• Title/Summary/Keyword: human-like motion

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Human-like Arm Movement Planning for Humanoid Robots Using Motion Capture Database (모션캡쳐 데이터베이스를 이용한 인간형 로봇의 인간다운 팔 움직임 계획)

  • Kim, Seung-Su;Kim, Chang-Hwan;Park, Jong-Hyeon;You, Bum-Jae
    • The Journal of Korea Robotics Society
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    • v.1 no.2
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    • pp.188-196
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    • 2006
  • During the communication and interaction with a human using motions or gestures, a humanoid robot needs not only to look like a human but also to behave like a human to make sure the meanings of the motions or gestures. Among various human-like behaviors, arm motions of the humanoid robot are essential for the communication with people through motions. In this work, a mathematical representation for characterizing human arm motions is first proposed. The human arm motions are characterized by the elbow elevation angle which is determined using the position and orientation of human hands. That representation is mathematically obtained using an approximation tool, Response Surface Method (RSM). Then a method to generate human-like arm motions in real time using the proposed representation is presented. The proposed method was evaluated to generate human-like arm motions when the humanoid robot was asked to move its arms from a point to another point including the rotation of its hand. The example motion was performed using the KIST humanoid robot, MAHRU.

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Face and Hand Activity Detection Based on Haar Wavelet and Background Updating Algorithm

  • Shang, Yiting;Lee, Eung-Joo
    • Journal of Korea Multimedia Society
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    • v.14 no.8
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    • pp.992-999
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    • 2011
  • This paper proposed a human body posture recognition program based on haar-like feature and hand activity detection. Its distinguishing features are the combination of face detection and motion detection. Firstly, the program uses the haar-like feature face detection to receive the location of human face. The haar-like feature is provided with the advantages of speed. It means the less amount of calculation the haar-like feature can exclude a large number of interference, and it can discriminate human face more accurately, and achieve the face position. Then the program uses the frame subtraction to achieve the position of human body motion. This method is provided with good performance of the motion detection. Afterwards, the program recognises the human body motion by calculating the relationship of the face position with the position of human body motion contour. By the test, we know that the recognition rate of this algorithm is more than 92%. The results show that, this algorithm can achieve the result quickly, and guarantee the exactitude of the result.

Generation Human -like Arm Motion to Catch a Moving Object

  • Kwon, Oh-Kyu;Park, Poo-Gyeon
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.161.5-161
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    • 2001
  • Robots are required to assist our activities in daily life. In this paper, we focus on arm movement to catch moving object as one of important tasks frequently performed by human. We propose an algorithm which enables a robot to perform human-like arm motion to catch a moving object. First we analyze human hand trajectories and velocity profiles to catch an object. From the experimental results, we extract some characteristics in the process of approaching and following a moving object and confirm that these are necessary to realize human-like motion. We then adopt an instantaneous optimal control method which evaluates the error and energy cost at each sampling step, and design two time-varying weight matrices to introduce human characteristic into robot motion. The matrix concerning the error is defined as a time-increasing ...

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A Joint Motion Planning Based on a Bio-Mimetic Approach for Human-like Finger Motion

  • Kim Byoung-Ho
    • International Journal of Control, Automation, and Systems
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    • v.4 no.2
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    • pp.217-226
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    • 2006
  • Grasping and manipulation by hands can be considered as one of inevitable functions to achieve the performances desired in humanoid operations. When a humanoid robot manipulates an object by his hands, each finger should be well-controlled to accomplish a precise manipulation of the object grasped. So, the trajectory of each joint required for a precise finger motion is fundamentally necessary to be planned stably. In this sense, this paper proposes an effective joint motion planning method for humanoid fingers. The proposed method newly employs a bio-mimetic concept for joint motion planning. A suitable model that describes an interphalangeal coordination in a human finger is suggested and incorporated into the proposed joint motion planning method. The feature of the proposed method is illustrated by simulation results. As a result, the proposed method is useful for a facilitative finger motion. It can be applied to improve the control performance of humanoid fingers or prosthetic fingers.

Human-like Whole Body Motion Generation of Humanoid Based on Simplified Human Model (단순인체모델 기반 휴머노이드의 인간형 전신동작 생성)

  • Kim, Chang-Hwan;Kim, Seung-Su;Ra, Syung-Kwon;You, Bum-Jae
    • The Journal of Korea Robotics Society
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    • v.3 no.4
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    • pp.287-299
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    • 2008
  • People have expected a humanoid robot to move as naturally as a human being does. The natural movements of humanoid robot may provide people with safer physical services and communicate with persons through motions more correctly. This work presented a methodology to generate the natural motions for a humanoid robot, which are converted from human motion capture data. The methodology produces not only kinematically mapped motions but dynamically mapped ones. The kinematical mapping reflects the human-likeness in the converted motions, while the dynamical mapping could ensure the movement stability of whole body motions of a humanoid robot. The methodology consists of three processes: (a) Human modeling, (b) Kinematic mapping and (c) Dynamic mapping. The human modeling based on optimization gives the ZMP (Zero Moment Point) and COM (Center of Mass) time trajectories of an actor. Those trajectories are modified for a humanoid robot through the kinematic mapping. In addition to modifying the ZMP and COM trajectories, the lower body (pelvis and legs) motion of the actor is then scaled kinematically and converted to the motion available to the humanoid robot considering dynamical aspects. The KIST humanoid robot, Mahru, imitated a dancing motion to evaluate the methodology, showing the good agreement in the motion.

