Rule–based reasoning and neural network perception for safe off–road robot mobility

Abstract-The histopathological d iagnosis of breast diseases requires highly trained and experienced experts, and often strains pathologists' cognitive capabilit ies. Accurate and timely d iagnosis of breast diseases is essential for the appropriate management of the patients.The paper presents a knowledge base system that uses a comb ination of rule -based and case-based techniques to achieve the diagnosis. Rule-based systems handle problems with well-defined knowledge bases this limits the flexibility of such system. Casebased reasoning has been adopted to overcome this inherent weakness of rule-based systems by incorporating previous cases in the generation of new cases to improve the performance of the system. The result of this research shows that the system is capable of assisting pathologists in making accurate, consistent and timely diagnoses. The system also aid in eliminating errors of o mission that have been viewed as a prominent cause of medical errors . In conclusion this paper investigated the histological features used in the diagnosis of breast diseases and proposed an integrated knowledge base system based on the features.

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“…This covers areas such as mining [28] , co mmerce [29] , diagnosis [30] , medicine [31] , and robotics [32] .…”

Section: Related Workmentioning

confidence: 99%

An Integrated Knowledge Base System Architecture for Histopathological Diagnosis of Breast Diseases

Kayode¹,

Afolabi²,

Adelusola³

2012

IJITCS

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“…There are several methods to estimate terrain slopes [1][2]4,10]. The slope will be either a positive value for upward terrain or a negative value for downward terrain.…”

Section: Terrain Slopementioning

confidence: 99%

Fuzzy-based speed estimation for navigation of unmanned robots

Jin

Lee

Lee³

et al. 2010

Int. J. Control Autom. Syst.

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This study presents a framework for assessing the navigation speed of unmanned robots by combining information extracted from the 3D world model of natural terrain with regional traversability based on the fuzzy technique. The proposed method divides the world model into several patches, extracts the slope and roughness of each terrain patch along four heading directions, and then uses them to evaluate the level of difficulty associated with the traversal. The slope is estimated through curved surface fitting, and roughness is obtained using fractal-based analysis together with another two RMS metrics. As navigation systems can cope with the imprecision and uncertainty of input data, we modify the Seraji's fuzzy-based measure to assess the traversability and navigation speed of each patch for path planning. The proposed method is tested on both fractal and real terrain to verify its effectiveness.

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“…The Traversability Index is used for classifying planetary surfaces and provides a simple means for incorporating the terrain quality data. Moreover, there are also other methods, such as the neural network based architecture [6] and a probabilistic modeling technique for high-speed rough-terrain analysis of outdoor mobile robots [7]. Except for only several methods, like the GESTALT, which has been validated on real planetary environment, many other methods still suffer degradation due to the complex, unstructured terrain and unavoidable uncertainty in measurement, although they are mostly experimentally shown accurate in well-known terrain.…”

Section: Related Workmentioning

confidence: 99%

Visual traversability analysis for micro planetary rover

Wang¹,

Shen²,

Xu³

et al. 2009

2009 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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Traversability analysis is a significant and challenging problem for planetary rover's navigation and safeguard on rocky and bumpy terrain. Moreover, the growing requirement for the micro rover in future planetary missions demands robust traversability analysis upon limited sensors and field of perception. In this paper, a framework for stereo based terrain mapping and traversability analysis in autonomous navigation is developed for the micro planetary rover. In this work, a Joint Reliability based Disparity Expansion (JRDE) algorithm is proposed to obtain accurate 3D information of the local terrain. Focusing on the low complexity and robust performance, we report a hierachical Digital Elevation Map (DEM) based method to achieve the traversability map with relative index value, which consists of elevation thresholding and estimation of slope and roughness. Path planning is subsequently fulfilled upon the traversability map. This method is validated with a set of planet-surface like scenes, while complete onboard system has also been proved fast and effective in artificial rocky environment.

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Rule–based reasoning and neural network perception for safe off–road robot mobility

Cited by 12 publications

References 19 publications

An Integrated Knowledge Base System Architecture for Histopathological Diagnosis of Breast Diseases

An Integrated Knowledge Base System Architecture for Histopathological Diagnosis of Breast Diseases

Fuzzy-based speed estimation for navigation of unmanned robots

Visual traversability analysis for micro planetary rover

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