This paper proposes a position and posture control method of the 6 DOF arm of the Humanoid Robot by Linear Visual Servoing. It is based on the linear approximation of the forward kinematics which has a similar kinematic structure as a human being. Forward kinematics is the transformation from joint space to binocular visual space. Pseudo inverse matrix of the 3 linear approximation matrices of the 3 points makes it possible to realize position and posture control of 6 DOF arm by Linear Visual Servoing. It is very robust to calibration error of camera angles, because it uses neither camera angles nor joint angles to calculate feedback command. Furthermore, the amount of calculation is very small compared to the conventional visual servoing schemes. Although the conventional 6 DOF arm control methods based on pseudo inverse matrix need non-linear complex calculation using joint angle, the proposed method does not need it. Simulation results are presented to demonstrate the effectiveness of the proposed method.

We proposed a simple visual servoing scheme called linear visual servoing (indicated as LVS). It is based on the linearity of the transformation from binocular visual space to joint space of the arm of the humanoid robot which has a similar kinetic structure as a human being. LVS is very robust to calibration errors, especially to camera angle errors, because it uses constant Jacobian matrix with neither camera angles nor joint angles to calculate feedback command. Furthermore, the amount of calculation is very small compared to conventional visual servoing schemes. Hence, it is especially suitable for humanoid robots which use active stereo vision. But conventional LVS can not deal with redundant arm, because it is based on linear approximation of inverse kinematics. In this paper, we propose a redundant arm positioning control method by linear visual servoing based on linear approximation of forward kinematics. Simulation and experimental results are presented to demonstrate the effectiveness of the proposed method.

In the drive towards miniaturization in manufacturing, accuracy in positioning minute objects by camera is vital For visual servoing, the rapid and robust detections of features in camera images is also essential to production line efficiency. Template matching provides flexibility in achieving this, often lacked by other methods, because it avoids the need to set object-specific parameters. Unfortunately, standard methods of template matching require much calculation, especially for detecting feature rotation. The delay this causes means that for many applications template matching provides too slow a source of visual feedback. As apr alternative, we propose a new method of detecting the translation and rotation of a feature from coarse optical flow, we and apply it to visual servoing. Coarse optical flow is derived from the difference in intensity between a region of the initial and current image and their pixel-by-pixel intensity gradients. Unlike template matching, our method can detect large rotations with relatively little calculation. Image resolution is then adjusted from coarse to fine. Sub-pixel accuracy results in a 100 fold improvement in precision (by area). We show experimental results for precise planar positioning.

With robots moving in an unknown 3D environment, it is necessary to work out a method for reconstruction of surface structures (that is, where a surface is present and where there is a free space). In this paper, a method is proposed to recover surfaces by means of active moving of a stereo camera. First, the surface structure of the environment under consideration is represented by a set of virtual 3D segments (arcs) obtained by connecting edge points that lie on the same epipolar line; then the 3D position information and occlusion information acquired by active moving of the stereo camera are used to decide if a physical surface exists between the arcs. Using surface structures that have been so far recovered, camera location that offers the best results in surface reconstruction is predicted, and the camera is moved to this new location to obtain more precise results. The proposed method offers a way to select view-points that ensure efficient surface reconstruction, which has not been discussed in any previous study. Experiments showed that the proposed method offers correct reconstruction of object surfaces with a small number of measurements. © 1997 Scripta Technica, Inc.

In this paper, foveated vision for scene exploration is implemented. The peripheral and central vision are the basic capabilities of foveated vision. The informations obtained from the peripheral vision are used to determine the next gaze point. Due to the low resolution of the periphery, however, the determination is not always appropriate. To solve this problem, we propose to evaluate the target object by the central vision after gazing. We implement foveated vision based on the Log Polar Mapping (LPM) and construct an evaluation scheme of the target object in the central vision using LPM rotational-invariance. The peripheral vision is realized by Zero Disparity Filter for LPM stereo images. Some experimental results are Mso shown to demonstrate the effectiveness of the proposed method.

