간행물

로봇학회논문지 KCI 등재 The Journal of Korea Robotics Society

권호리스트/논문검색
이 간행물 논문 검색

권호

제13권 제4호 (통권 제50호) (2018년 12월) 8

1.
2018.12 서비스 종료(열람 제한)
This paper deals with the paddle type end of arm tool for rescue robot instead of rescue worker in dangerous environments such as fire, earthquake, national disaster and defense. It is equipped at the dual arm manipulator of the rescue robot to safely lift up an injured person. It consists of the paddle for lifting person, sensors for detecting insertion of person onto the paddle, sensor for measuring the tilting angle of the paddle, and mechanical compliance part for preventing incidental injuries. The electronics is comprised of the DAQ module to acquire the sensors data, the control module to treat the sensors data and to manage the errors, and the communication module to transmit the sensors data. After optimally designing the mechanical and electronical parts, we successfully made the paddle type end of arm tool and evaluated its performance by using specially designed jigs. The developed paddle type end of arm tool is going to be applied to the rescue robot for performance verification through field testing.
2.
2018.12 서비스 종료(열람 제한)
In this paper, we introduce a target position reasoning system based on Bayesian network that selects destinations of robots on a map to explore compound disaster environments. Compound disaster accidents have hazardous conditions because of a low visibility and a high temperature. Before firefighters enter the environment, the robots notify information in advance, such as victim’s positions, number of victims, and status of debris of building. The problem of the previous system is that the system requires a target position to operate the robots and the firefighter need to learn how to use the robot. However, selecting the target position is not easy because of the information gap between eyewitness accounts and map coordinates. In addition, learning the technique how to use the robots needs a lot of time and money. The proposed system infers the target area using Bayesian network and selects proper x, y coordinates on the map based on image processing methods of the map. To verify the proposed system, we designed three example scenarios based on eyewetinees testimonies and compared time consumption between human and the system. In addition, we evaluate the system usability by 40 subjects.
3.
2018.12 서비스 종료(열람 제한)
In the midst of disaster, such as an earthquake or a nuclear radiation exposure area, there are huge risks to send human crews. Many robotic researchers have studied to send UGVs in order to replace human crews at dangerous environments. So far, two-dimensional camera information has been widely used for teleoperation of UGVs. Recently, three-dimensional information based teleoperations are attempted to compensate the limitations of camera information based teleoperation. In this paper, the 3D map information of indoor and outdoor environments reconstructed in real-time is utilized in the UGV teleoperation. Further, we apply the LTE communication technology to endure the stability of the teleoperation even under the deteriorate environment. The proposed teleoperation system is performed at explosive disposal missions and their feasibilities could be verified through completion of that missions using the UGV with the Explosive Ordnance Disposal (EOD) team of Busan Port Security Corporation.
4.
2018.12 서비스 종료(열람 제한)
3D depth perception has played an important role in robotics, and many sensory methods have also proposed for it. As a photodetector for 3D sensing, single photon avalanche diode (SPAD) is suggested due to sensitivity and accuracy. We have researched for applying a SPAD chip in our fusion system of time-of-fight (ToF) sensor and stereo camera. Our goal is to upsample of SPAD resolution using RGB stereo camera. Currently, we have 64 x 32 resolution SPAD ToF Sensor, even though there are higher resolution depth sensors such as Kinect V2 and Cube-Eye. This may be a weak point of our system, however we exploit this gap using a transition of idea. A convolution neural network (CNN) is designed to upsample our low resolution depth map using the data of the higher resolution depth as label data. Then, the upsampled depth data using CNN and stereo camera depth data are fused using semi-global matching (SGM) algorithm. We proposed simplified fusion method created for the embedded system.
5.
2018.12 서비스 종료(열람 제한)
In this paper, we describe a sensor module that monitors fire environment by analyzing fire characteristics. We analyzed the smoke characteristics of indoor fire. Six different environments were defined according to the type of smoke and the flame, and the sensors available for each environment were combined. Based on this analysis, the sensors were selected from the perspective of firefighter. The sensor module consists of an RGB camera, an infrared camera and a radar. It is designed with minimum weight to fit on the robot. the enclosure of sensor is designed to protect against the radiant heat of the fire scene. We propose a single camera mode, thermal stereo mode, data fusion mode, and radar mode that can be used depending on the fire scene. Thermal stereo was effectively refined using an image segmentation algorithm, SLIC (Simple Linear Iterative Clustering). In order to reproduce the fire scene, three fire test environments were built and each sensor was verified.
6.
2018.12 서비스 종료(열람 제한)
In this paper, a design for a vehicle body of an armored robot for complex disasters is described. The proposed design considers various requirements in complex disaster situations. Fire, explosion, and poisonous gas may occur simultaneously under those sites. Therefore, the armored robot needs a vehicle body that can protect people from falling objects, high temperature, and poisonous gas. In addition, it should provide intuitive control devices and realistic surrounding views to help the operator respond to emergent situations. To fulfill these requirements of the vehicle body, firstly, the frame was designed to withstand the impact of falling objects. Secondly, the positive pressure device and the cooling device were applied. Thirdly, a panoramic view was implemented that enables real-time observation of surroundings through a number of image sensors. Finally, the cockpit in the vehicle body was designed focused on the manipulability of the armored robot in disaster sites.
7.
2018.12 서비스 종료(열람 제한)
Unlike normal wheels, the Mecanum wheel enables omni-directional movement regardless of the orientation of a mobile robot. In this paper, a robust trajectory tracking control method is developed based on the dynamic model of the Mecanum wheel mobile robot in order that the mobile robot can move along the given path in the environment with disturbance. The method is designed using the impedance control to make the mobile robot to track the path, and the integral sliding mode control for robustness to disturbance. The good performance of the proposed method is verified using the MATLAB /Simulink simulation and also through the experiment on an actual Mecanum wheel mobile robot. In both the simulation and the experimentation, we make the mobile robot move along a reference trajectory while maintaining the robot's orientation at a constant angle to see the characteristics of the Mecanum wheel.
8.
2018.12 서비스 종료(열람 제한)
The recent prosthetic technologies pursue to control multi-DOFs (degrees-of-freedom) hand and wrist. However, challenges such as high cost, wear-ability, and motion intent recognition for feedback control still remain for the use in daily living activities. The paper proposes a multi-channel knit band sensor to worn easily for surface EMG-based prosthetic control. The knitted electrodes were fabricated with conductive yarn, and the band except the electrodes are knitted using non-conductive yarn which has moisture wicking property. Two types of the knit bands are fabricated such as sixteen-electrodes for eight-channels and thirty-two electrodes for sixteen-channels. In order to substantiate the performance of the biopotential signal acquisition, several experiments are conducted. Signal to noise ratio (SNR) value of the knit band sensor was 18.48 dB. According to various forearm motions including hand and wrist, sixteen-channels EMG signals could be clearly distinguishable. In addition, the pattern recognition performance to control myoelectric prosthesis was verified in that overall classification accuracy of the RMS (root mean squares) filtered EMG signals (97.84%) was higher than that of the raw EMG signals (87.06%).