• Title/Summary/Keyword: compliant grasping

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Strength and Stiffness Analysis for a Flexible Gripper with Parallel Pinching and Compliant Grasping Capabilities (순응형 파지와 정밀한 집기가 가능한 유연한 그리퍼의 강도 및 강성 분석)

  • Lee, Deok Won;Jeon, Hyeong Seok;Jeong, Young Jun;Kim, Yong Jae
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.10
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    • pp.817-825
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    • 2016
  • In this paper, we introduce a flexible gripper that we have engineered to precisely pinch in parallel and compliantly grasp objects. As found in most conventional industrial grippers, the parallel pinching property is essential for precise manipulation. On the other hand, the grippers with a flexible structure are more adept at grasping objects with arbitrary shapes and softness. To achieve these disparate properties, we introduce a flexible gripper mechanism composed of multiple flexible beam structures. Utilizing these beam structures, the proposed gripper is able to grasp arbitrarily shaped objects. Additionally, a unique combination of flexible beams enables the gripper to pinch objects using the parallel fingertips for enhanced precision. A detailed description of the proposed mechanism is provided, and an analysis of the strength and stiffness of the fingertip and finger body is presented. The Results section compares the theoretical and experimental analyses and verifies the properties and performance of the proposed gripper.

Development of a 16 DOF Anthropomorphic Robot Hand with Back-Drivability Joint for Stable Grasping (안정 파지를 위한 16자유도 역구동 관절을 가지는 인간형 로봇 손 개발)

  • Yang, Hyun-Dae;Park, Sung-Woo;Park, Jae-Han;Bae, Ji-Hun;Baeg, Moon-Hong
    • The Journal of Korea Robotics Society
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    • v.6 no.3
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    • pp.220-229
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    • 2011
  • This paper focuses on a development of an anthropomorphic robot hand. Human hand is able to dexterously grasp and manipulate various objects with not accurate and sufficient, but inaccurate and scarce information of target objects. In order to realize the ability of human hand, we develop a robot hand and introduce a control scheme for stable grasping by using only kinematic information. The developed anthropomorphic robot hand, KITECH Hand, has one thumb and three fingers. Each of them has 4 DOF and a soft hemispherical finger tip for flexible opposition and rolling on object surfaces. In addition to a thumb and finger, it has a palm module composed the non-slip pad to prevent slip phenomena between the object and palm. The introduced control scheme is a quitely simple based on the principle of virtual work, which consists of transposed Jacobian, joint angular position, and velocity obtained by joint angle measurements. During interaction between the robot hand and an object, the developed robot hand shows compliant grasping motions by the back-drivable characteristics of equipped actuator modules. To validate the feasibility of the developed robot hand and introduced control scheme, collective experiments are carried out with the developed robot hand, KITECH Hand.

Development of Flexible and Lightweight Robotic Hand with Tensegrity-Based Joint Structure for Functional Prosthesis (기능형 의수를 위한 텐스그리티 관절 구조 기반의 유연하고 가벼운 로봇 핸드 개발)

  • Geon Lee;Youngjin Choi
    • The Journal of Korea Robotics Society
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    • v.19 no.1
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    • pp.1-7
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    • 2024
  • This paper presents an under-actuated robotic hand inspired by the ligamentous structure of the human hand for a prosthetic application. The joint mechanisms are based on the concept of a tensegrity structure formed by elastic strings. These rigid bodies and elastic strings in the mechanism emulate the phalanx bones and primary ligaments found in human finger joints. As a result, the proposed hand inherently possesses compliant characteristics, ensuring robust adaptability during grasping and when interacting with physical environments. For the practical implementation of the tensegrity-based joint mechanism, we detail the installation of the strings and the routing of the driving tendon, which are related to extension and flexion, respectively. Additionally, we have designed the palm structure of the proposed hand to facilitate opposition and tripod grips between the fingers and thumb, taking into account the transverse arch of the human palm. In conclusion, we tested a prototype of the proposed hand to evaluate its motion and grasping capabilities.

Force Control of Robot Fingers using Series Elastic Actuators (직렬 탄성 액츄에이터 기반의 로봇 손가락의 힘 제어)

  • Lee, Seung-Yup;Kim, Byeong-Sang;Song, Jae-Bok;Chae, Soo-Won
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.10
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    • pp.964-969
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    • 2012
  • Robot hands capable of grasping or handling various objects are important for service robots to effectively aid humans. In particular, controlling a contact force and providing a compliant motion are essential when the hand is in contact with objects. Many dexterous robot hands equipped with force/torque sensors have been developed to perform force control, but they suffer from the complexity of control and high cost. In this paper, a low-cost robot hand based on SEA (Series Elastic Actuator), which is composed of compression spring, stretch sensor, and wire, is proposed. The grasping force can be estimated by measuring the compression length of spring, which would allow the hand to perform force control. A series of experimentations are carried out to verify the performance of force control of the proposed robot hand, and it is shown that it can successfully control the contact force without any additional force/torque sensors.

A Study on Real Time Control of Moving Stuff Action Through Iterative Learning for Mobile-Manipulator System

  • Kim, Sang-Hyun;Kim, Du-Beum;Kim, Hui-Jin;Im, O-Duck;Han, Sung-Hyun
    • Journal of the Korean Society of Industry Convergence
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    • v.22 no.4
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    • pp.415-425
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    • 2019
  • This study proposes a new approach to control Moving Stuff Action Through Iterative Learning robot with dual arm for smart factory. When robot moves object with dual arm, not only position of each hand but also contact force at surface of an object should be considered. However, it is not easy to determine every parameters for planning trajectory of the an object and grasping object concerning about variety compliant environment. On the other hand, human knows how to move an object gracefully by using eyes and feel of hands which means that robot could learn position and force from human demonstration so that robot can use learned task at variety case. This paper suggest a way how to learn dynamic equation which concern about both of position and path.