Probabilistic Meta-Conv1D Driving Energy Prediction for Mobile Robots in Unstructured Terrains-Reference-Cited by-同舟云学术

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Probabilistic Meta-Conv1D Driving Energy Prediction for Mobile Robots in Unstructured Terrains

Published:2022 Issue: Volume:10 Page:107913-107928
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Visca Marco¹^ORCID,Powell Roger²^ORCID,Gao Yang³^ORCID,Fallah Saber¹^ORCID

Affiliation:

1. Connected and Autonomous Vehicles Laboratory (CAV Laboratory), University of Surrey, Guildford, U.K.

2. Cybernetics Group, Remote Applications in Challenging Environments, U.K. Atomic Energy Authority, Culham Science Centre, Abingdon, U.K.

3. Space Technology for Autonomous and Robotic Laboratory (STAR Laboratory), University of Surrey, Guildford, U.K.

Funder

European Consortium for the Development of Fusion Energy (EUROfusion), funded by the European Union via the Euratom Research and Training Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09902974.pdf?arnumber=9902974

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Modeling analysis and experiment for energy system of ocean energy driven unmanned marine vehicle: The Yulang II case study;Journal of Field Robotics;2024-01-22

2. A Survey on Path Planning for Autonomous Ground Vehicles in Unstructured Environments;Machines;2024-01-02

3. A review on energy efficiency in autonomous mobile robots;Robotic Intelligence and Automation;2023-09-18

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