2023
DOI: 10.1017/s0263574723000577
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State of the art and future trends in obstacle-surmounting unmanned ground vehicle configuration and dynamics

Abstract: This article presents a review of the platform configuration and dynamic of obstacle-surmounting unmanned ground vehicles (UGVs). For now, unmanned systems have emerged as a result of the rapid advancement of artificial intelligence and modern manufacturing techniques both domestically and internationally. The research on unmanned systems has been improved a lot. The UGV platform can execute transportation, recurring, and military tasks independently. For the high-level self-control, adaption, and maneuverabil… Show more

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Cited by 6 publications
(6 citation statements)
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“…Conversely, the Agema models from the UAE excel in speed and agility [13]. the current literature [21][22][23][24][25], reveal a variety of UGVs that led to classification [25] based on three categories: size, mode of operation, and type of weapon. Each category contemplates four classes.…”
Section: Related Workmentioning
confidence: 99%
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“…Conversely, the Agema models from the UAE excel in speed and agility [13]. the current literature [21][22][23][24][25], reveal a variety of UGVs that led to classification [25] based on three categories: size, mode of operation, and type of weapon. Each category contemplates four classes.…”
Section: Related Workmentioning
confidence: 99%
“…The development of the conceptual A-UGV proposed in this work is motivated by the DEM 2018 REV 2021 [30], in which this work encompasses several lines of action of Some relevant state-of-the-art reviews in the civil and military sectors, available in the current literature [21][22][23][24][25], reveal a variety of UGVs that led to classification [25] based on three categories: size, mode of operation, and type of weapon. Each category contemplates four classes.…”
Section: Motivation and Main Objectivementioning
confidence: 99%
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“…In the last decade, the exponential growth of artificial intelligence, machine learning and other deep learning algorithms [12] have contributed for the development of many advanced UGVs with improved capabilities, e.g., sensing and control. Some relevant state of the art reviews in the civil and military sectors are available in the current literature [13][14][15][16][17].…”
Section: Introductionmentioning
confidence: 99%
“…Since UGV usually performs tasks in various terrain environments, all-terrain motion adaptability has become an indicator of a UGV's efficiency and reliability. For example, He et al (10) investigated the related dynamic characteristics of an obstacle-crossing UGV. Zhang et al (11) designed a bidirectional six-wheel planetary rover for road conditions on rugged planetary surfaces.…”
Section: Introductionmentioning
confidence: 99%