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A Study on Characteristics of Inter-Articular Coordination of Human Fingers for Robotic Hands (로봇 손을 위한 인간 손가락의 관절간 운동특성 고찰)

  • Kim Byoung-Ho
    • Journal of the Korean Society for Precision Engineering
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    • v.23 no.7 s.184
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    • pp.67-75
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    • 2006
  • One of challenging topics for humanoid hands is to modulate a human-like motion of humanoid fingers handling an object. To this end, recognizing the motion behavior of human fingers is very important aspect. Based on this concept, this paper identifies the .joint trajectories of human fingers for an operation of hand opening and closing, and specifies an empirical model that coordinates an inter-articular relationship of human fingers doing the given motion. It is expected that the inter-articular model presented in this paper is applicable for humanoid fingers to mimic the natural motion of human fingers.

Motion Imitation Learning and Real-time Movement Generation of Humanoid Using Evolutionary Algorithm (진화 알고리즘을 사용한 인간형 로봇의 동작 모방 학습 및 실시간 동작 생성)

  • Park, Ga-Lam;Ra, Syung-Kwon;Kim, Chang-Hwan;Song, Jae-Bok
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.10
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    • pp.1038-1046
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    • 2008
  • This paper presents a framework to generate human-like movements of a humanoid in real time using the movement primitive database of a human. The framework consists of two processes: 1) the offline motion imitation learning based on an Evolutionary Algorithm and 2) the online motion generation of a humanoid using the database updated bγ the motion imitation teaming. For the offline process, the initial database contains the kinetic characteristics of a human, since it is full of human's captured motions. The database then develops through the proposed framework of motion teaming based on an Evolutionary Algorithm, having the kinetic characteristics of a humanoid in aspect of minimal torque or joint jerk. The humanoid generates human-like movements far a given purpose in real time by linearly interpolating the primitive motions in the developed database. The movement of catching a ball was examined in simulation.

A Gait Implementation of a Biped Robot Based on Intelligent Algorithm (지능 알고리즘 기반의 이족 보행로봇의 보행 구현)

  • Kang Chan-Soo;Kim Jin-Geol;Noh Kyung-Kon
    • Journal of Institute of Control, Robotics and Systems
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    • v.10 no.12
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    • pp.1210-1216
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    • 2004
  • This paper deals with a human-like gait generation of a biped robot with a balancing weight of an inverted pendulum type by using genetic algorithm. The ZMP (Zero Moment Point) is the most important index in a biped robot's dynamic walking stability. To perform a stable walking of a biped robot, a balancing motion is required according to legs' trajectories and a desired ZMP trajectory. A dynamic equation of the balancing motion is nonlinear due to an inverted pendulum type's balancing weight. To solve the nonlinear equation by the FDM (Finite Difference Method), a linearized model of equation is proposed. And GA (Genetic Algorithm) is applied to optimize a human-like balancing motion of a biped robot. By genetic algorithm, the index of the balancing motion is efficiently optimized, and a dynamic walking stability is verified by the ZMP verification equation. These balancing motion are simulated and experimented with a real biped robot IWR-IV. This human-like gait generation will be applied to a humanoid robot, at future work.

An Interactive Interface for Rapid Motion Modification of an Articulated Object Model with Multiple Joints and Its Application to Kendo Coaching

  • Naoya, Yokoyama;Ishimatzu, T.
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.46.2-46
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    • 2001
  • A method of interactive human interface for motion modification of an articulated object model like a human body, a multiple joints robot, etc. has been developed, and implemented to a human body motion model. In the case of computer software models, the initial data setting for overall motion is rather easy. However, modifying or correcting the initially set motion is rather difficult for keeping consistency. In this research, the requirements shown below have mainly been set as the specifications ...

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Kinesiology Based Human-like Walking Pattern Design for a Bipedal Robot (인체운동학에 기반한 이족로봇의 인간형 걸음새 설계)

  • Park, Jin-Hee;Kwon, Sang-Joo
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.7
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    • pp.659-667
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    • 2011
  • The study of bipedal robot is towards similar shape and function with human. In this paper, we propose a human-like walking pattern compatible to the flexible foot with toe and heel structure. The new walking pattern for a bipedal robot consists of ZMP, center of mass (CoM), and ankle trajectory and is drawn by considering human kinesiology. First, the ZMP trajectory moves forward without stopping at a point even in the single support phase. The corresponding CoM trajectory to the ZMP one is derived by solving differential equations. As well, a CoM trajectory for the vertical axis is added by following the idea of human motion. The ankle trajectory closely mimics the rotational motion of human ankles during taking off and landing on the ground. The advantages of the proposed walking pattern are demonstrated by showing improved stability, decreased ankle torque, and the longer step length capability. Specifically, it is interesting to know that the vertical CoM motion is able to compensate for the initial transient response.