scholarly journals Energy Model for a Differential Guide Mobile Robot using Modelica Language

2021 ◽  
Vol 12 (5) ◽  
pp. 1159-1166
Author(s):  
Fadlo Said, Et. al.
Keyword(s):  
Energy Consumption ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Energy Model ◽  
Energy Models

Energy consumption is an important element in the autonomy of mobile robots. In this paper, an energy model has been developed in Modelica language. The power of the Modelica® language is shown by simulating the energy model for a differential guide mobile robot as well as the motors. The model is tested with typical motor energy, mixed energy models, and a trapezoidal velocity as input.

scholarly journals Energy Modeling and Power Measurement for Mobile Robots

Energies ◽  
2018 ◽  
Vol 12 (1) ◽  
pp. 27 ◽  
Author(s):  
Linfei Hou ◽  
Liang Zhang ◽  
Jongwon Kim
Keyword(s):  
Control System ◽  
Energy Consumption ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Electrical Power ◽  
Energy Model ◽  
Energy Modeling ◽  
Power Measurement ◽  
Sensor System ◽  
System Control

To improve the energy efficiency of a mobile robot, a novel energy modeling method for mobile robots is proposed in this paper. The robot can calculate and predict energy consumption through the energy model, which provides a guide to facilitate energy-efficient strategies. The energy consumption of the mobile robot is first modeled by considering three major factors: the sensor system, control system, and motion system. The relationship between the three systems is elaborated by formulas. Then, the model is utilized and experimentally tested in a four-wheeled Mecanum mobile robot. Furthermore, the power measurement methods are discussed. The energy consumption of the sensor system and control system was at the milliwatt level, and a Monsoon power monitor was used to accurately measure the electrical power of the systems. The experimental results showed that the proposed energy model can be used to predict the energy consumption of the robot movement processes in addition to being able to efficiently support the analysis of the energy consumption characteristics of mobile robots.

scholarly journals Modeling and Analysis of the Obstacle-Avoidance Strategies for a Mobile Robot in a Dynamic Environment

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Rui Wang ◽  
Ming Wang ◽  
Yong Guan ◽  
Xiaojuan Li
Keyword(s):  
Energy Consumption ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Obstacle Avoidance ◽  
Decision Process ◽  
Dynamic Environment ◽  
Formal Models ◽  
Modeling And Analysis ◽  
Avoidance Strategies ◽  
Markov Decision

Obstacle avoidance is a key performance of mobile robots. However, its experimental verification is rather difficult, due to the probabilistic behaviors of both the robots and the obstacles. This paper presents the Markov Decision Process based probabilistic formal models for three obstacle-avoidance strategies of a mobile robot in an uncertain dynamic environment. The models are employed to make analyses in PRISM, and the correctness of the analysis results is verified by MATLAB simulations. Finally, the minimum time and the energy consumption are determined by further analyses in PRISM, which prove to be useful in finding the optimal strategy. The present work provides a foundation for the probabilistic formal verification of more complicated obstacle-avoidance strategies.

scholarly journals Energy Estimation Based on Path Tracking for a Differential Drive Wheeled Mobile Robot

2021 ◽  
Vol 229 ◽  
pp. 01029
Author(s):  
Said Fadlo ◽  
Nabila Rabbah ◽  
Abdelhafid Ait Elmahjoub
Keyword(s):  
Energy Consumption ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Complex Analysis ◽  
Path Following ◽  
Path Tracking ◽  
Energy Estimation ◽  
Analysis And Design ◽  
Differential Drive ◽  
Model Complex

To improve the energy efficiency of mobile robots and increase their time of operation, a comprehensive energy model is needed. Having such a model requires a lot of complex analysis and design time. There has been a lot of research into optimizing the power consumption of mobile robots but have not benefited from the advantages of languages to model complex cyber-physical systems. In this work, we used the Simscape™ MATLAB® environment to simplify and speed up the design of an energy consumption model of a differential drive mobile robot. We also estimated the energy consumption of the mobile in a different path tracking scenario. Our results show that is possible to obtain a good accuracy of path following with acceptable energy consumption.

