Reachability Verification Based Reliability Assessment for Deep Reinforcement Learning Controlled Robotics and Autonomous Systems

Dong, Yi; Zhao, Xingyu; Wang, Sen; Huang, Xiaowei

doi:10.1109/lra.2024.3364471

IEEE Robot. Autom. Lett.

2024

DOI: 10.1109/lra.2024.3364471

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Reachability Verification Based Reliability Assessment for Deep Reinforcement Learning Controlled Robotics and Autonomous Systems

Yi Dong,

Xingyu Zhao,

Sen Wang

et al.

Abstract: How to cite:Please refer to published version for the most recent bibliographic citation information. If a published version is known of, the repository item page linked to above, will contain details on accessing it.

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Cited by 5 publications

References 26 publications

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Impulsive maneuver strategy for multi-agent orbital pursuit-evasion game under sparse rewards

Wang,

Zhang

2024

Aerospace Science and Technology

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Impulsive maneuver strategy for multi-agent orbital pursuit-evasion game under sparse rewards

Wang,

Zhang

2024

Aerospace Science and Technology

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Assessing Reliability and Economic Viability of Different EV Charging Station Configurations

Kumar,

Kumar

2024

Qeios

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With the increasing popularity of electric vehicles (EVs) as a mode of transportation, companies are prioritizing the development of charging infrastructure to cater to customer needs. Despite efforts to align charging station designs with distribution system requirements, maintaining reliability for EV charging ports remains challenging. To enhance reliability, a novel 56-ported design incorporating both uniform and non-uniform port arrangements has been proposed. These configurations have been tested with distribution systems ranging from 50 to 500 kW. Reliability assessments were conducted using standards outlined failure rate estimation and monte-carlo functions for evaluating port probability functions in terms of failure rate and reliability. By analyzing the failure rates of individual ports, an evaluation process was introduced to determine the overall success rate of the charging station. The failure rate of the proposed 56-ported charging station was further evaluated using the binomial distribution method. Additionally, cost estimation procedures were implemented considering the failure and success rates of individual port maintenance for the proposed configuration. The findings indicate that achieving lower failure rates and maintenance costs is possible through improved port arrangement reliability and enhanced voltage stability.

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Evaluation of Reliability and Financial Feasibility of Various EV Charging Station Layouts

Kumar,

Kumar

2024

Qeios

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As the popularity of electric vehicles (EVs) continues to rise, companies are increasingly focusing on expanding charging infrastructure to meet growing consumer demand. Despite attempts to design charging stations that align with distribution system requirements, ensuring reliable performance for EV charging ports remains a complex challenge. To address this issue, a unique design featuring 56 ports, comprising both uniform and non-uniform arrangements, has been introduced. These configurations underwent testing across distribution systems ranging from 50 to 500 kW. Reliability assessments were carried out using established standards for failure rate estimation and Monte Carlo simulations to evaluate port probability functions in terms of failure rate and reliability. By scrutinizing the failure rates of individual ports, a systematic evaluation method was established to gauge the overall performance of the charging station. The failure rate of the proposed 56-ported charging station was further assessed using the binomial distribution method. Also, cost estimation procedures were developed, taking into account the maintenance costs associated with the failure and success rates of individual ports for the proposed design. The research findings suggest that by enhancing port arrangement reliability and improving voltage stability, it is possible to achieve lower failure rates and maintenance costs, thereby enhancing overall system performance

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Reachability Verification Based Reliability Assessment for Deep Reinforcement Learning Controlled Robotics and Autonomous Systems

Abstract: How to cite:Please refer to published version for the most recent bibliographic citation information. If a published version is known of, the repository item page linked to above, will contain details on accessing it.

Cited by 5 publications

References 26 publications

Impulsive maneuver strategy for multi-agent orbital pursuit-evasion game under sparse rewards

Impulsive maneuver strategy for multi-agent orbital pursuit-evasion game under sparse rewards

Assessing Reliability and Economic Viability of Different EV Charging Station Configurations

Evaluation of Reliability and Financial Feasibility of Various EV Charging Station Layouts

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