We propose a simple visual servoing scheme based on the use of binocular visual space. When we use a hand-eye system which has a similar kinematic structure to a human being, we can approximate the transformation from a binocular visual space to a joint space of the manipulator as a linear time-invariant mapping. This relationship makes it possible to generate joint velocities from image observations using a constant linear mapping. This scheme is robust to calibration error, especially to camera turning, because it uses neither camera angles nor joint angles. Some experimental results are also shown to demonstrate the positioning precision remained unchanged despite the calibration error.

This paper describes a new binocular tracking method using Log Polar Mapping (LPM) which approximately represents the mapping of the retina into the visual cortex in primate vision. Using LPM makes it possible not only to obtain both a high central resolution and a Wide field of view, but also to significantly reduce processing image data. In this paper, LPM is performed in software by lookup table method, Our tracking method utilizes zero disparity filter (ZDF) for extracting the target object and virtual horopter method for estimating binocular disparities, respectively. The performance of both target extraction and disparity estimation is improved in comparison With the conventional methods, by using LPM. Some experimental results are also shown to demonstrate the effectiveness of the proposed method.

The major problem in binocular stereo vision is a well-known correspondence problem. Almost of the previous works solved this problem by imposing the additional constraints such as smoothness constraint or the ordering constraint etc. Therefore, they can not find the occlusion correctly and deal with the transparent surfaces, because these constraints are violated. In this paper, we propose an active algorithm to detect binocular disparities without using additional constraints. It is based on the motion parallax obtained by the moving monocular camera. The search range of binocular disparity is restricted based on the monocular motion parallax. The condition to find binocular disparities is only the uniqueness of disparity. Experimental results with complicated scene are presented to demonstrate the effectiveness of this method.

We propose position and attitude control method of Eye-In-Hand Robot by Dynamic visual servoing based on Virtual Spring-Dumper Hypothesis using Binocular Visual Space Error. We obtain the 3D position and attitude error from the binocular visual space error using Jacobian between cartesian space and binocular visual space. The proposed method is robust to calibration error of camera angles, because it does not use camera angles to calculate feedback command. Simulation results are presented to demonstrate the effectiveness of the proposed method.

We propose a method for following motion control of the mobile robot by using Linear Visual Servoing (LVS). Following motion control is realized by the following motion of the body to the target object keeping a desired distance. Following motion control by using LVS is based on linear approximation of the transformation between binocular visual space and motion space of the mobile robot. Motion space is defined by translational velocity and rotational velocity of the robot coordinate system which is attached at the center of gravity of the mobile robot. Some experimental results are presen...

This paper propose a, reaching control method of the 3 d.o.f. arm of the humanoid robot by linear visual servoing. Linear visual servoing is based on the linear approximation between binocular visual space and joint space of the arm of the humanoid robot which has a, similar kinematic structure as a human being. It is very robust to calibration error, especially to camera, angle errors and Joint angle errors, because it uses neither camera angles nor Joint angles to calculate feedback command. Although we showed that 3D linear visual servoing is effective in reaching control of the 3 d.o.f. arm of the humanoid robot, the reaching speed is slow because of image sampling time. Furthermore, visual servoing is effective when both the end tip of the arm and the target is in an image. In this paper, we propose a fast and accurate reaching control method of the humanoid robot by combining slow but accurate linear visual servoing and inaccurate but fast open loop control. Some experimental results are presented to demonstrate the effectiveness of the proposed method.

