並木 明夫

A new robotic hand system with high-speed finger motion of 180 [deg] per 0.1 [s] has been developed. With highspeed visual feedback at a rate of 1 [kHz], various dynamic manipulations are achieved. As examples of dynamic manipulation we describe the dynamic active catching tasks for a failing ball and a failing cylinder using a high-speed multifingered hand. We achieved these difficult tasks by utilizing high-speed motion and impact forces actively. Experimental results using active catching strategy based on visual feedback are shown.

In this paper a robotic batting algorithm using a high-speed arm and high-speed stereo vision is proposed. With this strategy, the desired trajectory of the manipulator is generated so that both high-speed swing motion and tracking motion combine to meet the ball squarely with the bat. As a result the manipulator can follow the ball while swinging the bat at high speed even if it is difficult to predict the trajectory of a ball. Experimental results are shown in which a high-speed manipulator hits a ball thrown by a human.

The efferent signal is the impulses from the brain to muscle or organ tissue. The afferent signal is the sensation that transmits the state of peripheral body parts to the brain. The motor control architectures of biological systems have hierarchical structures in which the efferent/afferent signals interact. Thanks to this architecture, flexible and reflective action is realized. In this paper, we propose a hierarchical control architecture for high-speed visual servoing on the basis of a biological signal interaction model. The proposed architecture has three modules: servo, motion planner and adaptation. The afferent signal corresponds to the feedback signal from the sensors; the efferent signal corresponds to the motion command. These signals interact in a hierarchical manner that realize a parameter adaptation mechanism. A series of dynamical tasks, tracking/grasping/handling of a moving object, is implemented as an example of high-speed visual servoing. The system contains a DSP network, high-speed active vision, dextrous hand and a seven-degrees-of-freedom manipulator Real-time experiments are conducted and the results exhibit the responsiveness and flexibility of the proposed hierarchical architecture.

This paper discusses the capturing robot with the maximum acceleration of 100 G in design specification. We find the combination of the arm with the mass of 0.1 kg and the spring capable of producing the initial compressed force of 100 N, so that we can achieve the 100 G. In order to reduce the total capturing time, we newly propose the arm/gripper coupling mechanism (AGCM) where the spring energy initially accumulated in the arm is transferred to the kinetic energy of the arm and continuously to the kinetic energy for closing the gripper at the capturing point without any time lag. The experimental results show the maximum acceleration of 91 G and the capturing time of 25 ms. Experiments on capturing a dropping ball are also executed with the assistance of the I ms-vison.

強化学習における割引率を学習進度によって調整することの有用性を示す.学習進度が浅いときには割引率を下げて即時報酬を重視し,学習が進むにつれて次第に割引率を大きくして,将来の報酬も考慮していくという戦略を提案する.また,学習進度の調整法として,指数的調整,TD誤差による調整,信頼度による調整を提案する.これをwindy gridworld 課題により検証する.

Research attempting to merge human and mechanical systems through a nervous system is one of the most dynamic fields in interface technology. Recently, artificial cochlear and retinal nerves were connected via a nervous system. However, there has been no report concerning the replacement of human tactile sensation by artificial sensors connected to the tactile sensory nerve system. The present study reports the development of a system which enables the touch strength applied to a robot hand to be sensed and applied to the hand of a human operator via the microstimulation method. The operator controls the grasping action of a robot hand equipped with tactile sensors at a remote location via a network. The contact information between an object and the robot hand is transmitted via the network, and the tactile sensory nerve of the operator is stimulated by a microelectrode. The force applied to the robot hand can be sensed as a applied force to the hand of the human operator. Applications of the proposed system include the presentation of tactile perception in remote manipulation. In addition, the proposed system is an effective method for transmitting sensation from artificial limbs. The present paper describes the experimental system and results.

In this paper we introduce a newly developed high-speed multi-fingered robotic hand. The hand has 8-joints and 3-fingers. A newly developed small harmonic drive gear and a high-power mini actuator are fitted in each finger link, and a strain gauge sensor is in each joint. The weight of the hand module is only 0.8kg, but high-speed motion and high-power grasping are possible. The hand can close its joints at 180deg per 0.1s, and the fingertips have an output force of about 28N. The hand system is controlled by a massively parallel vision system. Experimental results are shown in which a falling object was caught by the highspeed hand.

約0.1秒で開閉を行う能力を持つ高速動作可能な3本指ロボットハンドが開発されている。これをサンプリングタイム1[kHz]の高速視覚フィードバックで制御することで, 落下球を捕球するタスクを実現した。本発表では, その把握戦略と実験結果について述べる。

動的な操り動作を実現することを目標として, 指の開閉を約0.1秒で実行する能力を持つ3本指ロボットハンドを開発した。開発したハンドは全8自由度を持ち, 多様を把握形態をとることが可能であり, また軽量であるためにロボットアームに搭載可能である。本発表では, 開発したロボットハンドの設計方針について述べ, その性能評価報告を行う。

本発表では, 視覚から得た対象の運動からロボットの運動指令へのマッピングアルゴリズムを提案する。提案したアルゴリズムをロボットマニピュレータの捕球動作に応用し, その有効性を示す。

A new type of tactile sensor using pressure conductive rubber with electrical-wires stitches method was presented. The sensor is thin and flexible. In order to verify the effectiveness of tactile sensor, grasping sphere and column using robot hand which is equipped with tactile sensor was experimented. The sensor structure and characteristics were described. The sensor control system and experimental results were also described. Moreover, a trial as an example of application that transfer tactile sense information detected by this tactile sensor through the nerve system of a human's arm was presented.