scholarly journals Benchmark Framework for Mobile Robots Navigation Algorithms

2014 ◽  
Vol 23 (36) ◽  
pp. 65
Author(s):  
Nelson David Muñoz-Ceballos ◽  
Jaime Alejandro Valencia-Velásquez
Keyword(s):  
Energy Consumption ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Performance Metrics ◽  
Autonomous Mobile Robot ◽  
Educational Tool ◽  
Science Technology ◽  
Energy Consumption Optimization ◽  
Navigation Algorithms ◽  
Robot Systems

<p>Despite the wide variety of studies and research on mobile robot systems, performance metrics are not often examined. This makes difficult to establish an objective comparison of achievements. In this paper, the navigation of an autonomous mobile robot is evaluated. Several metrics are described. These metrics, collectively, provide an indication of navigation quality, useful for comparing and analyzing navigation algorithms of mobile robots. This method is suggested as an educational tool, which allows the student to optimize the algorithms quality, relating to important aspects<br />of science, technology and engineering teaching, as energy consumption, optimization and design.</p>

scholarly journals Constructing the optimal power algorithm for AS/RS systems using multi-mobile robots

2021 ◽  
Vol 877 (1) ◽  
pp. 012014
Author(s):  
H M Hameed ◽  
A T Rashid ◽  
M T Rashid ◽  
K A Al Amry
Keyword(s):  
Energy Consumption ◽  
Power Consumption ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Energy Saving ◽  
Optimal Path ◽  
Electrical Power ◽  
Route Planning ◽  
Optimal Power ◽  
Consumption Efficiency

Abstract For any mobile system there is especially advantageous from a business perspective to develop energy-saving techniques that also extend to existing production processes. Therefore, looking for ways to enhance the energy efficiency of robot operations to maximize energy consumption efficiency is of considerable significance, a route-planning issue that refers to finding the shortest path to meet the predetermined goal location in a certain complex environment. So, one of the energy saving methods for a multi-mobile robot environment is to find the optimal path for a mobile robot that can improve power consumption. In this paper, an optimal power algorithm for “automatic storage and retrieval system” using multi-mobile robots is introduced based on efficient motion planning among a group of multi-mobile robots that gives a significant improvement in the level of energy consumption. Energy mechanism can be achieved using electrical power quantities on real robots, models or analytical equations based on robots’ physical model. The simulation results indicate that the algorithm enhanced power consumption efficiency.

Ultrasonic sensor system for the uses in intelligent motion control system of a mobile robots group

2010 ◽  
Vol 7 ◽  
pp. 109-117
Author(s):  
O.V. Darintsev ◽  
A.B. Migranov ◽  
B.S. Yudintsev
Keyword(s):  
Control System ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Motion Control ◽  
High Speed ◽  
Ultrasonic Sensor ◽  
Sensor System ◽  
Motion Control System ◽  
Speed Sensor ◽  
Working Space

The article deals with the development of a high-speed sensor system for a mobile robot, used in conjunction with an intelligent method of planning trajectories in conditions of high dynamism of the working space.

scholarly journals Predicting the Energy Consumption of a Robot in an Exploration Task Using Optimized Neural Networks

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 920
Author(s):  
Liesle Caballero ◽  
Álvaro Perafan ◽  
Martha Rinaldy ◽  
Winston Percybrooks
Keyword(s):  
Neural Network ◽  
Energy Consumption ◽  
Mobile Robot ◽  
Energy Budget ◽  
Dynamic Models ◽  
Pearson Correlation ◽  
Experimental Conditions ◽  
Grid Map ◽  
Proposed Model ◽  
Exploration Task

