• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.3
• /
• pp.206-212
• /
• 2015

This paper proposes the physical human-robot interaction method that controls the robot arms using ITO touch panel sensor as the skin of robot. To implement physical human-robot interaction, the method of using the force/torque sensor and the method of using tactile sensor created by arranging small element type of sensor have been studied. However, these sensors have the pros and cons in terms of price and performance. This study aims to demonstrate the economy of element type sensor and the accuracy of force/torque sensor through experiment by proposing the method of physical interaction using the touch panel as the skin of robot, and by constructing overall system. The experiment was carried out for the method of controlling the robot arm by installing end-effecter and the method of controlling robot arm by creating the gesture with reference point on the touch panel. Through this experiment, the possibility of teaching control using the touch panel was confirmed.

• The Journal of Korea Robotics Society
• /
• v.17 no.3
• /
• pp.322-333
• /
• 2022

The Avatar robot, which is one of the teleoperation robots, aims to enable users to feel the robot as a part of the body to intuitively and naturally perform various tasks. Considering the purpose of the avatar robot, an end-effector identical to a human hand is advantageous, but a robotic hand with human hand level performance has not yet been developed. In this paper we propose a new 3-finger robotic hand with human-avatar hand posture mapping algorithm which were integrated with TOCABI-AVATAR, one of the teleoperation system. Due to the flexible rolling contact joints and tendon driven mechanism applied to the finger, the finger could implement adaptive grasping and absorb the impact force caused by unexpected contacts. In addition, human-avatar hand mapping algorithm using five calibration hand postures propose to compensate physical differences between operators. Using the TOCABI-AVATAR system with the robotic hands and mapping algorithm, the operator can perform 13 out of 16 hand postures of grasping taxonomy and 4 gestures. In addition, using the system, we participated in the ANA AVATAR XPRIZE Semi-final and successfully performed three scenarios which including various social interactions as well as object manipulation.

• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.5
• /
• pp.404-414
• /
• 2000

This paper addresses the development of a 3-fingered humanoid robot hand system and a real-time grasp synthesis of multifingered robot hands to find grasp configurations which satisfy the force closure condition of arbitrary shaped objects. We propose a fast and efficient grasp synthesis algorithm for planar polygonal objects, which yields the contact locations on a given polygonal object to obtain a force closure grasp by the multifingered robot hand. For an optimum grasp and real-time computation, we develop the preference and the hibernation process and assign physical constraints of the humanoid hand to the motion of each finger. The preferences consist of each sublayer reflecting the primitive preference similar to the conditional behaviors of humans for given objectives and their arrangements are adjusted by the heuristics inspired from human's grasping behaviors. The proposed method reduces the computational time significantly at the sacrifice of global optimality, and enables the grasp posture to be changable within two-finger and three-finger grasps. The performance of the presented algorithm is evaluated via simulation studies to obtain the force-closure grasps of polygonal objects with fingertip grasps. The architecture suggested is verified through experimental implementation to our robot hand system by solving the 2- or 3-finger grasp synthesis.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.12
• /
• pp.129-137
• /
• 2013

As the usage of computer based systems continues to increase in our normal life, there are constant efforts to enhance the accessibility of information for handicapped people. For this, it is essential to develop new interface ways for physical disabled peoples by means of human-computer interface (HCI) or human-machine interface (HMI). In this paper, we developed HMI using electromyogram (EMG) and electrooculogram (EOG) for people with physical disabilities. Developed system is composed of two modules, hardware module for signal sensing and software module for feature extraction and pattern classification. To maximize ease of use, only two skin contact electrodes are attached on both ends of brow, and EOG and EMG are measured simultaneously through these two electrodes. From measured signal, nine kinds of command patterns are extracted and defined using signal processing and pattern classification method. Through Java based real-time monitoring program, developed system showed 92.52% of command recognition rate. In addition, to show the capability of the developed system on real applications, five different types of commands are used to control ER1 robot. The results show that developed system can be applied to disabled person with quadriplegia as a novel interface way.