人間は視覚から膨大な情報を取り込みそれを元に行動している。将来ロボットが人間の生活空間に入り, 人間と協調, 共存して作業を行う場合, 視覚を用いて目標物体に対してリーチング及び移動追従させる制御が必要となる。我々は, 目標視空間座標の構成式においてカメラ角が全く含まれず, 完全な視差情報のみに基づく制御が可能な線形ビジュアルサーボによるヒューマノイドロボットのリーチング, 追従制御等を紹介する。

The planar positioning of an object using a camera is an important technique for minute manufacturing. And detecting a feature in an image is an essential subject for it, thus research has been actively pursued in this area. Template matching is a useful method of detecting a feature in an image. It doesnt require any complicated settings, and we can use it more easily than other methods (centroid determination in binary image processing, etc.), by an equipment on the market. However, template matching is poor at detecting the rotation of a feature, and the amount of calculation is large. I...

This paper presents, in positioning a robot manipulator by visual servoing with stereo vision, when pan angles are not exactly calibrated, the analysis of unreconstructible surface from images, the effect on visual servoing, and the region robust to calibration error about pan angles.

This paper presents, in positioning a robot manipulator by visual servoing with stereo vision, when pan angles are not exactly calibrated, the analysis of unreconstructible surface from images, the effect on visual servoing, and the region robust to calibration error about pan angles.

This paper describes a new binocular tracking method using Log Polar Mapping (LPM) which approximately represents the mapping of the retina into the visual cortex in primate vision : Using LPM makes it possible not only to obtain both a high central resolution and a wide field of view, but also to significantly reduce processing image data. In this paper, LPM is performed in software by lookup table method. Our tracking method utilizes zero disparity filter (ZDF) for extracting the target object and virtual horopter method for estimating binocular disparities, respectively. The performance of both target extraction and disparity estimation is improved in comparison with the conventional methods, by using LPM. Some experimental results are also shown to demonstrate the effectiveness of the proposed method.

We propose a simple visual servoing scheme based on the use of binocular visual space. When we use a hand-eye system which has a similar kinematic structure to a human being, we can approximate the transformation from a binocular visual space to a joint space of the manipulator as a linear time-invariant mapping. This relationship makes it possible to generate joint velocities from image observations using a constant linear mapping. This scheme is robust to calibration error, because it uses neither camera angles nor joint angles. Some experimental results are also shown to demonstrate the positioning precision remained unchanged despite the calibration error.

We propose a linear approximation method of the inverser kinematics of a manipulator by using a binocular visual space. When we use a hand-eye system which has a similar structure as a human being, we can approximate the transformation from a binocular visual space to a joint space of the manipulator as a linear function. We show that the most suitable structure of a stereo camera and a manipulator for linear approximation of the inverser kinematics is similar to human being.

We propose a simple visual servoing based on linear approximation of the inverse kinematics. When we use a hand-eye system which has a similar structure as a human being, we can approximate the transformation from a binocular visual space to a joint space of the manipulator as a linear function. This relationship makes it possible to produce the desired joint angles from the image data using a constant linear function instead of the variable nonlinear image jacobian and robot jacobian. This method is robust to the calibration error, because it uses neithor camera angles nor joint angles. We...

未知の3次元環境を認識・行動するロボットにとって, 環境の面構造(どこが面でどこが空間か)を復元する手法を確立することは必要不可欠な課題である. 本論文では, ステレオカメラをアクティブに運動させることにより環境の面構造を復元する一方法を提案する. まず, 左右の各画像中で同一のエピポーラ線上に連続して出現する二つのエッジ間に対応する仮想的な3次元線分(アーク)の集合によって環境の面構造を表現し, ステレオカメラをアクティブに運動させることにより得られるエッジ点の3次元位置情報と隠れ情報に基づいて, 各アーク間に物体表面が存在するか否かの判定を行う. 更に, 現在までに復元された面構造に基づいて, 物体表面が存在するか否かが新たに最も多く決定できるであろうカメラ位置を予測し, その位置ヘステレオカメラを移動させた後, 同様の処理を新たに決定できる可能性があるアークが生じなくなるまで繰り返し行う. 本方法は, 従来の研究ではほとんど議論されていなかった面構造を効率良く復元するためのカメラの移動戦略や視点の選択法に対する一つの解答を与えている. 提案する手法を用いれば, 少ない観測回数で環境の面構造が正しく復元できることが, 実シーンを用いた実験により示される.