This paper deals with the problem of determining a useful energy budget for a mobile robot in a given environment without having to carry out experimental measures for every possible exploration task. The proposed solution uses machine learning models trained on a subset of possible exploration tasks but able to make predictions on untested scenarios. Additionally, the proposed model does not use any kinematic or dynamic models of the robot, which are not always available. The method is based on a neural network with hyperparameter optimization to improve performance. Tabu List optimization strategy is used to determine the hyperparameter values (number of layers and number of neurons per layer) that minimize the percentage relative absolute error (%RAE) while maximize the Pearson correlation coefficient (R) between predicted data and actual data measured under a number of experimental conditions. Once the optimized artificial neural network is trained, it can be used to predict the performance of an exploration algorithm on arbitrary variations of a grid map scenario. Based on such prediction, it is possible to know the energy needed for the robot to complete the exploration task. A total of 128 tests were carried out using a robot executing two exploration algorithms in a grid map with the objective of locating a target whose location is not known a priori by the robot. The experimental energy consumption was measured and compared with the prediction of our model. A success rate of 96.093% was obtained, measured as the percentage of tests where the energy budget suggested by the model was enough to actually carry out the task when compared to the actual energy consumed in the test, suggesting that the proposed model could be useful for energy budgeting in actual mobile robot applications.

scholarly journals Practical Model for Energy Consumption Analysis of Omnidirectional Mobile Robot

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1800
Author(s):  
Linfei Hou ◽  
Fengyu Zhou ◽  
Kiwan Kim ◽  
Liang Zhang
Keyword(s):  
Energy Consumption ◽  
Power Consumption ◽  
Mobile Robot ◽  
Load Capacity ◽  
Working Environment ◽  
Energy Consumption Analysis ◽  
Mecanum Wheel ◽  
Save Energy ◽  
Energy Consumption Modeling ◽  
Robot Platform

The four-wheeled Mecanum robot is widely used in various industries due to its maneuverability and strong load capacity, which is suitable for performing precise transportation tasks in a narrow environment. While the Mecanum wheel robot has mobility, it also consumes more energy than ordinary robots. The power consumed by the Mecanum wheel mobile robot varies enormously depending on their operating regimes and environments. Therefore, only knowing the working environment of the robot and the accurate power consumption model can we accurately predict the power consumption of the robot. In order to increase the applicable scenarios of energy consumption modeling for Mecanum wheel robots and improve the accuracy of energy consumption modeling, this paper focuses on various factors that affect the energy consumption of the Mecanum wheel robot, such as motor temperature, terrain, the center of gravity position, etc. The model is derived from the kinematic and kinetic model combined with electrical engineering and energy flow principles. The model has been simulated in MATLAB and experimentally validated with the four-wheeled Mecanum robot platform in our lab. Experimental results show that the accuracy of the model reached 95%. The results of energy consumption modeling can help robots save energy by helping them to perform rational path planning and task planning.

scholarly journals Optimal Surface Aeration Control in Full-Scale Oxidation Ditches through Energy Consumption Analysis

Water ◽  
2018 ◽  
Vol 10 (7) ◽  
pp. 945 ◽  
Author(s):  
Yong Qiu ◽  
Chi Zhang ◽  
Bing Li ◽  
Ji Li ◽  
Xiaoyuan Zhang ◽  
...  
Keyword(s):  
Control System ◽  
Energy Consumption ◽  
Rural Areas ◽  
Energy Model ◽  
Full Scale ◽  
Economic Feasibility ◽  
Model Parameters ◽  
Online Data ◽  
Improve Energy Efficiency ◽  
Aeration Control

Oxidation ditches are popularly used in rural areas and decentralized treatment facilities where energy deficiency is of concern. Aeration control technologies are well established for diffusion systems in order to improve energy efficiency, but there are still challenges in their application in oxidation ditches because surface aerators have unique characteristics with respect to oxygen transfer and energy consumption. In this paper, an integral energy model was proposed to include the energy, aeration, and fluidic effects of surface aerators, by which the energy for aeration of each aerator can be estimated using online data. Two types of rotating disks with different diameters (1800 mm and 1400 mm) were monitored in situ to estimate the model parameters. Furthermore, a feedforward–feedback loop control strategy was proposed using the concept of energy analysis and optimization. The simplified control system was implemented in a full-scale Orbal oxidation ditch, achieving an approximately 10% saving in full-process energy consumption. The cost–benefit analysis and carbon emission assessment confirmed the economic feasibility and environmental contribution of the control system. The energy model can help process designers and operators to better understand and optimally control the aeration process in oxidation ditches.

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