Behavior Fusion for Visually-Guided Service Robots

Abdellatif, Mohamed

doi:10.5772/6165

Cited by 4 publications

(3 citation statements)

References 15 publications

(18 reference statements)

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“…There are other works in the same line, in (Calisi et al, 2007) is presented an approach that integrates appearance models and stereoscopic vision for decision people tracking in domestic environments. In (Abellatif, 2008) the author used a vision system for obstacle detection and avoidance, it was proposed a method to integrate the behavior decisions by using potential field theory (Khatib, 1985) with fuzzy logic variables. It was used Hue, Saturation, and Intensity (HSI) color since it is perceptually uniform.…”

Section: Introductionmentioning

confidence: 99%

Vision Based Obstacle Detection Module for a Wheeled Mobile Robot

Montiel¹,

González²,

Sepúlveda³

2010

Mobile Robots Navigation

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Section: Introductionmentioning

confidence: 99%

Vision Based Obstacle Detection Module for a Wheeled Mobile Robot

Montiel¹,

González²,

Sepúlveda³

2010

Mobile Robots Navigation

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“…In [8], repulsive behaviour from previously visited areas was used for exploration. In [9,10], a complex behaviour architecture was proposed in which a combination of several weighted behaviours were fused together for efficient exploration. These behaviours can be generally formulated as: "go to frontier", "go to unexplored areas", "avoid other robots" and "avoid obstacles".…”

Section: Robot Exploration Algorithms and Backtracking Techniquesmentioning

confidence: 99%

“…The exploration process could be decomposed into smaller, simple, reactive tasks, which leads to the use of behaviourbased exploration approaches [5][6][7][8][9][10][11]. The exploration task is divided into simple simultaneous actions.…”

Section: Robot Exploration Algorithms and Backtracking Techniquesmentioning

confidence: 99%

Robotic Exploration: New Heuristic Backtracking Algorithm, Performance Evaluation and Complexity Metric

El-Hussieny

Assal

Abdellatif

2015

International Journal of Advanced Robotic Systems

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Mobile robots have been used to explore novel environments and build useful maps for navigation. Although sensor-based random tree techniques have been used extensively for exploration, they are not efficient for timecritical applications since the robot may visit the same place more than once during backtracking. In this paper, a novel, simple yet effective heuristic backtracking algorithm is proposed to reduce the exploration time and distance travelled. The new algorithm is based on the selection of the most informative node to approach during backtracking. A new environmental complexity metric is developed to evaluate the exploration complexity of different structured environments and thus enable a fair comparison between exploration techniques. An evaluation index is also developed to encapsulate the total performance of an exploration technique in a single number for the comparison of techniques. The developed backtracking algorithm is tested through computer simulations for several structured environments to verify its effectiveness using the developed complexity metric and the evaluation index. The results confirmed significant performance improvement using the proposed algorithm. The new evaluation index is also shown to be representative of the performance and to facilitate comparisons.

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