球の輪郭線や円柱の側面のように,視点位置に依存して生成される輪郭線(=輪郭生成線)の像を隠れ輪郭と呼ぶ.隠れ輪郭には物体表面を記述するための多くの有益な情報が含まれている.本論文では.ステレオカメラをアクティブに運動させることにより曲面の隠れ輪郭を検出する一方法を提案する.まず,物体表面と隠れ輪郭の幾何学的関係を記述するモデル(隠れ輪郭モデル)を導出する.カメラのアクティブな移動によって生じる像の動きをこのモデルに当てはめると,もう一方のカメラにおける対応点の存在範囲を拘束することができる.この幾何学的拘束に基づいて各画像間でステレオ対応付けを行い,得られた対応点の系列をモデルに最小2乗フィッティングさせることによって画像中の隠れ輪郭を検出する.本論文で示す方法では,隠れ輪郭のモデルを直接利用してステレオ対応処理を行っているために,モデルを用いない方法や発見的拘束を用いる従来の手法に比べて,より正確に隠れ輪郭を検出することができる.また,隠れ輪郭近傍の局所3次元形状をモデルから容易に推定することができるという利点もある.人工画像ならびに実画像を用いたいくつかの実験により提案する手法の有効性を示している.

This paper presents a new method of visual servoing with stereo vision to control the position of a manipulator with respect to an object. Conventional control methods by visual servoing use a monocular camera and have several problems. For example, either shape information or desired distance of the target object from the camera must be given. Furthermore, it is not stable if the initial positional error of features in the image is very large. These problems are caused by image the Jacobian matrix, that is, the approximate value at desired position is used instead of correct one. By using stereo vision, the image Jacobian matrix can be calculated correctly at any position. So neither shape information nor desired distance of the target object is required. It is also stable even if the initial error is very large. Both simulation and experimental results are presented to demonstrate the effectiveness of this method.

The major problem in binocular stereo vision is a well-known correspondence problem. Almost of the previous works solved it by regularization with the additional constraints such as the smoothness constraint or the ordering constraint. Therefore, they can not find the occlusion correctly and deal with the transparent surfaces, because these constraints are violated in the complicated scene contain-ing many occlusion. In this paper, we propose a method to detect binocular disparity and occlusion without using additional constraints by moving stereo cameras actively. It is based on the motion...

