Dynamic Obstacle Avoidance in Multi-Robot Motion Planning Using Prediction Principle in Real Environment
Suparna Roy,
Dhrubojyoti Banerjee,
Chiranjib Guha Majumder,
Amit Amit Konar,
R. Janarthanan
Issue:
Volume 1, Issue 2, April 2013
Pages:
16-23
Received:
28 December 2012
Accepted:
Published:
2 April 2013
Abstract: This paper provides a new approach to the multi-robot path planning problem predicting the position of a dynamic obstacle which undergoes linear motion in the given workspace changing its direction at regular intervals of time. The prediction is done in order to avoid collision of the robots with the dynamic obstacle. First the work is done in simula-tion environment then the entire work has been implemented on Khepera II mobile robot. The performance of the above mentioned approach has been found to be satisfactory compared to the classical non-predictive approaches of dynamic obstacle avoidance.
Abstract: This paper provides a new approach to the multi-robot path planning problem predicting the position of a dynamic obstacle which undergoes linear motion in the given workspace changing its direction at regular intervals of time. The prediction is done in order to avoid collision of the robots with the dynamic obstacle. First the work is done in simu...
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Computer-Aided Diagnosis of Pneumoconiosis X-ray Images Scanned with a Common CCD Scanner
Koji Abe,
Takeshi Tahori,
Masahide Minami,
Munehiro Nakamura,
Haiyan Tian
Issue:
Volume 1, Issue 2, April 2013
Pages:
24-33
Received:
Accepted:
Published:
2 April 2013
Abstract: This paper presents a discrimination of pneumoconiosis X-ray images obtained with a common CCD scanner. Current computer-aided diagnosis systems of pneumoconiosis have been proposed to images obtained with a special scanner such as a drum scanner or a film scanner for X-ray pictures. However, since the special scanners need a large storage space and the scanners and commitment of the imaging need high-priced costs, the systems are not practical in small clinics. In this paper, we propose features for measuring abnormalities of pneumoconiosis as variables for the discrimination. Devices in the proposed system are only a tablet PC and a CCD scanner. In images obtained with CCD scanner, abnormal levels of pneumoconiosis could depend on density distribution in rib areas. Therefore, the proposed method measures the abnormalities by extracting characteristics of the distribution in the areas. Besides, using the abnormalities, the proposed method discriminates chest X-ray images into normal or abnormal cases of pneumoconiosis. Experimental results of the discriminations for 59 right-lung images have shown that the proposed abnormalities are well extracted for the discrimination.
Abstract: This paper presents a discrimination of pneumoconiosis X-ray images obtained with a common CCD scanner. Current computer-aided diagnosis systems of pneumoconiosis have been proposed to images obtained with a special scanner such as a drum scanner or a film scanner for X-ray pictures. However, since the special scanners need a large storage space an...
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