대학생의 무도스포츠 참여기피요인이 장애요인 및 극복에 미치는 영향

박수근 ( Park Su-geun ),김인재 ( Kim In-jae ) 대한무도학회 2016 대한무도학회지 Vol.18 No.4

본 연구는 대학생의 무도스포츠 참여기피요인이 장애요인 및 극복에 미치는 영향을 실증적으로 규명하는데 연구의 목적이 있다. 연구 대상은 대전광역시에 소재하고 있는 대학교를 재학 중인 대학생 편의표본추출법으로 353명의 자료를 대상으로 분석에 이용하였다. 설문지의 작성은 자기평가기입 법으로 작성하도록 하였으며, 회수된 설문지의 자료처리는 각 응답 내용을 코드화 한 후 Windows용 한글 SPSS version 18.0을 이용하여 요인분석, 신뢰도분석, 빈도분석, 상관관계분석, 다중회귀분석을 실시하였다. 위와 같은 절차 및 자료 분석을 통하여 얻어진 결론은 다음과 같다. 첫째, 무도스포츠의 참여기피요인과 장애요인 간에는 변인간 정(+)의 상관관계를 보이고 있으며, 극복요인는 부(-)의 상관관계를 보이고 있다. 참여기피요인이 높을수록 장애요인은 높으며, 참여기피요인, 장애요인이 높을수록 극복요인은 낮아진다. 둘째, 무도스포츠 참여기피요인과 장애요인의 관계를 분석한 결과 힘듦, 흥미는 시간장애에 영향을 미치며 흥미, 시설, 타인의식은 개인장애에 영향을 미친다. 또한 힘듦, 타인의식, 흥미는 사회장애에 영향을 미치며, 흥미, 타인의식, 시설은 경제장애에 미친다. 셋째, 무도스포츠 참여기피요인과 극복의 관계를 분석한 결과 흥미, 체력은 에너지 충전에 부적 영향을 미치며, 흥미, 체력은 동반자 탐색에 부적 영향을 미친다. 또한, 흥미, 체력은 인식변화에 부적영향을 미치며, 흥미, 힘듦은 자신감에 부적영향을 미친다. 넷째, 무도스포츠 장애요인과 극복의 관계를 분석한 결과 개인장애, 시간장애는 에너지충전에 부적 영향을 미치며, 개인장애는 동반자탐색에 부적영향을 미친다. 시간장애는 인식변화에 부적영향을 미치며, 시간장애, 개인장애는 자신감에 부적영향을 미친다. The purpose of this study is to empirically identify The Influence of Overcoming an Obstacle Factors with Martial arts Participation Avoidance Factors of College Students. To achieve this objective, subjects were chosen among college students enrolled in universities located in Daejeon metropolitan city. Once they are set as the population, subjects are recruited using the convenience sampling method. In the process of collecting data, 47 subjects` answers with insincere data and missing columns are excluded and a total of 353 subjects` data are used for analysis in this study. Self-administered questionnaire was used. After contents of each question are coded, factor analysis, reliability analysis, frequency analysis, correlation analysis and simple regression analysis are performed by using Hangeul SPSS version 18.0 for Windows. Through the above process and data analysis, the results are obtained as follows. First, a positive (+) correlation between martial arts participation avoidance factor and obstacle factor is shown, but overcoming factor shows a negative correlation. Obstacle factor is higher with higher participation avoidance factor, but overcoming factor is lower with higher participation avoidance factor and obstacle factor. Second, as a result of analysis on relationships between martial arts participation avoidance factor and obstacle factor, interest factors of martial arts participation avoidance factor affect time obstacle, individual obstacle, society obstacle and economic obstacle in order. Difficulty factor affects time obstacle and society obstacle in order. Other`s awareness factor affects individual obstacle, society obstacle and economic obstacle in order. Facility factor affects individual obstacle and economic obstacle in order. Third, as a result of analysis on relationships between martial arts participation avoidance factor and overcoming, energy charge, partner exploration and awareness change affect the interest and physical strength among martial arts participation avoidance factors. Awareness change affects only awareness of other and facility factor. Fourth, as a result of analysis on relationships between obstacle factor and overcoming, energy charge, partner exploration, awareness change and self-confidence affect individual obstacle and time obstacle. Partner exploration affects society obstacle. A study on the relationship among the service recovery fairness, training satisfaction and trust and training behavior of Hapkido gymnasium

