A Mobile Robot Estimating the Real-time Moving Sound Sources by using the Curvature Trajectory

It is proposed to determine the velocity of the embedded mobile robot in a real world test environment .The test environment considered in this work is the man-made road surfaces like cement road surface, sand road surface, Bituminous Thar road surface, Grass road surface and loose gravel road surfaces etc. First, fuzzy logic control of velocity estimation a mobile robot is done using Matlab for the different surfaces. Then the real time tests on the different surfaces were carried out. The simulated values are compared with the test values. The comparison showed that the simulation values were close to the real time test values.

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Using Sun’s Java Real-Time System to Manage Behavior-Based Mobile Robot Controllers

Journal of Robotics ◽

10.1155/2011/525724 ◽

2011 ◽

Vol 2011 ◽

pp. 1-11

Author(s):

Andrew McKenzie ◽

Shameka Dawson ◽

Fei Hu ◽

Monica Anderson

Keyword(s):

Mobile Robot ◽

Real Time ◽

Challenging Behavior ◽

Timing Constraints ◽

Time System ◽

Real Time System ◽

Garbage Collector ◽

The Real ◽

Robot Controller ◽

Behavior Based

Implementing a robot controller that can effectively manage limited resources in a deterministic, real-time manner is challenging. Behavior-based architectures that decompose autonomy into levels of intelligence are popular due to their robustness but do not provide real-time features that enforce timing constraints or support determinism. We propose an architecture and approach for using the real-time features of the Real-Time Specification for Java (RTSJ) in a behavior-based mobile robot controller to show that timing constraints affect performance. This is accomplished by extending a real-time aware architecture that explicitly enumerates timing requirements for each behavior. It is not enough to reduce latency. The usefulness of this approach is demonstrated via an implementation on Solaris 10 and the Sun Java Real-Time System (Java RTS). Experimental results are obtained using a K-team Koala robot performing path following with four composite behaviors. Experiments were conducted using several task period sets in three cases: real-time threads with the real-time garbage collector, real-time threads with the non- real-time garbage collector, and non-real-time threads with the non-real-time garbage collector. Results show that even if latency and determinism are improved, the timing of each individual behavior significantly affects task performance.

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Delay Dependent Stability in the Real Time Control of a Mobile Robot Using Neural Networks

2007 International Symposium on Computational Intelligence in Robotics and Automation ◽

10.1109/cira.2007.382844 ◽

2007 ◽

Author(s):

V. Sree Krishna Chaitanya ◽

P. Dwarikanath Patro ◽

Prabir Kumar Sarkar

Keyword(s):

Neural Networks ◽

Mobile Robot ◽

Real Time ◽

Real Time Control ◽

The Real ◽

Time Control ◽

Delay Dependent ◽

Delay Dependent Stability

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Applications based on electromyography sensors

ITM Web of Conferences ◽

10.1051/itmconf/20192902007 ◽

2019 ◽

Vol 29 ◽

pp. 02007

Author(s):

Robert Kristof ◽

Cristian Moldovan ◽

Valentin Ciupe ◽

Inocenţiu Maniu ◽

Magdalena Banda

Keyword(s):

Mobile Robot ◽

Real Time ◽

Industrial Robot ◽

Experimental Results ◽

Real Time Control ◽

The Real ◽

Time Control ◽

Myo Armband ◽

Tracked Mobile Robot

This paper presents our work regarding two different applications that use the electromyography sensors incorporated in the Thalmic Labs Myo Armband. The first application is about the HumanMachine Interface (HMI) for controlling an industrial robot bycreating the environment for the user to control a robot’s gripper position just by moving his arm. The second application refers to the real time control of a tracked mobile robot that is built with the Arduino development board. For each application thesystem design and the experimental results are presented.

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Development of Autonomous Mobile Robot for Obstacle Avoidance

Journal of Robotics and Mechatronics ◽

10.20965/jrm.1993.p0481 ◽

1993 ◽

Vol 5 (5) ◽

pp. 481-486 ◽

Cited By ~ 1

Author(s):

Masafumi Uchida ◽

◽

Syuichi Yokoyama ◽

Hideto Ide ◽

Keyword(s):

Mobile Robot ◽

Motion Planning ◽

Real Time ◽

Obstacle Avoidance ◽

Potential Field ◽

Potential Method ◽

Working Environment ◽

Planning Problem ◽

Autonomous Mobile Robot ◽

The Real

The potential method is superior for solving the problem of motion planning; however, it must address the problem of the real-time generation of potential field. Obstacle avoidance is a motion planning problem. In a previous study, we investigated the real-time generation of potential field. Based on parallel processing with element group, we proposed the system by Sensory Point Moving (SPM) method. As a result of computer simulation, it was confirmed that the SPM method is effective for generating an obstacle avoidance path in 2-D and a more complex working environment like a 3-D one. In this paper, we discuss the development of autonomous mobile robot for obstacle avoidance based on the SPM method.

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Research on the Peripheral Sound Visualization Using the Improved Ripple Mode

Advanced Engineering Forum ◽

10.4028/www.scientific.net/aef.2-3.123 ◽

2011 ◽

Vol 2-3 ◽

pp. 123-126

Author(s):

Bin Xu ◽

Dan Yang ◽

Yun Yi Zhang ◽

Xu Wang

Keyword(s):

Neural Network ◽

Power Spectrum ◽

Real Time ◽

Sound Source ◽

Sound Intensity ◽

Visualization Method ◽

Audio Signals ◽

Sound Sources ◽

The Real ◽

Spectrum Function

In this paper, we proposed a peripheral sound visualization method based on improved ripple mode for the deaf. In proposed mode, we designed the processes of transforming sound intensity and exterminating the locations of sound sources. We used power spectrum function to determine the sound intensity. ARTI neural network was subtly applied to identify which kind of the real-time input sound signals and to display the locations of the sound sources. We present the software that aids the development of peripheral displays and four sample peripheral displays are used to demonstrate our toolkit’s capabilities. The results show that the proposed ripple mode correctly showed the information of combination of the sound intensity and location of the sound source and ART1 neural network made accurate identifications for input audio signals. Moreover, we found that participants in the research were more likely to achieve more information of locations of sound sources.

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Enabling Flexibility in Manufacturing by Integrating Shopfloor and Process Perception for Mobile Robot Workers

Applied Sciences ◽

10.3390/app11093985 ◽

2021 ◽

Vol 11 (9) ◽

pp. 3985

Author(s):

Angelos Christos Bavelos ◽

Niki Kousi ◽

Christos Gkournelos ◽

Konstantinos Lotsaris ◽

Sotiris Aivaliotis ◽

...

Keyword(s):

Mobile Robot ◽

Real Time ◽

Sensor Data ◽

The Real ◽

Digital World ◽

Autonomous Operation ◽

Robot Perception ◽

Process Understanding ◽

Smart Control ◽

Human Operators

Robotic flexibility in industry is becoming more and more relevant nowadays, especially with the rise of the Industry 4.0 concept. This paper presents a smart execution control framework for enabling the autonomous operation of flexible mobile robot workers. These robot resources are able to autonomously navigate the shopfloor, undertaking multiple operations while acting as assistants to human operators. To enable this autonomous behavior, the proposed framework integrates robot perception functions for the real-time shopfloor and process understanding while orchestrating the process execution. A Digital World Model is deployed synthesizing the sensor data coming from multiple 2D and 3D sensors from the shopfloor. This model is consumed for the perception functions enabling the real-time shopfloor and process perception by the robot workers. This smart control system has been applied and validated in a case study from the automotive sector.

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