Search Results - "Computing methodologies Artificial intelligence Planning and scheduling"

Analyzing and Improving Fault Tolerance of Learning-Based Navigation Systems by Wan, Zishen, Anwar, Aqeel, Hsiao, Yu-Shun, Jia, Tianyu, Reddi, Vijay Janapa, Raychowdhury, Arijit

“…Learning-based navigation systems are widely used in autonomous applications, such as robotics, unmanned vehicles and drones. Specialized hardware accelerators…”
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Derm: SLA-aware Resource Management for Highly Dynamic Microservices by Chen, Liao, Luo, Shutian, Lin, Chenyu, Mo, Zizhao, Xu, Huanle, Ye, Kejiang, Xu, Chengzhong

“…Ensuring efficient resource allocation while providing service level agreement (SLA) guarantees for end-to-end (E2E) latency is crucial for microservice…”
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FedLight: Federated Reinforcement Learning for Autonomous Multi-Intersection Traffic Signal Control by Ye, Yutong, Zhao, Wupan, Wei, Tongquan, Hu, Shiyan, Chen, Mingsong

“…Although Reinforcement Learning (RL) has been successfully applied in traffic control, it suffers from the problems of high average vehicle travel time and…”
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EffBT: An Efficient Behavior Tree Reactive Synthesis and Execution Framework by Wu, Ziji, Huang, Yu, Huang, Peishan, Wen, Shanghua, Li, Minglong, Wang, Ji

“…Behavior Trees (BTs), originated from the control of Non-Player-Characters (NPCs), have been widely embraced in robotics and software engineering communities…”
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MROS: A framework for robot self-adaptation by Silva, Gustavo Rezende, Garcia, Nadia Hammoudeh, Bozhinoski, Darko, Deshpande, Harshavardhan, Oviedo, Mario Garzon, Wasowski, Andrzej, Montero, Mariano Ramirez, Corbato, Carlos Hernandez

“…Self-adaptation can be used in robotics to increase system robust- ness and reliability. This work describes the Metacontrol method for self-adaptation in…”
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Decictor: Towards Evaluating the Robustness of Decision-Making in Autonomous Driving Systems by Cheng, Mingfei, Xie, Xiaofei, Zhou, Yuan, Wang, Junjie, Meng, Guozhu, Yang, Kairui

“…Autonomous Driving System (ADS) testing is crucial in ADS development, with the current primary focus being on safety. However, the evaluation of…”
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PROMISE: High-Level Mission Specification for Multiple Robots by Garcia, Sergio, Pelliccione, Patrizio, Menghi, Claudio, Berger, Thorsten, Bures, Tomas

“…Service robots, a type of robots that perform useful tasks for humans, are foreseen to be broadly used in the near future in both social and industrial…”
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Cocktail: Learn a Better Neural Network Controller from Multiple Experts via Adaptive Mixing and Robust Distillation by Wang, Yixuan, Huang, Chao, Wang, Zhilu, Xu, Shichao, Wang, Zhaoran, Zhu, Qi

“…Neural networks are being increasingly applied to control and decision making for learning-enabled cyber-physical systems (LE-CPSs). They have shown promising…”
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SEO: Safety-Aware Energy Optimization Framework for Multi-Sensor Neural Controllers at the Edge by Odema, Mohanad, Ferlez, James, Shoukry, Yasser, Al Faruque, Mohammad Abdullah

“…Runtime energy management has become quintessential for multi-sensor autonomous systems at the edge for achieving high performance given the platform…”
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PolyGym: Polyhedral Optimizations as an Environment for Reinforcement Learning by Brauckmann, Alexander, Goens, Andres, Castrillon, Jeronimo

“…The polyhedral model allows a structured way of defining semantics-preserving transformations to improve the performance of a large class of loops. Finding…”
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Construction of DAG Models for Autonomous Systems by Huang, Jing, Jiang, Kuan, Wang, Weijie, Liang, Wei, Chang, Wanli

“…Directed Acyclic Graphs (DAGs) are widely deployed as task models in autonomous systems, including vehicles and drones, to capture functional dependency. DAG…”
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Using physical quantities in robot software models by Burgueño, Loli, Mayerhofer, Tanja, Wimmer, Manuel, Vallecillo, Antonio

“…One of the challenges of modeling any software application that deals with real-world physical systems resides in the correct representation of numerical…”
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Human-Robot Mutual Adaptation in Shared Autonomy by Nikolaidis, Stefanos, Zhu, Yu Xiang, Hsu, David, Srinivasa, Siddhartha

“…Shared autonomy integrates user input with robot autonomy in order to control a robot and help the user to complete a task. Our work aims to improve the…”
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Planning with Trust for Human-Robot Collaboration by Chen, Min, Nikolaidis, Stefanos, Soh, Harold, Hsu, David, Srinivasa, Siddhartha

“…Trust is essential for human-robot collaboration and user adoption of autonomous systems, such as robot assistants. This paper introduces a computational model…”
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Social Momentum: A Framework for Legible Navigation in Dynamic Multi-Agent Environments by Mavrogiannis, Christoforos I., Thomason, Wil B., Knepper, Ross A.

“…Intent-expressive robot motion has been shown to result in increased efficiency and reduced planning efforts for copresent humans. Existing frameworks for…”
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Preference-Conditioned Language-Guided Abstraction by Peng, Andi, Bobu, Andreea, Li, Belinda Z., Sumers, Theodore R., Sucholutsky, Ilia, Kumar, Nishanth, Griffiths, Thomas L., Shah, Julie A.

“…Learning from demonstrations is a common way for users to teach robots, but it is prone to spurious feature correlations. Recent work constructs state…”
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Mimicking Associative Learning of Rats via a Neuromorphic Robot in Open Field Maze Using Spatial Cell Models by Liu, Tianze, Bakr Siddique, Md Abu, An, Hongyu

“…Data-driven Artificial Intelligence (AI) approaches have exhibited remarkable prowess across various cognitive tasks using extensive training data. However,…”
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Effects of Robot Motion on Human-Robot Collaboration by Dragan, Anca D., Bauman, Shira, Forlizzi, Jodi, Srinivasa, Siddhartha S.

“…Most motion in robotics is purelyfifnctional, planned to achieve the goal and avoid collisions. Such motion is great in isolation, but collaboration affords a…”
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Mandala: an agent-based platform to support interoperability in systems-of-systems by Mendes, Altair, Loss, Stefano, Cavalcante, Everton, Lopes, Frederico, Batista, Thais

“…A particular challenge to the construction of systems-of-systems (SoS) is the high heterogeneity of their constituent systems, thereby making interoperability…”
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Do You Want Your Autonomous Car To Drive Like You? by Basu, Chandrayee, Yang, Qian, Hungerman, David, Singhal, Mukesh, Dragan, Anca D.

“…With progress in enabling autonomous cars to drive safely on the road, it is time to start asking how they should be driving. A common answer is that they…”
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