In this paper a new high-speed vision device and its application to a grasp system is proposed, and we discuss a processing architecture for grasping based on visual and tactile feedback designed with real-time control in mind. First, we describe a high-speed vision chip that serves as a robotic eye that includes a general-purpose parallel processing array along with a photo-detector all on a single silicon chip. Next, we present a grasping algorithm based on real-time visual and tactile feedback, and a high-speed sensory-motor fusion system for robotic grasping. We then describe a grasping experiment using high-speed vision, and finally, based on these results, the effectiveness of high-speed sensory-motor fusion for robotic grasping is discussed.

In this paper grasping of a dynamically moving object is achieved using high-speed visual and force feedback. First a hierarchical processing model based on high-speed sensory feedback to realize manipulation in a changing environment is proposed. In this model high-speed sensory feedback is used at hierarchical three stages: (1) servo control, (2) motion planning, and (3) switching of motion planners. Because the motion planners are switched according to an external environment at a high rate, responsiveness and flexibility to dynamic changes of the environment is achieved. Next based on t...

This paper discusses a design concept of a sensory-motor fusion system to achieve high performance in a dynamic changing environment. From the viewpoint of a dynamic system, the new concept called "dynamics matching" is proposed to match the dynamics constraints of a system. Based on this concept, we will describe a high-speed vision chip that has a general purpose parallel processing array along with a photodetector all in a single silicon chip. Next we will describe a new sensory-motor fusion system which consists of a hierarchical parallel processing system, a vision chip system, and a multifingered hand-arm. All sensory feedback, including visual feedback, can be achieved in I ms. In addition, as an application of the system, we will demonstrate high-speed grasping using visual and force feedback.

神経系を介して生体系と機械系を一体化しようとする試みは, 医用生体工学の中でも最も注目を浴びている領域の一つである。しかしながら, いまだ世界において実際に遠隔地にある外部機器と生体の感覚神経を接続し, 人工感覚を生成するシステムを作成した報告は全く見あたらない。本研究では, 遠隔地にあるロボットハンドを被験者がネットワーク経由で操作を行い, ハンドと対象物との接触情報を, 再度ネットワーク経由で被験者の触感覚神経を刺激することで, ハンドに加えられた感覚刺激を自分の手に感覚が加えられたものとして感じる事を可能とするシステムを開発し, 実験に成功した。本報告ではこの実験システムに関して報告する

従来のロボットハンドは精密さと器用さに重点をおいて作られていたために鈍重なものが多く, 人間の手腕のように素早い動作や動的な操りを行うのは難しかった。本研究では, アームの上に載せて動的な操りを行うロボットハンドを実現するために, 瞬時に大出力が発生できる高速・軽量アクチュエータと軽量な2自由度指モジュールを開発した。結果として, 180度を0.1秒で開閉する高速な動作を実現することができた。

A hierarchical control architecture is proposed on the basis of an interaction model between efferent and afferent information in brain motor control. The model has five levels: motoneurons, premotor interneurons, pattern generator, parameter selection and action planning. The effectors including biophysical properties receive the commands from motoneurons. In the proposed architecture, the premotor interneurons and motoneurons are implemented as a servo module; the pattern generator corresponds to the motion planner; and the parameter selection is realized by adaptation module. The afferent information is the feedback signal and the efferent information corresponds motion command and parameter adaptation. Grasping and handling of a dynamically moving object are implemented on a DSP network with a high-speed vision, a dextrous hand and a 7 DOF manipulator. The results show responsive and flexible actions that exhibit the effectiveness of the proposed hierarchical modular structure.

人間やロボットなどにおける感覚運動統合において, ダイナミクス整合という概念を提起する. これは有限の計算資源やハードウェアの物理的特性や制御系の制約, タスクの内容といった拘束条件の下で, 情報処理系や制御系の時間的な特性, すなわちダイナミクスを適応的・能動的に調整することによって, システム全体としてのパフォーマンスの最大化を実現するという考えである. 本稿ではこの問題に対する一つのアプローチとして, パフォーマンスを報酬とした強化学習を用いることにより具体的なアルゴリズムを構成し, ターゲットトラッキングを例題とした数値実験によりその効果を検証した.

To achieve robotic manipulation tasks in the real world in which there are dynamic changes in an environment, we have developed a high-speed sensory-motor fusion system consisting of a multiprocessor system, a massively parallel active vision, and a multifingered hand-arm. This 1-ms sensory-motor fusion system has the following three features: 1) 1-ms high-speed visual and force feedback to deal with changes in the real world environment; 2) heterogeneous sensor fusion to process a multiple environments; and 3) hierarchical parallel processing architecture to perform multiple tasks. These features allow dynamic motion in the real-world environment.