Robotics & Machine Learning Daily News2024,Issue(Jul.2) :126-126.

Studies Conducted at Monash University on Robotics Recently Reported (Should I J ust Stick To the Wall? Evaluating the Social Acceptance and Preferred Driving Si de of Wall Following)

莫纳什大学最近进行的机器人研究报告(我应该坚持墙吗?评价社会接受度和优先驱动标准

Robotics & Machine Learning Daily News2024,Issue(Jul.2) :126-126.

Studies Conducted at Monash University on Robotics Recently Reported (Should I J ust Stick To the Wall? Evaluating the Social Acceptance and Preferred Driving Si de of Wall Following)

莫纳什大学最近进行的机器人研究报告(我应该坚持墙吗?评价社会接受度和优先驱动标准

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摘要

根据来自澳大利亚克莱顿的新闻报道,NewsRx Co Robertors的研究人员称,“需要安全、可预测的、可而可靠的rob ot导航是移动机器人在家庭和办公环境中移动的基础,最短路径导航是一种常用的机器人导航方法,它利用最有效的路径到达目标。这项研究的资助者包括莫纳什大学工程学院电气和计算机系统工程学院。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in Robotic s. According to news reporting originating from Clayton, Australia, by NewsRx co rrespondents, research stated, “The need for safe, predictable, and reliable rob ot navigation is fundamental for mobile robots to move around in home and office environments. Shortest-path navigation is a popular robot navigation method tha t uses the most efficient path to get to the desired goal.” Funders for this research include Monash University, Faculty of Engineering, Sch ool of Electrical and Computer Systems Engineering.

Key words

Clayton/Australia/Australia and New Ze aland/Emerging Technologies/Machine Learning/Robot/Robotics/Monash Universi ty

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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