• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.639-644
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• 2003

An unstructured environment requires a robot to possess outstanding mobility and advanced control algorithms since there exist complicated configurations such as obstacle, uneven surface, etc. Especially, when a quadruped robot walks in these environments, obstacles in the walking route will obstruct the walking or may give rise to a serious trouble. In this paper, we introduce a strategy for the stable walking in unstructured environment. The proposed strategy consists of two control algorithms. One is a collision{free algorithm to avoid obstacles and the other is an algorithm to overcome any obstacle. These are based on the obstacle detection method and a shape reconstruction algorithm, Which algorithms are described in detail. In addition, the validity of these algorithms have been demonstrated through experiments using a quadruped walking robot called "MRWALLSPECT III(Multifunctional Robot for Wall inSPECTion version 3 )".

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.3
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• pp.67-75
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• 1998

This paper presents a new robot motion planning method for moving obstacle avoidance. To consider the mobility of a moving obstacle, we define virtual distance function(VDF) between the robot and the obstacle. At each sampling time, we use the VDF to construct an artificial potential, considering the motion of obstacles. The robot moves according to the repulsive and attractive force vector induced by the artificial potential function. The proposed algorithm can be driven the robot to avoid moving obstacles in real time. Some simulation studies show the effectiveness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.2
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• pp.97-103
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• 2016

In this paper, a smartphone-controlled personal mobility system (PMS) with semi-autonomous navigation is developed. The proposed PMS moves to waypoints and then reaches the destination where the waypoints and destination are selected by the user using Google maps in a smartphone. The hardware environment consists of a GPS (Global Positioning System) in the smartphone and a compass sensor. In addtion, while it is moving in autonomous mode, the user can intervene and change the direction and speed of the PMS in order to avoid obstacles that may be encountered accidentally in a dynamic environment. That is why it is called "semi-autonomous navigation". Experimental results showed that the proposed PMS is effectively able to migrate to the waypoints and destination in both autonomous and manual modes.

• ETRI Journal
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• v.45 no.5
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• pp.758-767
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• 2023

In this study, we introduce a loosely coupled relative position estimation method that utilizes a decentralized ultrawideband (UWB), Global Navigation Support System and inertial navigation system for flight controllers (FCs). Key obstacles to multidrone collaboration include relative position errors and the absence of communication devices. To address this, we provide an extended Kalman filter-based algorithm and module that correct distance errors by fusing UWB data acquired through random communications. Via simulations, we confirm the feasibility of the algorithm and verify its distance error correction performance according to the amount of communications. Real-world tests confirm the algorithm's effectiveness on FCs and the potential for multidrone collaboration in real environments. This method can be used to correct relative multidrone positions during collaborative transportation and simultaneous localization and mapping applications.

• The Journal of Korea Robotics Society
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• v.11 no.2
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• pp.83-91
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• 2016

Most of outdoor mobile robots have a suspension on each wheel in order to relieve the shock by ground obstacles and to improve the driving stability. Typically, in the actual operations, the suspensions have been used under a given set of conditions as all the damping and spring coefficients of the suspensions are fixed. However, it is necessary to readjust the coefficients of the suspensions according to surface conditions that may cause the unstable shaking of a robot body at high speed driving. Therefore, this paper is focused on the mobility analysis of an outdoor robot when the coefficients of suspensions (in particular, damping coefficients) are changed while driving on an uneven road surface. In this paper, a semi-active suspension with twelve damping coefficient levels was used and a small sized vehicle with the suspensions was employed to analyze the mobility dependent on a change of the damping coefficient. And the mobility was evaluated through driving experiments on a bumped slope.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.156-168
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• 2017

Personal mobility (PM) can increase the mobility of individual, so that the elderly can be set as the target group for using PM because of relatively low walking ability to normal. In this study, we design PM device for elderly that can be used safely in the walking environment such as sidewalk. There are various obstacles in the walking environment, so the device must have mechanical performance to overcome all of them. In this study, we survey the status and level of obstacle factors in walking environment to determine the dynamic performance of the PM device for elderly. We check up several guidelines about walking facilities to define obstacle points for the device, establish field survey methodologies, and conduct field survey for some specific road sections. Based on the survey results, we confirm the possible problems that could arise when the dynamic performance of the device is selected based on the facility-related criteria. We also define the performance requirements for the device based on the requirements for electric wheelchair.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.166-172
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• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.119-125
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• 2023

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.331-339
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• 2008

Nowadays with advancement in technology and aging society, the number of disabled citizens is increasing. The disabled citizens always need a caretaker for daily life routines especially for mobility. In future, the need is considered to increase more. To reduce the burden from the disabled, various devices for healthcare are introduced using computer technology. The power wheelchair is an important and convenient mobility device. The demand of power wheelchair is increasing for assistance in mobility. In this paper we proposed a robotic wheelchair for mobility aid to reduce the burden from the disabled. The main issue in an autonomous wheelchair is the automatic detection and avoidance of obstacles and going to the pre-designated place. The proposed algorithm detects the obstacles and avoids them to drive the wheelchair to the desired place safely. By this way, the disabled will not always have to worry about paying deep attention to the surroundings and his path. User has a handheld bio-sensor monitoring system for get user's bio-signal. If user detects unusual signal, alarm send to protector.

• Tunnel and Underground Space
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• v.34 no.1
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• pp.1-14
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• 2024

An image-reconstruction technology, involving the deployment of an unmanned mobility equipped with high-speed LiDAR (Light Detection And Ranging) has been proposed to reconstruct the shape of abandoned mine. Unmanned mobility operation is remarkably useful in abandoned mines fraught with operational difficulties including, but not limited to, obstacles, sludge, underwater and narrow tunnel with the diameter of 1.5 m or more. For cases of real abandoned mines, quadruped robots, quadcopter drones and underwater drones are respectively deployed on land, air, and water-filled sites. In addition to the advantage of scanning the abandoned mines with 2D solid-state lidar sensors, rotation of radiation at an inclination angle offers an increased efficiency for simultaneous reconstruction of mineshaft shapes and detecting obstacles. Sensor and robot posture were used for computing rotation matrices that helped compute geographical coordinates of the solid-state lidar data. Next, the quadruped robot scanned the actual site to reconstruct tunnel shape. Lastly, the optimal elements necessary to increase utility in actual fields were found and proposed.