Author name cluster

Hiroaki Seki

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

4 papers

1 author row

IROS Conference 2023 Conference Paper

Whole Shape Estimation of Transparent Object from Its Contour using Statistical Shape Model

Kaihei Okada
Riku Kobayashi
Tokuo Tsuji
Tatsuhiro Hiramitsu
Hiroaki Seki
Toshihiro Nishimura
Yosuke Suzuki
Tetsuyou Watanabe

This study presents a method for estimating the three-dimensional (3D) shapes of transparent objects from an RGB-D image using a statistical shape model. Statistical shape models compress the dimensions of multiple shapes to represent shape variations using fewer parameters. It is difficult to measure the depth of a transparent object using sensors. Therefore, the statistical shape model is deformed to fit the contour extracted from an RGB image and estimate the shape of the object. The depth image is used only to detect the plane on which the transparent objects are placed. Unlike other estimation methods, the proposed method estimates the whole shape of a transparent object. To validate the proposed method, the obtained estimation accuracy is compared with that of a machine-learning-based method. In addition, the estimated whole shape is compared with the measured data from a 3D scanner.

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IROS Conference 2021 Conference Paper

Casting manipulation of unknown string by robot arm

Kenta Tabata
Hiroaki Seki
Tokuo Tsuji
Tatsuhiro Hiramitsu

Casting manipulation has been studied to expand the robot’s movable range. In this manipulation, the robot throws and reaches the end effector to a distant target. Usually, a special casting manipulator, which consists of rigid arm links and specific flexible linear objects, is constructed for an effective casting manipulation. However, the special manipulator cannot perform normal manipulations, such as picking and placing, grasping, and operating objects. We propose that the normal robot arm, which can perform normal tasks, picks up an unknown string in the surrounding environment and realizes casting manipulation with it. As the properties of the string are not provided in advance, it is crucial how to reflect it in casting manipulation. This is realized by the motion generation of the robot arm with the simulation of string movement, actual string manipulation by the robot arm, and string parameter estimation from the actual string movement. After repeating these three steps, the simulated string movement approximates the actual to realize casting manipulation with the unknown string. We confirmed the effectiveness of the proposed method through experiments. The try of this study will lead to enhancement of the performance of home service robot, exploration robot, rescue robot and entertainment robot.

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ICRA Conference 2000 Conference Paper

Autonomous/Semi-Autonomous Navigation System of a Wheelchair by Active Ultrasonic Beacons

Hiroaki Seki
S. Kobayashi
Yoshitsugu Kamiya
Masatoshi Hikizu
Hisanao Nomura

This paper describes the autonomous and semi-autonomous navigation system of a powered wheelchair for disabled people and nursing staffs. In order to detect its position reliably, this system utilizes active ultrasonic beacons on ceiling. 2 receivers on a wheelchair measure the time-of-flight of the ultrasonic pulses from 2 beacons. Since the distances from only 1 beacon can be obtained at once, the position should be dynamically estimated with its movement in a measurement interval during navigation. Three types of navigation mode by this positioning system are also proposed to assist users. "Automatic transfer mode" guides a wheelchair to a target position autonomously. "Operation assistance mode" helps a user's operation by moving a wheelchair straight toward a commanded direction. "Selective semi-automatic mode" runs path networks selecting a desired direction at each branch point. These navigations were successful in practice.

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IROS Conference 1995 Conference Paper

Detection of kinematic constraint from search motion of a robot using link weights of a neural network

Hiroaki Seki
Ken Sasaki
Masaharu Takano

In this paper, a method for detecting kinematic constraints in a plane when the shapes of the grasped object and the environment are not given is presented. This method utilizes the displacement and force information obtained by "active search motion" of a robot. A new neural network configuration for this detection is proposed. It consists of two multilayer networks (primary and secondary network). The primary network learns the movable space (constraint) obtained by the search motion. By the generated link weights which reflect the movable space, the secondary network determines the type and the orientation of the constraint. Simulation and experimental results are presented and analyzed.

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