People Tracking Using a Robot in Motion with Laser Range Finder

Lee, Jae Hoon; Tsubouchi, Takashi; Yamamoto, Keijirou; Egawa, Saku

doi:10.1109/iros.2006.282147

Cited by 74 publications

(42 citation statements)

References 9 publications

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“…After a brief review, the aim is to develop a intelligent moving machine provided with simple and robust relative location technologies that do not require structuring the environment. They may have simple semi-reactive strategies that do not require the use of internal maps and the ability to find the smooth path [15]. This approach in based on a control system able to display and integrate an exploration, obstacle avoidance, target following behaviour and a relative location device based on an single emitter and a directional sensor system.…”

Section: Distributed Sensor Network Approachmentioning

confidence: 99%

An Overview of Intelligent Moving Machines (IMM)

Chaturvedi¹,

Yadav²

2015

IJCA

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The intelligent moving machine is design for fast response, cost effective and obstacle avoiding in its path. The introduction of intelligent behavior of moving machine can adapt the change taken place in the environment and or operating conditions etc. This adaptive behavior of moving machine makes it more robust and useful for industrial applications. The paper deals with an overview of Intelligent Moving Machine (IMM) based on two broad category. Firstly, overview based on applications of intelligent moving machine and secondly, technique based intelligent moving machine.

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Section: Distributed Sensor Network Approachmentioning

confidence: 99%

An Overview of Intelligent Moving Machines (IMM)

Chaturvedi¹,

Yadav²

2015

IJCA

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“…Such a filter requires to specify a model of motion. Several models of the human walk have been described and used in the literature in order to analyze RLS data [2,8,10,12,21,23,25,37,38,41]. The role of such a model is to help filtering out the component of the signal which does not correspond to the movement predicted by the model.…”

Section: Weaknesses Of Classical Approachesmentioning

confidence: 99%

Design of a reliable processing pipeline for the non-intrusive measurement of feet trajectories with lasers

Pierard

Azrour

Droogenbroeck

2014

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Reliable measurements of feet trajectories are needed in some applications, such as biomedical applications. This paper describes the data processing pipeline used in GAIMS, which is a non-intrusive system that measures feet trajectories based on multiple range laser scanners. Our processing pipeline relies on a new tracking paradigm, and it is based on two innovative algorithms: the first algorithm localizes the feet directly from the observed point cloud without any clustering, and the other algorithm identifies the feet. After reviewing the various types of noise affecting the point cloud, this paper explains the limitations of the classical processing approach and gives an overview of our new pipeline. The effectiveness of the proposed approach is established by discussing the results that have been obtained in several studies based on GAIMS.

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“…The candidate shape of a human's leg is picked out from LRF data and the truth is judged by searching for the circle pair that has the size of leg section, and using the pattern match with the leg appearance movement model. Lee extracts the set of the LRF detection points based on a dynamic feature from the time series of data, and detects a pair that suits the person's walking step pattern and the leg size from the sets, and finally concludes that the pair is human and continues tracking it (Lee et al, 2006). Okusako detects the person's position by the block match with the template of typical scanning shape of the leg observed during walking (Okusako et al, 2006).…”

Section: Lrf Tracking Problemsmentioning

confidence: 99%