• Journal of Mechanical Science and Technology
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• 제14권2호
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• pp.131-140
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• 2000

For a walking robot with high constant body speed, the dynamic effects of the legs on the transfer phase are dominant compared with other factors. This paper presents a new force distribution algorithm to maximize walkable terrain without slipping considering the dynamic effects of the legs on the transfer phase. Maximizing the walkable terrain means having the capability of walking on more slippery ground under the same constraint, namely constant body speed. A simple force distribution algorithm applied to the proposed walking model with a pantograph leg shows an improvement in the capability of preventing foot-slippage compared with one using a pseudo-inverse method.

• 대한임베디드공학회논문지
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• 제12권5호
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• pp.331-341
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• 2017

This paper presents the sea-trial results of Crabster CR6000 which is a deep-sea walking robot developed by KRISO in 2016. Crabster CR6000 is designed to inspect deep-sea environment rejecting the disturbance on the silent and calm abyssal area. The sea-trial was conducted at the East Sea and the Philippine Sea on December 2016. The Crabster CR6000 undocked successfully from the Shuttle after touchdown on the sea-bed and walked out on the soft sediment soil of the 4,743m seafloor at the fourth diving in the Philippine Sea. The advanced technologies and capabilities of CR6000 were verified from the operational and functional test conducted in the sea-trial. The experimental data acquired from the sea-trial were summarized and the first experience of the deep-sea walking robot was presented in this paper.

• 한국정보통신학회논문지
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• 제14권8호
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• pp.1925-1936
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• 2010

영상카메라와 무선통신 기능을 탑재한 손모양 및 장애물 인식이 가능한 다족 로봇을 독자적으로 설계 및 제작하고 제작한 로봇에 최적화된 보행패턴 알고리즘을 개발하여 적용하였다. 영상센서의 입력화상에 대해 하프변환 (Hough Transform)을 사용하여 물체의 외곽선을 추출하여 장애물을 인식하여 회피하는 실시간 자율보행이 가능한 알고리즘을 개발하였다. 로봇의 목표물 및 목적지 설정을 위하여 미리 학습시킨 피부색의 평균값과 입력영상의 확률거리(Mahalanobis Distance)를 산출하여 손 영역을 검출하고 손가락 개수에 따라 로봇의 명령 제어가 가능하도록 하였다. 장애물 및 손모양 인식에 따른 다족 자율 보행 로봇의 수행 실험 평균 결과 약 96%의 장애물 인식률과 94%의 손 모양 인식률을 보였다.