A New Approach to Moving Obstacle Avoidance Problem of a Mobile Robot

Ko, Nak Yong,Choi, Jung-Sang 한국공작기계학회 1998 한국생산제조학회지 Vol.7 No.1

This paper presents a new solution approach to moving obstacle avoidance problem of a mobile robot. A new concept avoidability measure(AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between. As an AVM, virtual distance function(VDF) is derived as a function of the distance from the obstacle to the robot and outward speed of the obstacle relative to the robot. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terms of the VDF, an artificial potential field is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived from the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid moving obstacles in real time. Since the algorithm considers the mobility of the obstacle as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.

Intelligent Obstacle Avoidance Control Strategy for Wheeled Mobile Robot

Yen-Sheng Chen,Jih-Gau Juang 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8

This paper presents intelligent strategies for a wheeled mobile robot to avoid obstacle and move to target location. The obstacle detection for the wheeled mobile robot is carried out by ultrasonic sensors. There are two models in this study, short-distance obstacle avoidance model and target-driven obstacle avoidance model. In short-distance obstacle avoidance model, the wheeled mobile robot utilizes signals of the ultrasonic sensors to avoid obstacle. Intarget-driven obstacle avoidance model, fuzzy theory with sensor signals is used to control the speed of the wheeledmobile robot and make it move to target location. In this study, software simulations are made on the MATLABplatform. Both obstacle avoidance models are successfully performed.

이동로봇의 동적장애물 회피를 위한 가변 포텐셜장 설계

김동헌(Dong Hun Kim) 제어로봇시스템학회 2021 제어·로봇·시스템학회 논문지 Vol.27 No.3

This paper presents the design of a variable potential field for dynamic obstacle avoidance by mobile robots. In this scheme, the RPF (Repulsive Potential Field) for obstacle avoidance has a different magnitude in each direction based on the angle between a goal and an obstacle, unlike a conventional RPF in which the magnitude is the same in each direction. Conventional potential field designs for path planning use scaling parameters of the potential field as fixed values. Therefore, the local minimum problem occurs because of which the robot cannot reach its destination. This is because of the obstacle in the approach to the destination due to repulsive forces in all directions around the potential field. Similarly, studies on existing potential field designs for avoiding dynamic obstacles have used methods such as fixed obstacles by designing only the location of the dynamic obstacles in the current step. Therefore, a collision is inevitable when the dynamic obstacle moves faster than the robot. Thus, in this study, the scaling parameters of the RPF were designed using variable values depending on the locations of the obstacle and destination. In addition, a new field design was developed for obstacle avoidance considering the speeds of dynamic obstacles. The experimental results proved that a potential field could be effectively designed for avoiding dynamic obstacles and those near the destination.

Implementation of Obstacle Avoidance and Target Following based on Machine Learning for Unmanned Aerial Vehicle At Low Altitude

( Yu-hung Lin ),( Tzu-fang Lai ),( Po-yen Lin ),( Tse-min Chen ) 한국농업기계학회 2018 한국농업기계학회 학술발표논문집 Vol.23 No.1