小・中・高校生を対象とした学部体験入学・出張講座等

ヒューマノイドロボットのデモを行った,日付:2013.11～2013.11

小・中・高校生を対象とした学部体験入学・出張講座等

ヒューマノイドロボットのデモを行った,日付:2013.8～2013.8

学術雑誌等の編集委員・査読・審査員等

論文の査読

小・中・高校生を対象とした学部体験入学・出張講座等

ヒューマノイドロボットのデモを行った,日付:2012.8～2012.8

小・中・高校生を対象とした学部体験入学・出張講座等

ヒューマノイドロボットのデモを行った,日付:2012.11～2012.11

小・中・高校生を対象とした学部体験入学・出張講座等

高校生に大して2泊3日のサイエンスキャンプを行った,日付:8月20日～22日

公開講座・講演会の企画・講師等

体験学習でロボットの操作体験をさせた,日付:11月24日

公開講座・講演会の企画・講師等

体験学習でロボットの操作体験をさせた,日付:11月24日

小・中・高校生を対象とした学部体験入学・出張講座等

ヒューマノイドロボットのデモを行った,日付:2011.8～2011.8

小・中・高校生を対象とした学部体験入学・出張講座等

ヒューマノイドロボットのデモを行った,日付:2011.11～2011.11

小・中・高校生を対象とした学部体験入学・出張講座等

ヒューマノイドロボットのデモを行った,日付:2010.11～2010.11

小・中・高校生を対象とした学部体験入学・出張講座等

ヒューマノイドロボットのデモを行った,日付:2010.8～2010.8

公開講座・講演会の企画・講師等

オープンキャンパスでヒューマノイドロボットのデモを行った,日付:2009.11

小・中・高校生を対象とした学部体験入学・出張講座等

ヒューマノイドロボットのデモを行った,日付:2009.8

小・中・高校生を対象とした学部体験入学・出張講座等

ヒューマノイドロボットのデモを行った,日付:2008.8～2009.8

公開講座・講演会の企画・講師等

オープンキャンパスにおけるデモ,日付:2008.11

小・中・高校生を対象とした学部体験入学・出張講座等

ヒューマノイドロボットのデモを行った,日付:2008.8～2009.8

公開講座・講演会の企画・講師等

ヒューマノイドロボットのデモを行った,日付:2007.11

小・中・高校生を対象とした学部体験入学・出張講座等

ヒューマノイドロボットのデモを行った,日付:2007.8

公開講座・講演会の企画・講師等

ヒューマノイドロボットのデモを行った,日付:2006.11

小・中・高校生を対象とした学部体験入学・出張講座等

ヒューマノイドロボットのデモを行った,日付:2006.8

学術雑誌等の編集委員・査読・審査員等

奨励賞選考委員,任期:１

公開講座・講演会の企画・講師等

和歌山商工会議所からの依頼により、和歌山商工まつりにてロボットの展示デモンストレーションを行った。,日付:2004.10

小・中・高校生を対象とした学部体験入学・出張講座等

桐蔭高校の依頼により、1年生の理科系学生40人にスーパーサイエンスハイスクールにおけるロボット教育として、ロボットのしくみの講義とマインドストームを用いた製作実習の指導を行った。,日付:2004.7

公開講座・講演会の企画・講師等

放送大学からの依頼により、社会人に対してロボットのしくみについて講義した。,日付:2003.4～2004.4

小・中・高校生を対象とした学部体験入学・出張講座等

桐蔭高校の依頼により、1年生の理科系学生40人にスーパーサイエンスハイスクールにおけるロボット教育として、ロボットのしくみの講義とマインドストームを用いた製作実習の指導を行った。,日付:2003.11～2004.11

公開講座・講演会の企画・講師等

放送大学からの依頼により、社会人に対してロボットのしくみについて講義した。,日付:2003.4～2004.4

小・中・高校生を対象とした学部体験入学・出張講座等

桐蔭高校の依頼により、1年生の理科系学生40人にスーパーサイエンスハイスクールにおけるロボット教育として、ロボットのしくみの講義とマインドストームを用いた製作実習の指導を行った。,日付:2003.11～2004.11

小・中・高校生を対象とした学部体験入学・出張講座等

桐蔭高校によるスーバーサイエンスプログラムにおいて高校1年生の理科系学生約40名に対してロボットのしくみと動作プログラムの製作実習の指導を行った。,日付:2003.1

学術雑誌等の編集委員・査読・審査員等

会誌編集委員会委員,任期:2年

学術雑誌等の編集委員・査読・審査員等

論文査読小委員会委員,任期:2年

研究成果に係る新聞掲載、テレビ・ラジオ出演

人間と類似の構造を持ったヒューマノイドロボットにおける視空間と関節空間の線形近似に基づいた線形ビジュアルサーボによる腕の制御方法について報道された。

学協会、政府、自治体等の公的委員

学協会、政府、自治体等の公的委員,任期:2010.4～2012.3

学協会、政府、自治体等の公的委員

学協会、政府、自治体等の公的委員,任期:2009.7～2009.9

国や地方自治体、他大学・研究機関等での委員

奨励賞選考委員 ,任期:2006.11～2007.9