• Journal of Institute of Control, Robotics and Systems
• /
• v.7 no.6
• /
• pp.532-539
• /
• 2001

In robot teleoperation, much research has been carried out to control the slave robot from remote site. One of the essential devices for robot teleoperation is the masterarm, which is a path command generating device worn on human arm. In this paper, a new masterarm based on human kinematics is proposed. Its controller is based on the distributed controller architecture composed of two controller parts: a host controller and a set of satellite controllers. Each satellite controller measures the corresponding joint angle, while the host controller performs forward and inverse kinematics calculation. This distributed controller architecture can make the data updating faster, which allows to implement real-time implementation. The host controller and the satellited controllers are networked via three-wire daisy-chained SPI(Serial Peripheral Interface) protocol, so this architecture makes the electrical wiring very simple, and enhances maintenance. Analytical method for finding three additional unknown joint angles is derived using only three measured angles for each shoulder and wrist, which makes th hardware implementation very simple by minimizing the required number of satellite controllers. Finally, the simulation and experiment results are given to demonstrate the usefulness and performance of the proposed masterarm.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.2051-2056
• /
• 2003

In this paper, a tele-manipulation in explosive ordnance disposal(EOD) applications is discussed. The ROBHAZ-DT2 is developed as a teleoperated mobile manipulator for EOD. In general, it has been thought that the robot must have appropriate functions and accuracy enough to handle the complicated and dangerous mission. However, the research on the ROBHAZ-DT2 revealed that the teleoperation causes more restrictions and difficulties in EOD mission. Thus to solve the problem, a novel user interface for the ROBHAZ-DT2 is developed, in which the operator can interact with various human senses (i.e. visual, auditory and haptic sense). It enables an operator to control the ROBHAZ-DT2 simply and intuitively. A tele-manipulation control scheme for the ROBHAZ-DT2 is also proposed including compliance control via force feedback. It makes the robot adapt itself to circumstances, while the robot faithfully follows a command of the operator. This paper deals with a detailed description on the user interface and the tele-manipulation control for the ROBHAZ-DT2. An EOD demonstration is conducted to verify the validity of the proposed interface and the control scheme.

• The Journal of Korea Robotics Society
• /
• v.3 no.3
• /
• pp.226-236
• /
• 2008

In this paper, control software architecture is designed to enable a heterogeneous multiple humanoid robot demonstration executing tasks cooperating with each other. In the heterogeneous humanoid robot team, one large humanoid robot and two small humanoid robots are included. For the efficient and reliable information sharing between many software components for humanoid control, sensing and planning, CORBA based software framework is applied. The humanoid tasks are given in terms of finite state diagram based human-robot interface, which is interpreted into the XML based languages defining the details of the humanoid mission. A state transition is triggered based on the event which is described in terms of conditions on the sensor measurements such as robot locations and the external vision system. In the demonstration of the heterogeneous humanoid team, the task of multiple humanoid cleaning the table is given to the humanoid robots and successfully executed based on the given state diagram.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2001.04a
• /
• pp.182-187
• /
• 2001

This study deals with CARS (Computer Aided ROMUM System) which is a computer version of ROMUM (RObot Modularization of the Unit Motion). ROMUM was a method developed by the concept of modularization of the unit motion of robots. Because CARS is a computer assisted method of menu-driven type for human interface, this method can be easily applied for analyzing the work motion and measuring the execution time of robots. Therefore, it will be helpful for reducing the analysis effort and time of robot work.

• Journal of the Korea Convergence Society
• /
• v.11 no.4
• /
• pp.17-25
• /
• 2020

This study focuses on the analysis of the service process and interaction mode of the serving robot used in the restaurant, Through user research, shadowing research and indepth interviews with customers and catering service personnel, this paper analyzes the contact points between catering service machines, people and users, constructs user journey map to understand users' expectations. In addition to the delivery service that can be allocated to the machine and people, the blueprint construction of ordering, reception and table cleaning services can also included in the service process. The final proposal is to improve the existing machine human interface and design a new service scheme.

• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.11
• /
• pp.904-911
• /
• 2016

This paper presents a novel driving system by the humanoid robot to drive a vehicle in disaster response situations. To enhance robot's capability for substituting human activities in responding to natural and man-made disaster, the one of prerequisite skills for the rescue robot is the mounted mobility to maneuver a vehicle safely in disaster site. Therefore, our driving system for the humanoid is developed in order to steer a vehicle through unknown obstacles even under poor communication conditions such as time-delay and black-out. Especially, the proposed system includes a tele-manipulation interface and stable navigation strategies. First, we propose a new type of path estimation method to overcome limited communication. Second, we establish navigation strategies when the operator cannot recognize obstacles based on Dynamic Window Approach. The effectiveness of the proposed developments is verified through simulation and experiments, which demonstrate suitable system for driving a vehicle in disaster response.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.1541-1544
• /
• 1997

The rehailitation robot, one of the service robot, is the important area in the service automation. In the paper, we describe the overall configuration of KARES(KAIST Rehabilitation Engineering System), which is an intellingent rehabilitaion robotic system designed to assist the independent livelihood of the handicapped and the eldrly. KARES consists of the 6 degree of freedom robot arm mounted on a wheelchair, the controller ofr the arm, sensors to perceive environment, and user interface. Basic desired hobs in KARES are gripping the target object and moving it to the user's face for eating, drinking, or cooperation work wiht the mouth. Currently, the manual operation of the arm is available for gripping to target objects. The autonomous functionality will be ginven for the facilities of the human operator.

• Journal of Intelligence and Information Systems
• /
• v.17 no.1
• /
• pp.53-69
• /
• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.628-632
• /
• 2003

An intelligent miniature humanoid robot system is designed and implemented as a platform for researching walking algorithm. The robot system consists of a mechanical robot body, a control system, a sensor system, and a human interface system. The robot has 6 dofs per leg, 3 dofs per arm, and 2 dofs for a neck, so it has total of 20 dofs to have dexterous motion capability. For the control system, a supervisory controller runs on a remote host computer to plan high level robot actions based on the vision sensor data, a main controller implemented with a DSP chip generates walking trajectories for the robot to perform the commanded action, and an auxiliary controller implemented with an FPGA chip controls 20 actuators. The robot has three types of sensors. A two-axis acceleration sensor and eight force sensing resistors for acquiring information on walking status of the robot, and a color CCD camera for acquiring information on the surroundings. As an example of an intelligent robot action, some experiments on playing soccer are performed.

• Journal of the Korean Society for Precision Engineering
• /
• v.30 no.6
• /
• pp.650-657
• /
• 2013

This study uses a muscle activation sensor and elbow joint model to develop an estimation algorithm for human elbow joint torque for use in a human-robot interface. A modular-type MVS (Muscle Volume Sensor) and calibration algorithm are developed to measure the muscle activation signal, which is represented through the normalization of the calibrated signal of the MVS. A Hill-type model is applied to the muscle activation signal and the kinematic model of the muscle can be used to estimate the joint torques. Experiments were performed to evaluate the performance of the proposed algorithm by isotonic contraction motion using the KIN-COM$^{(R)}$ equipment at 5, 10, and 15Nm. The algorithm and its feasibility for use as a human-robot interface are verified by comparing the joint load condition and the torque estimated by the algorithm.