This research developed an integrated system that consist of orientation sensing, balance control, machine vision recognition and shape sorting and avoidance of obstacle with which the UVA will meet the requirement of a low altitude shuttle in orchards and forest. This research also focused on employing machine learning as the main control core to achieve the performances of target following and obstacle avoidance for unmanned aerial vehicle (UAV). In order to keep the balance of a quadcopter, the orientation data from gyroscope and accelerometer will be the inputs of a double loop PID controller. Target is recognized by machine vision. Distances and shapes of obstacles are defined by a laser rangefinder that mounted on the vehicle. The control of UAV depending on the shape of the obstacle, execute different obstacle avoidance strategies. The results of experiment indicated that the complementary filter can compensate the defects of the gyroscope and accelerometer since it fixes steady-state error of gyroscope and oscillation in high frequency of accelerometer. Double-loop PID controller is more stable than single-loop PID controller is. Due to the stability of control board and safety of operators in target following and obstacle avoidance experiment, a three wheels omni robot was employed to conduct the performance evaluation. The final results validate that the novel UAV is equipped with the ability of shuttling among orchards in low-altitude, target following, classification of obstacle shape and obstacle avoidance.

이중 심층 Q 네트워크 기반 장애물 회피 경로 계획

자오 용지앙(Yongjiang Zhao),첸센폰(Senfeng Cen),성승제(Seung-Je Seong),허정규(J. G. Hur),임창균(Chang-Gyoon Lim) 한국전자통신학회 2023 한국전자통신학회 논문지 Vol.18 No.2

심층 강화 학습(Deep Reinforcement Learning)을 사용한 경로 계획에서 장애물을 자동으로 회피하기 위해 로봇을 학습시키는 일은 쉬운 일이 아니다. 많은 연구자가 DRL을 사용하여 주어진 환경에서 로봇 학습을 통해 장애물 회피하여 경로 계획을 수립하려는 가능성을 시도하였다. 그러나 다양한 환경에서 로봇과 장착된 센서의 오는 다양한 요인 때문에 주어진 시나리오에서 로봇이 모든 장애물을 완전히 회피하여 이동하는 것을 실현하는 일은 흔치 않다. 이러한 문제 해결의 가능성과 장애물을 회피 경로 계획 실험을 위해 테스트베드를 만들었고 로봇에 카메라를 장착하였다. 이 로봇의 목표는 가능한 한 빨리 벽과 장애물을 피해 시작점에서 끝점까지 도달하는 것이다. 본 논문에서는 벽과 장애물을 회피하기 위한 DRL의 가능성을 검증하기 위해 이중 심층 Q 네트워크(DDQN)를 제안하였다. 실험에 사용된 로봇은 Jetbot이며 자동화된 경로 계획에서 장애물 회피가 필요한 일부 로봇 작업 시나리오에 적용할 수 있을 것이다. It remains a challenge for robots to learn avoiding obstacles automatically in path planning using deep reinforcement learning (DRL). More and more researchers use DRL to train a robot in a simulated environment and verify the possibility of DRL to achieve automatic obstacle avoidance. Due to the influence factors of different environments robots and sensors, it is rare to realize automatic obstacle avoidance of robots in real scenarios. In order to learn automatic path planning by avoiding obstacles in the actual scene we designed a simple Testbed with the wall and the obstacle and had a camera on the robot. The robot's goal is to get from the start point to the end point without hitting the wall as soon as possible. For the robot to learn to avoid the wall and obstacle we propose to use the double deep Q networks (DDQN) to verify the possibility of DRL in automatic obstacle avoidance. In the experiment the robot used is Jetbot, and it can be applied to some robot task scenarios that require obstacle avoidance in automated path planning.

A Novel Approach to Coupling Terms to Avoid Obstacles in a Manipulator Movement Reproduction

Byung Su Kim,Min Cheol Lee 제어·로봇·시스템학회 2024 International Journal of Control, Automation, and Vol.22 No.4

