Virtual Reality based Mobile Robot Navigation in Greenhouse Environment

The difficulties of transporting heavy mobile robots limit robotic experiments in agriculture. Virtual reality however, offers an alternative to conduct experiments in agriculture. This paper presents an application of virtual reality in a robot navigational experiment using SolidWorks and simulated into MATLAB. Trajectories were initiated using Probabilistic Roadmap and compared based on travel time, distance and tracking error, and the efficiency was calculated. The simulation results showed that the proposed method was able to conduct the navigational experiment inside the virtual environment. U-turn trajectory was chosen as the best trajectory for crop inspection with 82.7% efficiency.

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Mobile Robots Navigation, Mapping, and Localization Part I

Encyclopedia of Artificial Intelligence ◽

10.4018/978-1-59904-849-9.ch158 ◽

2011 ◽

pp. 1072-1079

Author(s):

Lee Gim Hee ◽

Marcelo H. Ang Jr.

Keyword(s):

Mobile Robot ◽

Mobile Robots ◽

Material Handling ◽

Robot Navigation ◽

Emerging Market ◽

Autonomous Mobile Robots ◽

Mobile Robot Navigation ◽

The Military ◽

The Given ◽

Fundamental Requirement

The development of autonomous mobile robots is continuously gaining importance particularly in the military for surveillance as well as in industry for inspection and material handling tasks. Another emerging market with enormous potential is mobile robots for entertainment. A fundamental requirement for autonomous mobile robots in most of its applications is the ability to navigate from a point of origin to a given goal. The mobile robot must be able to generate a collision-free path that connects the point of origin and the given goal. Some of the key algorithms for mobile robot navigation will be discussed in this article.

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A knowledge based fuzzy-probabilistic roadmap method for mobile robot navigation

Applied Soft Computing ◽

10.1016/j.asoc.2019.03.055 ◽

2019 ◽

Vol 79 ◽

pp. 391-409 ◽

Cited By ~ 13

Author(s):

J.C. Mohanta ◽

Anupam Keshari

Keyword(s):

Mobile Robot ◽

Robot Navigation ◽

Mobile Robot Navigation ◽

Knowledge Based ◽

Probabilistic Roadmap ◽

Probabilistic Roadmap Method

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Hexagonal Grid-Based Framework for Mobile Robot Navigation

Remote Sensing ◽

10.3390/rs13214216 ◽

2021 ◽

Vol 13 (21) ◽

pp. 4216

Author(s):

Piotr Duszak ◽

Barbara Siemiątkowska ◽

Rafał Więckowski

Keyword(s):

Path Planning ◽

Mobile Robot ◽

Mobile Robots ◽

Robot Navigation ◽

Hexagonal Lattice ◽

Planning Method ◽

Experimental Results ◽

Mobile Robot Navigation ◽

Rectangular Grid ◽

Grid Based

The paper addresses the problem of mobile robots’ navigation using a hexagonal lattice. We carried out experiments in which we used a vehicle equipped with a set of sensors. Based on the data, a traversable map was created. The experimental results proved that hexagonal maps of an environment can be easily built based on sensor readings. The path planning method has many advantages: the situation in which obstacles surround the position of the robot or the target is easily detected, and we can influence the properties of the path, e.g., the distance from obstacles or the type of surface can be taken into account. A path can be smoothed more easily than with a rectangular grid.

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An Approach in Designing Hierarchy of Fuzzy Behaviors for Mobile Robot Navigation

Journal of Advanced Computational Intelligence and Intelligent Informatics ◽

10.20965/jaciii.2007.p0268 ◽

2007 ◽

Vol 11 (3) ◽

pp. 268-275

Author(s):

Long Thanh Ngo ◽

◽

Long The Pham ◽

Phuong Hoang Nguyen ◽

Kaoru Hirota ◽

...

Keyword(s):

Mobile Robot ◽

Fuzzy Controller ◽

Robot Navigation ◽

Individual Behavior ◽

Mobile Robot Navigation ◽

Simulation Results

We propose an approach to the design hierarchical behaviors for mobile robot navigation in which robot perceives information about the environment from sensor then computes fuzzy output for individual behavior. Each behavior involves a fuzzy controller with the same output. The behavior hierarchy combines commands from fuzzy behavior output and defuzzifies it to archive crisp values for controlling the direction in which robot moves. Simulation results and statistics demonstrate the feasibility of our proposal.

