Autonomous navigation and environment modeling for MAVs in 3-D enclosed industrial environments

2013 ◽  
Vol 64 (9) ◽  
pp. 1161-1177 ◽  
Author(s):  
Qing Li ◽  
Da-Chuan Li ◽  
Qin-fan Wu ◽  
Liang-wen Tang ◽  
Yan Huo ◽  
...  
Keyword(s):  
Autonomous Navigation ◽  
Environment Modeling ◽  
Industrial Environments

scholarly journals Autonomous Navigation Framework for Intelligent Robots Based on a Semantic Environment Modeling

2020 ◽  
Vol 10 (9) ◽  
pp. 3219 ◽  
Author(s):  
Sung-Hyeon Joo ◽  
Sumaira Manzoor ◽  
Yuri Goncalves Rocha ◽  
Sang-Hyeon Bae ◽  
Kwang-Hee Lee ◽  
...  
Keyword(s):  
Autonomous Navigation ◽  
Action Planning ◽  
Environment Modeling ◽  
Modeling Framework ◽  
Intelligent Robots ◽  
Semantic Models ◽  
Autonomous Robot Navigation ◽  
Environment Maps ◽  
Implicit And Explicit ◽  
And Behavior

Humans have an innate ability of environment modeling, perception, and planning while simultaneously performing tasks. However, it is still a challenging problem in the study of robotic cognition. We address this issue by proposing a neuro-inspired cognitive navigation framework, which is composed of three major components: semantic modeling framework (SMF), semantic information processing (SIP) module, and semantic autonomous navigation (SAN) module to enable the robot to perform cognitive tasks. The SMF creates an environment database using Triplet Ontological Semantic Model (TOSM) and builds semantic models of the environment. The environment maps from these semantic models are generated in an on-demand database and downloaded in SIP and SAN modules when required to by the robot. The SIP module contains active environment perception components for recognition and localization. It also feeds relevant perception information to behavior planner for safely performing the task. The SAN module uses a behavior planner that is connected with a knowledge base and behavior database for querying during action planning and execution. The main contributions of our work are the development of the TOSM, integration of SMF, SIP, and SAN modules in one single framework, and interaction between these components based on the findings of cognitive science. We deploy our cognitive navigation framework on a mobile robot platform, considering implicit and explicit constraints for autonomous robot navigation in a real-world environment. The robotic experiments demonstrate the validity of our proposed framework.

scholarly journals Realtime autonomous navigation in V-Rep based static and dynamic environment using EKF-SLAM

2021 ◽  
Vol 10 (4) ◽  
pp. 296
Author(s):  
Umme Hani ◽  
Lubna Moin
Keyword(s):  
Mobile Robot ◽  
Autonomous Navigation ◽  
Dynamic Environment ◽  
Mobile Robot Navigation ◽  
Autonomous Mobile Robot ◽  
Environment Modeling ◽  
Localization And Mapping ◽  
Differential Drive Robot ◽  
Unpredictable Environment ◽  
Primary Focus

<p>Localization in an autonomous mobile robot allows it to operate autonomously in an unknown and unpredictable environment with the ability to determine its position and heading. Simultaneous localization and mapping (SLAM) are introduced to solve the problem where no prior information about the environment is available either static or dynamic to achieve standard map-based localization. The primary focus of this research is autonomous mobile robot navigation using the extended Kalman filter (EKF)-SLAM environment modeling technique which provides higher accuracy and reliability in mobile robot localization and mapping results. In this paper, EKF-SLAM performance is verified by simulations performed in a static and dynamic environment designed in V-REP i.e., 3D Robot simulation environment. In this work SLAM problem of two-wheeled differential drive robot i.e., Pioneer 3-DX in indoor static and dynamic environment integrated with Laser range finder i.e., Hokuyo URG-04LX- UG01, LIDAR, and Ultrasonic sensors is solved. EKF-SLAM scripts are developed using MATLAB that is linked to V-REP via remote API feature to evaluate EKF-SLAM performance. The reached results confirm the EKF- SLAM is a reliable approach for real-time autonomous navigation for mobile robots in comparison to other techniques.</p>

Geophysical Support of Magnetometer Autonomous Navigation Systems

2020 ◽  
Author(s):  
Vladimir T. Minligareev ◽  
Elena N. Khotenko ◽  
Vadim V. Tregubov ◽  
Tatyana V. Sazonova ◽  
Vaclav L. Kravchenok
Keyword(s):  
Autonomous Navigation ◽  
Navigation Systems

Autonomous Navigation and Obstacle Avoidance

2009 ◽  
Author(s):  
Jesse Berger ◽  
Cory Carson ◽  
Massood Towhidnejad ◽  
Richard Stansbury
Keyword(s):  
Obstacle Avoidance ◽  
Autonomous Navigation

Orbital Stellar Stereoscopic Observatory Project: Motivation and Autonomous Navigation in the Heliocentric Transfer and Operational Orbits

2016 ◽  
Vol 4 (3) ◽  
Author(s):  
V.V. Kouprianov ◽  
S.D. Tsekmeister ◽  
A.V. Bakholdin ◽  
G.V. Levko ◽  
M.S. Chubey ◽  
...  
Keyword(s):  
Autonomous Navigation
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