Autonomous armoured logistics carrier for natural environments

Ibañez‐Guzmán, Javier; Jian, Xu; Malcolm, Andrew Alexander; Gong, Zhiming; Chan, C.W.; Tay, A.L.P.

doi:10.1109/iros.2004.1389397

Cited by 5 publications

(6 citation statements)

References 6 publications

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“…It is also named as autopilot or automated guided vehicle (AGV) [3]. The autonomous vehicle consists of Visual Guidance System (VGS), Vehicle Control System (VCS), Vehicle Piloting System (VPS) and Robust Communications System (RCS) [4]. Studies suggest that advantages of Autonomous Transport Systems include increase in road and parking capacity, improved safety, efficient traffic flow, and decrease in traffic congestion and fuel economy.…”

Section: Background Literaturementioning

confidence: 99%

Autonomous Vehicles in Developing Countries: A Case Study on User’s View Point in Pakistan

Sanaullah

Hussain

Chaudhry

et al. 2016

Advances in Intelligent Systems and Computing

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Section: Background Literaturementioning

confidence: 99%

Autonomous Vehicles in Developing Countries: A Case Study on User’s View Point in Pakistan

Sanaullah

Hussain

Chaudhry

et al. 2016

Advances in Intelligent Systems and Computing

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“…In such cases, advanced sensors such as stereo cameras, Laser RADAR (LADAR), and appropriate sensor fusion techniques are necessary to deal with the complex environment (Stephens et al 1989;Matthies et al 1998;Ibanez-Guzman et al 2004). Due to the inherent difficulties in understanding natural objects and changing environments, autonomous driving is still in its infancy.…”

Section: Related Workmentioning

confidence: 99%

Vision-based motion planning for an autonomous motorcycle on ill-structured roads

Song

Lee

et al. 2007

Auton Robot

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We report our development of a vision-based motion planning system for an autonomous motorcycle designed for desert terrain, where uniform road surface and lane markings are not present. The motion planning is based on a vision vector space (V 2 -Space), which is a unitary vector set that represents local collision-free directions in the image coordinate system. The V 2 -Space is constructed by extracting the vectors based on the similarity of adjacent pixels, which captures both the color information and the directional information from prior vehicle tire tracks and pedestrian footsteps. We report how the V 2 -Space is constructed to reduce the impact of varying lighting conditions in outdoor environments. We also show how the V 2 -Space can be used to incorporate vehicle kinematic, dynamic, and time-delay constraints in motion planning to fit the highly dynamic requirements of the motorcycle. The combined algorithm of the V 2 -Space construction and the motion planning runs in O(n) time, where n is the number of pixels in the captured image. Experiments show that our algorithm outputs correct robot motion commands more than 90% of the time.

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“…In such cases, advanced sensors such as stereo cameras, Laser RADAR (LADAR), and appropriate sensor fusion techniques are necessary to deal with the complex environment [11]- [13]. Due to the inherent difficulties in understanding natural objects and changing environments, autonomous driving is still in its infancy.…”

Section: Related Workmentioning

confidence: 99%

Vision-based Motion Planning for an Autonomous Motorcycle on Ill-Structured Road

Song

Lee

et al. 2006

2006 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-We report our development of a vision-based motion planning system for an autonomous motorcycle designed for desert terrain, where uniform road surface and lane markings are not present. The motion planning is based on a vision vector space (V 2 -Space), which is an unitary vector set that represents local collision-free directions in the image coordinate system. V 2 -Space is constructed by extracting the vectors based on the similarity of adjacent pixels, which captures both the color information and the directional information from prior vehicle tire tracks and pedestrian footsteps. We report how V 2 -Space is constructed to reduce the impact of varying lighting conditions in outdoor environments. We also show how V 2 -Space can be used to incorporate vehicle kinematic, dynamic, and timedelay constraints in motion planning to fit the highly dynamic requirements of the motorcycle. The combined algorithm of the V 2 -Space construction and the motion planning runs in O(n) time, where n is the number of pixels in the captured image. Experiments show that our algorithm outputs correct robot motion commands more than 90% of the time.

show abstract

Autonomous armoured logistics carrier for natural environments

Cited by 5 publications

References 6 publications

Autonomous Vehicles in Developing Countries: A Case Study on User’s View Point in Pakistan

Autonomous Vehicles in Developing Countries: A Case Study on User’s View Point in Pakistan

Vision-based motion planning for an autonomous motorcycle on ill-structured roads

Vision-based Motion Planning for an Autonomous Motorcycle on Ill-Structured Road

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