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pro vyhledávání: '"Tahir, Nazish"'
Offloading time-sensitive, computationally intensive tasks-such as advanced learning algorithms for autonomous driving-from vehicles to nearby edge servers, vehicle-to-infrastructure (V2I) systems, or other collaborating vehicles via vehicle-to-vehic
Externí odkaz:
http://arxiv.org/abs/2408.03435
Autor:
Tahir, Nazish, Parasuraman, Ramviyas
We propose integrating the edge-computing paradigm into the multi-robot collaborative scheduling to maximize resource utilization for complex collaborative tasks, which many robots must perform together. Examples include collaborative map-merging to
Externí odkaz:
http://arxiv.org/abs/2311.10194
Autor:
Tahir, Nazish, Parasuraman, Ramviyas
To circumvent persistent connectivity to the cloud infrastructure, the current emphasis on computing at network edge devices in the multi-robot domain is a promising enabler for delay-sensitive jobs, yet its adoption is rife with challenges. This pap
Externí odkaz:
http://arxiv.org/abs/2311.10196
Autor:
Tahir, Nazish, Parasuraman, Ramviyas
When a mobile robot lacks high onboard computing or networking capabilities, it can rely on remote computing architecture for its control and autonomy. This paper introduces a novel collaborative Simulation Twin (ST) strategy for control and autonomy
Externí odkaz:
http://arxiv.org/abs/2303.06172
Autor:
Tahir, Nazish, Parasuraman, Ramviyas
Resource-constrained mobile robots that lack the capability to be completely autonomous can rely on a human or AI supervisor acting at a remote site (e.g., control station or cloud) for their control. Such a supervised autonomy or cloud-based control
Externí odkaz:
http://arxiv.org/abs/2210.16703
Akademický článek
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Autor:
Tahir, Nazish1 nazish.tahir@uga.edu, Parasuraman, Ramviyas1 ramviyas@uga.edu
Publikováno v:
IEEE Transactions on Systems, Man & Cybernetics. Systems. May2023, Vol. 35 Issue Part1, p2616-2628. 13p.
