Multi-agent deep reinforcement learning for multi-robot applications: A survey
J Orr, A Dutta - Sensors, 2023 - mdpi.com
Deep reinforcement learning has produced many success stories in recent years. Some
example fields in which these successes have taken place include mathematics, games …
example fields in which these successes have taken place include mathematics, games …
Real-time outage management in active distribution networks using reinforcement learning over graphs
Self-healing smart grids are characterized by fast-acting, intelligent control mechanisms that
minimize power disruptions during outages. The corrective actions adopted during outages …
minimize power disruptions during outages. The corrective actions adopted during outages …
A Systematic Literature Review on Multi-Robot Task Allocation
A KA, U Subramaniam - ACM Computing Surveys, 2024 - dl.acm.org
Muti-Robot system is gaining attention and is one of the critical areas of research when it
comes to robotics. Coordination among multiple robots and how different tasks are allocated …
comes to robotics. Coordination among multiple robots and how different tasks are allocated …
Efficient planning of multi-robot collective transport using graph reinforcement learning with higher order topological abstraction
Efficient multi-robot task allocation (MRTA) is fundamental to various time-sensitive
applications such as disaster response, warehouse operations, and construction. This paper …
applications such as disaster response, warehouse operations, and construction. This paper …
Fast Decision Support for Air Traffic Management at Urban Air Mobility Vertiports using Graph Learning
Urban Air Mobility (UAM) promises a new dimension to decongested, safe, and fast travel in
urban and suburban hubs. These UAM aircraft are conceived to operate from small airports …
urban and suburban hubs. These UAM aircraft are conceived to operate from small airports …
Multi-robot planning on dynamic topological graphs using mixed-integer programming
Planning for multi-robot teams in complex environments is a challenging problem, especially
when these teams must coordinate to accomplish a common objective. In general, optimal …
when these teams must coordinate to accomplish a common objective. In general, optimal …
[PDF][PDF] 机器人感知与控制关键技术及其智能制造应用
王耀南， 江一鸣， 姜娇， 张辉， 谭浩然， 彭伟星… - 自动化学报, 2023 - source.kongzhi.net
智能机器人在服务国家重大需求, 引领国民经济发展和保障国防安全中起到重要作用,
被誉为“制造业皇冠顶端的明珠”. 随着新一轮工业革命的到来, 世界主要工业国家都开始加快 …
被誉为“制造业皇冠顶端的明珠”. 随着新一轮工业革命的到来, 世界主要工业国家都开始加快 …
Learning to Allocate Time-Bound and Dynamic Tasks to Multiple Robots Using Covariant Attention Neural Networks
S Paul, S Chowdhury - Journal of Computing and …, 2024 - asmedigitalcollection.asme.org
In various applications of multi-robotics in disaster response, warehouse management, and
manufacturing, tasks that are known a priori and tasks added during run time need to be …
manufacturing, tasks that are known a priori and tasks added during run time need to be …
[PDF][PDF] A Systematic Literature Review on Multi-Robot Task Allocation
KA Athira, U SUBRAMANIAM - ACM Computing Surveys, 2024 - researchgate.net
Autonomous robots that are capable of perceiving their surroundings, making decisions
based on their observations or previous learning, and subsequently performing actions or …
based on their observations or previous learning, and subsequently performing actions or …
Graph learning based decision support for multi-aircraft take-off and landing at urban air mobility vertiports
View Video Presentation: https://doi. org/10.2514/6.2023-1848. vid As city populations
continue to rise, urban air mobility (UAM) seeks to provide much needed relief from traffic …
continue to rise, urban air mobility (UAM) seeks to provide much needed relief from traffic …