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Design and Implementation of a 3D Range Scanner for Mobile Robots

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.572.644 ◽

2013 ◽

Vol 572 ◽

pp. 644-647

Author(s):

Gökhan Aslan ◽

Erhan Ilhan Konukseven ◽

Buğra Koku

Keyword(s):

Mobile Robot ◽

Mobile Robots ◽

Autonomous Navigation ◽

Robot Navigation ◽

Low Cost ◽

Vertical Axis ◽

Field Of View ◽

Mobile Robot Navigation ◽

Design And Implementation ◽

Speed Accuracy

In an efficient autonomous navigation and exploration, the robots should sense the environment as exactly as possible in real-time and act correctly on the basis of the acquired 3D data. Laser scanners have been used for the last 30 years for mobile robot navigation. However, they often did not enough speed, accuracy and field of view. In this paper we present the design and implementation of a scanning platform, which can be used for both outdoor and indoor mobile robot navigation and mapping. A 3D scanning platform based on a 2D laser rangefinder was designed in compact way for fast and accurate mapping with maximum field of view. The range finder is rotated around the vertical axis to extract the 3D indoor information. However, the scanner is designed to be placed in any direction on a mobile robot. The designed mechanism provides 360º degree horizontal by 240º degree vertical field of view. The maximum resolution is 0.36º degrees in elevation and variable in azimuth (0.1 degrees if scanning platform is set to complete a 360º degree rotation in 3.6 seconds). The proposed low cost compact design is tested by scanning a physical environment with known dimensions to show that it can be used as a precise and reliable high quality 3D sensor for autonomous mobile robots.

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ADAPTIVE CONTROL OF MOBILE ROBOTS USING A NEURAL NETWORK

International Journal of Neural Systems ◽

10.1142/s0129065701000643 ◽

2001 ◽

Vol 11 (03) ◽

pp. 211-218 ◽

Cited By ~ 2

Author(s):

Celso de Sousa ◽

Elder Moreira Hermerly

Keyword(s):

Neural Network ◽

Adaptive Control ◽

Mobile Robot ◽

Mobile Robots ◽

Robot Navigation ◽

Control Approach ◽

On Line ◽

Simulation Results ◽

Previous Learning

A Neural Network - based control approach for mobile robot is proposed. The weight adaptation is made on-line, without previous learning. Several possible situations in robot navigation are considered, including uncertainties in the model and presence of disturbance. Weight adaptation laws are presented as well as simulation results.

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A Human-Inspired Method for Mobile Robot Navigation

Volume 6A: 37th Mechanisms and Robotics Conference ◽

10.1115/detc2013-13523 ◽

2013 ◽

Cited By ~ 1

Author(s):

Fatemeh Heidari ◽

Reza Fotouhi

Keyword(s):

Mobile Robot ◽

Mobile Robots ◽

Real Time ◽

Robot Navigation ◽

Mobile Robot Navigation ◽

Laser Range Finder ◽

Deadlock Detection ◽

Sensory Data ◽

Unstructured Environment ◽

And Coping

A new method for real-time navigation of mobile robots in complex and mostly unstructured environment is presented. This novel human-inspired method (HIM) uses distance-based sensory data from a laser range finder for real-time navigation of a wheeled mobile robot in unknown and cluttered settings. The approach requires no prior knowledge from the environment and is easy to be implemented for real-time navigation of mobile robots. HIM endows the robot a human-like ability for reasoning about the situations to reach a predefined goal point while avoiding static and moving or unforeseen obstacles; this makes the proposed strategy efficient and effective. Results indicate that HIM is capable of creating smooth (no oscillations) paths for safely navigating the mobile robot, and coping with fluctuating and imprecise sensory data from uncertain environment. HIM specifies the best path ahead, according to the situation of encountered obstacles, preventing the robot to get trapped in deadlock and impassable conditions. This deadlock detection and avoidance is a significant ability of HIM. Also, this algorithm is designed to analyze the environment for detecting both negative and positive obstacles in off-road terrain. The simulation and experimental results of HIM is compared with a fuzzy logic based (FLB) approach.

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