Shape estimation of flexible cable

Ishikura, Michihisa; Takeuchi, Eijiro; Konyo, Masashi; Tadokoro, Satoshı

doi:10.1109/iros.2012.6385700

Cited by 8 publications

(3 citation statements)

References 7 publications

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“…The objective accuracy of the posture estimation is defined with the tip position error. Ishikura et al [17] achieved a tip position error of under about 0.2 m at 35 s estimation with a 3.0 m mock-up robot by using the inertial sensor approach. To overcome this method, we set the objective accuracy as 0.2 m.…”

Section: Methodsmentioning

confidence: 99%

“…Ishikura et al proposed an inertial sensor-based posture estimation method. [17] Because of a cumulative error problem peculiar to inertial sensors, the estimation error increases with the passage of time. Moreover, it is difficult to maintain precision due to a sudden posture change problem caused by external forces.A non-integral method, that is, a method independent of drive time, is needed.…”

Section: Introductionmentioning

confidence: 99%

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Posture estimation of hose-shaped robot by using active microphone array

Bando¹,

Otsuka²,

Mizumoto³

et al. 2015

Advanced Robotics

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Hose-shaped rescue robots have been developed for searching narrow spaces such as under collapsed buildings. The posture estimation independent of the past history is critical, because conventional inertial-sensor-based posture estimation has two main problems; a cumulative error problem peculiar to inertial sensors, and a sudden posture change problem caused by external forces. For coping with the two problems, we developed a novel posture estimation method by putting an active microphone array, a set of microphones and loudspeakers, on the robot. The method calculates the time difference of arrival (TDOA) of the reference signal emitted from one loudspeaker, and estimates the posture from the distance obtained by TDOA. This concise method still has three problems: (1) external noise, (2) reverberation and reflection, and (3) obstacles. These problems are tackled by (1) TSP signal, (2) GCC-PHAT and a threshold-based onset detection, and (3) rejecting incorrect onset times, respectively. Experiments with simulated sounds and actual recordings demonstrate that the method attains the performance of estimation comparable to that of conventional methods, that is, less than 20 cm of the tip position error. Even without historical data, the method attains the similar performance while conventional methods fail.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Posture estimation of hose-shaped robot by using active microphone array

Bando¹,

Otsuka²,

Mizumoto³

et al. 2015

Advanced Robotics

Self Cite

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show abstract

“…This method often failed to extract similar points due to excessive brightness canceled by the tip light or the image having few characteristics, as with a smooth wall. Ishikura et al [11] then estimated a ASC posture by using inertial sensors and magnetic sensors. They adopted a flexible dynamics model of the ASC and estimated 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) November 3-7, 2013.…”

Section: Introductionmentioning

confidence: 99%

Posture estimation of hose-shaped robot using microphone array localization

Bando

Mizumoto

Itoyama

et al. 2013

2013 IEEE/RSJ International Conference on Intelligent Robots and Systems

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This paper presents a posture estimation of hoseshaped robot using microphone array localization. The hoseshaped robots, one of major rescue robots, have problems with navigation because their posture is too flexible for a remote operator to control to go as far as desired. For navigational and mission usability, the posture estimation of the hose-shaped robot is essential. We developed a posture estimation method with a microphone array and small loudspeakers equipped on the hose-shaped robot. Our method consists of two steps: (1) playing a known sound from the loudspeaker one-by-one, and (2) estimating the microphone positions on the hose-shaped robot instead of estimating the posture directly. We designed a time difference of arrival (TDOA) estimation method to be robust against directional noise and implemented a prototype system using a posture model of the hose-shaped robot and an Extended Kalman Filter (EKF). The validity of our approach is evaluated by the experiments with both signals recorded in an anechoic chamber and simulated data.

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