Many people have attempted to generate specific movements based on the concept that neural networks in the brain and spinal cord create multiple sets of temporal templates. Dynamic movement primitives (DMPs) are inspired by the motion control of biological systems and can be mathematically represented as stable nonlinear dynamic systems in the form of motion primitives. One way to improve the work efficiency of robots in various industries is to leverage the ability of DMPs to generalize learned trajectories to enable them to perform a wider range of tasks. This study discusses obstacle avoidance techniques using DMPs and proposes a novel approach to obstacle avoidance. DMPs have the ability to generalize and have extensions that make them valuable in generalizing in unforeseen situations. Obstacle avoidance in DMPs has been approached in various ways, with previous research utilizing potential field methods as typical obstacle avoidance techniques. We added a formulated coupling term to DMPs to avoid obstacles. This novel approach proposes modeling obstacles as point clouds, objects surrounded by bounding boxes or smooth standard shapes, and adding a new coupling term to smoothly avoid obstacles without disrupting the existing reference movement’s topology while closely following a reference trajectory. This study also discusses the determination of the magnitude and direction of a desired repelling force against obstacles. Overall, this study discusses obstacle avoidance techniques using DMPs and introduces a novel approach that improves obstacle avoidance in DMPs. The goal of this study is to confirm the effectiveness of the proposed approach by implementing previous and newly proposed algorithms for semi-elliptical trajectories and applying them to robot manipulators.

PATH PLANNING AND PATH TRACKING FOR AUTONOMOUS VEHICLE BASED ON MPC WITH ADAPTIVE DUAL-HORIZON-PARAMETERS

Yaohua Li,Jikang Fan,Yang Liu,Xiaoyu Wang 한국자동차공학회 2022 International journal of automotive technology Vol.23 No.5

According to the position relationship between the vehicle and the obstacle, a new obstacle avoidance path planner was designed to solve the limitation of traditional local obstacle avoidance path planner in excessive obstacle avoidance. In order to improve the control accuracy of the path tracking controller and ensure the stability of the vehicle, a comprehensive evaluation index of path tracking performance considering control accuracy and driving stability was established. The optimal prediction time domain and control time domain parameters at different vehicle speeds were obtained, and an adaptive dual time domain parameter path tracking controller was designed. Based on the joint-simulation platform, the integrated structure of the planning layer and the control layer was simulated and verified. Simulation results show that the new obstacle avoidance function can avoid excessive obstacle avoidance while ensuring real-time performance, and improve the driving stability of the vehicle. The adaptive time-domain parameter path tracking controller has better comprehensive control performance and can improve driving safety under extreme conditions. The integrated structure of local obstacle avoidance path planning and path tracking control are beneficial for the vehicle to plan and accurately track the local obstacle avoidance path in multiple static obstacle scenes.

Autonomous Navigation of an Underwater Robot in the Presence of Multiple Moving Obstacles

Kyoung-Youb Kwon,Joongseon Joh 한국지능시스템학회 2005 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.5 No.2

Obstacle avoidance of underwater robots based on a modified virtual force field algorithm is proposed in this paper. The VFF(Virtual Force Field) algorithm, which is widely used in the field of mobile robots, is modified for application to the obstacle avoidance of underwater robots. This Modified Virtual Force Field(MVFF) algorithm using the fuzzy lgoc can be used in moving obstacles avoidance. A fuzzy algorithm is devised to handle various situations which can be faced during autonomous navigation of underwater robots. The proposed obstacle avoidance algorithm has ability to handle multiple moving obstacles. Results of simulation show that the proposed algorithm can be efficiently applied to obstacle avoidance of the underwater robots.

Autonomous Navigation of an Underwater Robot in the Presence of Multiple Moving Obstacles

Kwon, Kyoung-Youb,Joh, Joong-Seon Korean Institute of Intelligent Systems 2005 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.5 No.2

Obstacle avoidance of underwater robots based on a modified virtual force field algorithm is proposed in this paper. The VFF(Virtual Force Field) algorithm, which is widely used in the field of mobile robots, is modified for application to the obstacle avoidance of underwater robots. This Modified Virtual Force Field(MVFF) algorithm using the fuzzy lgoc can be used in moving obstacles avoidance. A fuzzy algorithm is devised to handle various situations which can be faced during autonomous navigation of underwater robots. The proposed obstacle avoidance algorithm has ability to handle multiple moving obstacles. Results of simulation show that the proposed algorithm can be efficiently applied to obstacle avoidance of the underwater robots.