Navigation of outdoor mobile robots using dead reckoning and visually detected landmarks

Mäkelä, Hannu; Koskinen, Kari

doi:10.1109/icar.1991.240417

Cited by 19 publications

(6 citation statements)

References 4 publications

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“…and calculating the data for the current position of the shovel [71]. This method has good accuracy and low cost for short-term positioning, but has accumulated errors for long-term positioning estimation, which need to be corrected by correction techniques [68,72].…”

Section: Positioning Technologymentioning

confidence: 99%

Research Status and Development Trend of Underground Intelligent Load-Haul-Dump Vehicle—A Comprehensive Review

2022

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The underground intelligent load-haul-dump vehicle (LHD) is a product of the deep integration of traditional LHD with information network technology, automatic controlling and artificial intelligence technology. It gathers the functions of environmental perception, autonomous driving and fault diagnosis in one machine and exhibits higher safety and greater efficiency than traditional LHD. Hence, it is a particularly important piece of underground mining equipment for building green, safe and smart mines. Taking the studies about intelligent LHD collected by CNKI and WOS databases from 1980 to 2022 as a sample data source, employing Citespace visual analysis software for key feature extraction from the documents, statistical analysis was conducted to clarify the current research progress and the frontier topics of the intelligent LHD academia in the past 40 years, in relation to the future development trends. The development history and application status of underground intelligent LHD was expounded in this article, summarizing the research status at home and abroad from four aspects: ore heap perception and modeling technology, trajectory planning method of bucket shoveling, autonomous navigation technology, real-time monitoring and intelligent fault diagnosis technology. The demerits and merits of the technologies were reviewed as well, with future developing and researching trends of the underground intelligent LHD concluded.

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Section: Positioning Technologymentioning

confidence: 99%

Research Status and Development Trend of Underground Intelligent Load-Haul-Dump Vehicle—A Comprehensive Review

2022

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“…This deadreckoning error accumulates because of the discrepancy between measured shaft encoder changes and the actual wheel movements which cannot be directly measured. Various schemes have been reported to correct for this effect [1,2,3,4] and this paper describes a technique developed at Newcastle based on a recently developed 3D scene analyser [5]. The incorporation of a robot manipulator is natural in mobile robots applied to advanced robotics applications e.g.…”

Section: Introductionmentioning

confidence: 99%

<title>Matching 3D segmented objects using wire frame analysis</title>

Allen

O’Brien

1993

SPIE Proceedings

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This paper describes a novel technique in 3D sensory fusion for autonomous mobile vehicles. The primary sensor is a monocular camera mounted on a robot manipulator which pans to up to three positions on a 0.5 m vertical circle, whilst mounted on the mobile vehicle. The passive scene is analysed using a method of inverse perspective, which is described and the resulting scene analysis comprises 3D wire frames of all surfaces detected in 3D. The 3D scene analysis uses a dual T-800 transputer based multiprocessor which cycles through generating primary scene information at rates of 1 update per 10 seconds. A PC-based 3D matching algorithm is then used to match the segmented objects to a database of pre-taught 3D wire frames. The matching software is written in Prolog.

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“…In order to improve the accuracy of localization, many approaches combine external sensors; such as cameras, beacon, laser range finders, sonar, GPS etc. Makela et al [3] studied the integration of dead reckoning and visual landmark recognition methods for the navigation of outdoor mobile robots. Stella et al [4] proposed a cooperation strategy between odometry and visual self-location method.…”

Section: Introductionmentioning

confidence: 99%

Indoor localization for autonomous mobile robot based on passive RFID

Park

Hashimoto

2009

2008 IEEE International Conference on Robotics and Biomimetics

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-In this paper, we propose a novel method using read-time of IC tags to reduce the localization error of an RFID navigation system. In order to reduce localization error, many approaches have been introduced. However, they do not deal with the problems that arise when the antenna can read at most one tag at any given moment. Using this, our passive RFID system is able to estimate the robot's location and orientation more accurately without the use of external sensors or a vision system. The experimental results show that the proposed method effectively estimates both the location and the pose of a mobile robot during navigation. We present results of trajectories of the robot in navigation and compare them with a generally utilized RFID algorithm.

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Navigation of outdoor mobile robots using dead reckoning and visually detected landmarks

Cited by 19 publications

References 4 publications

Research Status and Development Trend of Underground Intelligent Load-Haul-Dump Vehicle—A Comprehensive Review

Research Status and Development Trend of Underground Intelligent Load-Haul-Dump Vehicle—A Comprehensive Review

<title>Matching 3D segmented objects using wire frame analysis</title>

Indoor localization for autonomous mobile robot based on passive RFID

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