Towards a Multi-mission QoS and Energy Manager for Autonomous Mobile Robots

Ho, Dinh-Khanh; Chehida, Karim Ben; Miramond, Benoît; Auguin, Michel

doi:10.1109/irc.2018.00057

Cited by 9 publications

(5 citation statements)

References 6 publications

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“…En particular, las métricas para evaluar las funcionalidades de los robots móviles se han basado en la precisión, la funcionalidad y el consumo de recursos (Singh Gill et al, 2019). Aplicar un buen conjunto de criterios de desempeño permite: optimizar parámetros de los algoritmos, probar el desempeño de la navegación para diferentes entornos, optimizar la planificación de movimientos, comparar cuantitativamente diferentes algoritmos de control, apoyar el desarrollo de los algoritmos y ayudar a decidir sobre los ajustes necesarios entre diversos aspectos del funcionamiento del sistema (Ho et al, 2018).…”

Section: Introductionunclassified

Criterios de desempeño para evaluar algoritmos de navegación de robots móviles: una revisión

Ceballos

Suarez-Rivera

2022

Rev. iberoam. autom. inform. ind.

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En este artículo se presenta una revisión de literatura sobre criterios de desempeño para evaluar la navegación de un robot móvil, los cuales ayudan a comparar cuantitativamente diferentes características, como: el sistema de control, la navegación en diferentes entornos de trabajo, el desempeño energético, etc. El interés en criterios de desempeño y procedimiento de comparación (benchmarks) ha crecido en los últimos años, principalmente por investigadores y fabricantes de robots que buscan satisfacer la creciente demanda de aplicaciones en el mercado global, cada vez más competido. El conjunto de criterios está compuesto por métricas, índices, mediciones y benchmarks, desde el más básico como contabilizar el éxito en alcanzar la meta, pasando por otros más elaborados como los de seguridad en la trayectoria generada en la evasión de obstáculos, hasta criterios que comparan aspectos más complejos de la navegación como el consumo energético. Finalmente, se describen algunos benchmarks y software para simulación y comparación de algoritmos de navegación. Estos criterios se constituyen en una importante herramienta para diseñadores e investigadores en robótica móvil.

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Section: Introductionunclassified

Criterios de desempeño para evaluar algoritmos de navegación de robots móviles: una revisión

Ceballos

Suarez-Rivera

2022

Rev. iberoam. autom. inform. ind.

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“…To guarantee energy awareness, our approach uses optimal control and heuristics where both the paths and schedules variations are trajectories, varying between given bounds (i.e., physical constraints of the robot and computing hardware, quality of service, desired quality of the coverage, etc.). Past planning-scheduling studies also employ optimization techniques [11], [12], [17], [21]; some use a greedy approach [7], [18], [22]; whereas others use reinforcement learning-based approaches [10], [27]. Hybrid approaches [17] are also available, where the techniques are mixed.…”

Section: Introductionmentioning

confidence: 99%

Energy-Aware Planning-Scheduling for Autonomous Aerial Robots

Seewald¹,

Marina²,

Midtiby³

et al. 2022

Preprint

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In this paper, we present an online planningscheduling approach for battery-powered autonomous aerial robots. The approach consists of simultaneously planning a coverage path and scheduling onboard computational tasks. We further derive a novel variable coverage motion robust to airborne constraints and an empirically motivated energy model. The model includes the energy contribution of the schedule based on an automatic computational energy modeling tool. Our experiments show how an initial flight plan is adjusted online as a function of the available battery, accounting for uncertainty. Our approach remedies possible in-flight failure in case of unexpected battery drops, e.g., due to adverse atmospheric conditions, and increases the overall fault tolerance.

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“…However, compared with the traditional cloud computing model, due to the many new key technologies and usage methods brought about by fog computing, there may be concurrent failure of multimedia services [5] and other complex and difficult to grasp, such as fog node location information leakage [6], interruption of multimedia transmission network, heterogeneous network Cooperative errors will affect the efficiency of the whole system. In recent years, academia and industry have proposed mechanisms or methods to enhance the performance of multimedia service systems in different scenarios [7][8][9][10][11][12][13][14][15][16][17][18][19]. However, how to properly combine fog computing and multimedia services to meet the needs of large-scale concurrent multimedia applications requires more reliable, feasible system models and in-depth computing support algorithms.…”

Section: Introductionmentioning

confidence: 99%

“…About multimedia applications, computing and communication, article [7] researched the hierarchical parallelization of Multi-coloring algorithms for the most useful preconditioners for the conjugate gradient method, namely Block IC Preconditioners. In article [8], a Multi-mission QoS and Energy Manager was indicated for satisfying the increasing demand on the autonomy of mobile robotic platforms requires adaptive on-line decisions for Autonomous Mobile Robots. In [9], to solve the imbalance between power efficiency and performance, the authors studied the reconfigurable architecture by designing an acceleration architecture namely deep neural architecture for Neural Approximation in Multimedia Computing.…”

Section: Introductionmentioning

confidence: 99%

Fog computing support scheme based on fusion of location service and privacy preservation for QoS enhancement

Chen

Wang

Gong

2019

Peer-to-Peer Netw. Appl.

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In the case of large-scale concurrent multimedia services, the resource utilization, QoS guarantee ability and system execution efficiency of distributed multimedia systems are facing many challenges. In order to further solve the above problems, this paper introduces fog computing into distributed multimedia systems and large-scale concurrent multimedia services, and considers the privacy protection of location services. Firstly, in order to solve the limitations of computing, storage, energy continuity, network access and other aspects of the fog node mobile devices, the framework of the fog computing multimedia information service system is constructed to obtain accurate location service data of the mobile terminal. At the same time, collaborative control of fog nodes, fog computing support nodes, public networks and other devices, to achieve the various functions of multimedia services. Secondly, to further improve the efficiency and security of fog computing, this section studies the time slice, bandwidth, hardware and other network resource allocation and management algorithms. Finally, the superiority and feasibility of the proposed algorithm in enhancing QoS performance are validated from different aspects of mathematical analysis and simulation experiments. For example, the resource utilization of multimedia system is increased by 1.34 times, and the load balancing capability and real-time guarantee are improved.

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Towards a Multi-mission QoS and Energy Manager for Autonomous Mobile Robots

Cited by 9 publications

References 6 publications

Criterios de desempeño para evaluar algoritmos de navegación de robots móviles: una revisión

Criterios de desempeño para evaluar algoritmos de navegación de robots móviles: una revisión

Energy-Aware Planning-Scheduling for Autonomous Aerial Robots

Fog computing support scheme based on fusion of location service and privacy preservation for QoS enhancement

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