Energy estimation for differential drive mobile robots on straight and rotational trajectories

Jaramillo-Morales, Mauricio F.; Dogru, Sedat; Gómez-Mendoza, Juan Bernardo; Marques, Lino

doi:10.1177/1729881420909654

Cited by 23 publications

(12 citation statements)

References 20 publications

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“…θ = [ θ 1 θ 2 ] = are the angular positions of the wheels: In another study, they proposed a power model for a two-wheel differential drive mobile robot with prediction accuracies of 96.67% for linear trajectories and 81.25% for curved trajectories, making it an excellent hybrid model (Jaramillo-Morales et al , 2020).…”

Section: Energy Consumption For Autonomous Mobile Robotsmentioning

confidence: 99%

A review on energy efficiency in autonomous mobile robots

Wu,

Yeong,

et al. 2023

RIA

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Purpose This paper aims to provide a comprehensive analysis of the state of the art in energy efficiency for autonomous mobile robots (AMRs), focusing on energy sources, consumption models, energy-efficient locomotion, hardware energy consumption, optimization in path planning and scheduling methods, and to suggest future research directions. Design/methodology/approach The systematic literature review (SLR) identified 244 papers for analysis. Research articles published from 2010 onwards were searched in databases including Google Scholar, ScienceDirect and Scopus using keywords and search criteria related to energy and power management in various robotic systems. Findings The review highlights the following key findings: batteries are the primary energy source for AMRs, with advances in battery management systems enhancing efficiency; hybrid models offer superior accuracy and robustness; locomotion contributes over 50% of a mobile robot’s total energy consumption, emphasizing the need for optimized control methods; factors such as the center of mass impact AMR energy consumption; path planning algorithms and scheduling methods are essential for energy optimization, with algorithm choice depending on specific requirements and constraints. Research limitations/implications The review concentrates on wheeled robots, excluding walking ones. Future work should improve consumption models, explore optimization methods, examine artificial intelligence/machine learning roles and assess energy efficiency trade-offs. Originality/value This paper provides a comprehensive analysis of energy efficiency in AMRs, highlighting the key findings from the SLR and suggests future research directions for further advancements in this field.

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Section: Energy Consumption For Autonomous Mobile Robotsmentioning

confidence: 99%

A review on energy efficiency in autonomous mobile robots

Wu,

Yeong,

et al. 2023

RIA

View full text Add to dashboard Cite

show abstract

“…When a mobile node is about to return to its initial position, the sink node is informed in order to change its availability ( f lag m i ), its position, and, if necessary, remove it from the idle list (see Algorithm 6, lines [22][23][24][25][26][27]. When a mobile node is not needed and becomes idle at its current position, the sink node is informed and changes the status of the mobile node, and it is added to the idle list (see Algorithm 6, lines [28][29][30].…”

Section: Sink Nodementioning

confidence: 99%

“…We present two works that focus on different mobile robots, namely the P3-DX robot [28] and the Nomad Super Scout robot [29], respectively; these are popular mobile robots in the research community of energy consumption models. P3-DX is a mobile robot with two wheels driven by two DC motors and powered by a rechargeable battery.…”

Section: Moving Energy Modelmentioning

confidence: 99%

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A Node Placement Algorithm Utilizing Mobile Nodes in WSN and IoT Networks

Temene

Sergiou

Ioannou

et al. 2022

Telecom

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The operation of the Internet of Things (IoT) networks and Wireless Sensor Networks (WSN) is often disrupted by a number of problems, such as path disconnections, network segmentation, node faults, and security attacks. A method that gains momentum in resolving some of those issues is the use of mobile nodes or nodes deployed by mobile robots. The use of mobile elements essentially increases the resources and the capacity of the network. In this work, we present a Node Placement Algorithm with two variations, which utilizes mobile nodes for the creation of alternative paths from source to sink. The first variation employs mobile nodes that create locally-significant alternative paths leading to the sink. The second variation employs mobile nodes that create completely individual (disjoint) paths to the sink. We then extend the local variation of the algorithm by also accounting for the energy levels of the nodes as a contributing factor regarding the creation of alternative paths. We offer both a high-level description of the concept and also detailed algorithmic solutions. The evaluation of the solutions was performed in a case study of resolving congestion in the network. Results have shown that the proposed algorithms can significantly contribute to the alleviation of the problem of congestion in IoT and WSNs and can easily be used for other types of network problems.

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“…In this realm, a major body of research has dealt with power issue of wheeled mobile robots. Many researches in this area have concentrated their efforts on ascertainment of effect of straight and rotational transport trajectories of the robot on its power consumption (Effati et al, 2020; Jaramillo‐Morales et al, 2020; Kaplan et al, 2017; Kim & Kim, 2014a, 2014b, 2017, 2021). Overall outcome of the researches indicates that power provided for the robot is devoted for five systems (sensors, actuators, communication, control, and motion) (Kagan et al, 2020; Sadrpour et al, 2013; Stefek et al, 2020; Xie et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Characterization of motion power loss of off‐road wheeled robot in a slippery terrain

Shafaei

Mousazadeh

2022

Journal of Field Robotics

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For the first time in realm of power study of off‐road wheeled robots, this study deals with motion power loss due to slippage of robot wheels traversed on slippery terrain. For this purpose, effects of slippery terrain type (solid balls with diameter of 0.0127, 0.0254, and 0.0508 m), tire air pressure (20.68, 34.47, and 55.16 kPa), and robot forward speed (0.17, 0.33, and 0.5 m/s) on the power loss were characterized. Derived results proved that the increasing effect of slippery terrain type on the power loss was dominant (1.08 and 3.21 times) than that of robot forward speed and tire air pressure, respectively. Meanwhile, the increasing effect of robot forward speed on the power loss was prevailed (2.98 times) than that of tire air pressure. Hence, to minimize the power loss of the robot traversed on each type of slippery terrain, adjustment of robot forward speed should be considered as first priority. A comparison between motion power loss (43.60–249.40 W) and provided motion power for the robot (136–436.37 W) implies that 12.93–75.44% of provided motion power was wasted by slippage of the robot wheels on slippery terrains. Overall, the analytical results obtained in this study lead to open a new prospection for comprehending of the power loss trends of off‐road wheeled robots traversed on slippery terrains. As slippery terrain composed of solid balls, the results can be especially utilized for final phase of unloading robotic operations of catalyst handling procedure in process towers and reactors of oil, gas, petrochemical, and chemical industries.

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Energy estimation for differential drive mobile robots on straight and rotational trajectories

Cited by 23 publications

References 20 publications

A review on energy efficiency in autonomous mobile robots

A review on energy efficiency in autonomous mobile robots

A Node Placement Algorithm Utilizing Mobile Nodes in WSN and IoT Networks

Characterization of motion power loss of off‐road wheeled robot in a slippery terrain

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