the parafoils to follow a reference trajectory as a group.

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