• International Journal of Fuzzy Logic and Intelligent Systems
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• 제7권2호
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• pp.138-142
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• 2007

This paper presents an algorithm which extends the rapidly-exploring random tree (RRT) framework to deal with change of the task environments. This algorithm called the Retrieval RRT Strategy (RRS) combines a support vector machine (SVM) and RRT and plans the robot motion in the presence of the change of the surrounding environment. This algorithm consists of two levels. At the first level, the SVM is built and selects a proper path from the bank of RRTs for a given environment. At the second level, a real path is planned by the RRT planners for the: given environment. The suggested method is applied to the control of $KUKA^{TM}$, a commercial 6 DOF robot manipulator, and its feasibility and efficiency are demonstrated via the cosimulatation of $MatLab^{TM}\;and\;RecurDyn^{TM}$.

• 로봇학회논문지
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• 제7권2호
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• pp.150-159
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• 2012

In this paper, we propose a cost-aware Rapidly-exploring Random Tree (RRT) path planning algorithm for mobile robots. A mobile robot is presented with a cost map of the field of interest and assigned to move from one location to another. As a robot moves, the robot is penalized by the cost at its current location according to the cost map. The overall cost of the robot is determined by the trajectory of the robot. The goal of the proposed cost-aware RRT algorithm is to find a trajectory with the minimal cost. The cost map of the field can represent environmental parameters, such as temperature, humidity, chemical concentration, wireless signal strength, and stealthiness. For example, if the cost map represents packet drop rates at different locations, the minimum cost path between two locations is the path with the best possible communication, which is desirable when a robot operates under the environment with weak wireless signals. The proposed cost-aware RRT algorithm extends the basic RRT algorithm by considering the cost map when extending a motion segment. We show that the proposed algorithm gives an outstanding performance compared to the basic RRT method. We also demonstrate that the use of rejection sampling can give better results through extensive simulation.

• 대한수의학회지
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• 제15권1호
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• pp.93-99
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• 1975

In order to compare the diagnostic value of Modified California Mastitis Test (MCMT), Modified Whiteside Test (MWT) and Resazurin Reduction Test (RRT) using the direct microscopic leucocyte count (DMLC) as standard, a total of 739 quarter milk samples were examined. The results obtained were as follows: 1. Of the 739 samples, 24.4% had positive DMLC value (over 500,000 leucocytes per mI.), 32.6% positive MCMT reaction, 34.9% positive RRT reaction and 39.9% positive MWT reaction. 2. The identical ratings of the three mastitis screening tests with DMLC values were 60.7% (MWT), 61. 8% (MCMT) and 72.1% (RRT). 3. The mean reaction values of the predicted mastitis screening tests were $1.09{\pm}0.01$ (MWT), $1.12{\pm}0.06$ (MCMT) and $1.25{\pm}0.40$ (RRT). The efficiency ratings of them were 34.8% (MWT), 49.3% (RRT) and 55.0% (MCMT) respectively.

• 제어로봇시스템학회논문지
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• 제22권3호
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• pp.217-225
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• 2016

In this paper, we propose an improved path planning method and obstacle avoidance algorithm for two-wheel mobile robots, which can be effectively applied in an environment where obstacles can be represented by circles. Firstly, we briefly introduce the rapidly exploring random tree (RRT) and single polar polynomial (SPP) algorithm. Secondly, we present additional two methods for applying our proposed method. Thirdly, we propose a global path planning, smoothing and obstacle avoidance method that combines the RRT and SPP algorithms. Finally, we present a simulation using our proposed method and check the feasibility. This shows that proposed method is better than existing methods in terms of the optimality of the trajectory and the satisfaction of the kinematic constraints.

• 비파괴검사학회지
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• 제29권3호
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• pp.256-263
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• 2009

After several PWSCCs were found in Bugey(France), Ringhals(Sweden), Tihange(Belgium), Oconee, Arkansas, Crystal Fever, Davis-Basse, VC Summer(U.S.A.), Thuruga(Japan), USNRC and PNNL started the research on PWSCC, that is, the PINC project. USNRC required KINS to participate in the PINC project in May 2005. KINS organized the Korean consortium at March 2006 and Pre-RRT for RVHP were performed for the preparation of PINC RRT. Through these preliminary RRT, Korea NDE teams can learn and develop the detection and sizing technique for RVHP dissimilar metal weld. These techniques are now being prepared in Korea and need to be utilized for the In-service inspection of the RVHP and BMI of Korea Nuclear Power Plants. PINC RRT mock-ups will be helpful to training.

• Nuclear Engineering and Technology
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• 제51권3호
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• pp.825-836
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• 2019

One of the most challenging safety precautions for workers in dynamic, radioactive environments is avoiding radiation sources and sustaining low exposure. This paper presents a sampling-based algorithm, DL-RRT*, for minimum dose walk-path re-planning in radioactive environments, expedient for occupational workers in nuclear facilities to avoid unnecessary radiation exposure. The method combines the principle of random tree star ($RRT^*$) and $D^*$ Lite, and uses the expansion strength of grid search strategy from $D^*$ Lite to quickly find a high-quality initial path to accelerate convergence rate in $RRT^*$. The algorithm inherits probabilistic completeness and asymptotic optimality from $RRT^*$ to refine the existing paths continually by sampling the search-graph obtained from the grid search process. It can not only be applied to continuous cost spaces, but also make full use of the last planning information to avoid global re-planning, so as to improve the efficiency of path planning in frequently changing environments. The effectiveness and superiority of the proposed method was verified by simulating radiation field under varying obstacles and radioactive environments, and the results were compared with $RRT^*$ algorithm output.

• 한국항공우주학회지
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• 제50권11호
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• pp.809-817
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• 2022

무인 로봇과 UAV의 발달로 경로 계획 알고리즘의 필요성이 높아지고 있으며 다양한 환경에서 잘 작동하는 RRT^* 알고리즘이 여러 분야에서 유용하게 활용되고 있다. RRT^* 알고리즘에 다양한 변형을 통해 더 좋은 경로를 생성하기 위한 많은 연구가 진행되고 있으며, 이러한 노력 덕분에 알고리즘의 성능 향상은 거듭되는 중이다. 본 논문은 이러한 연구의 연장선에서 샘플링 범위의 제한을 이용하여 효율적인 경로를 생성하는 방법을 제안한다. 장애물이 있는 환경에서 경로가 장애물에 근접할수록 최적의 경로에 가까워진다는 발상에 근거하여 더 짧은 경로를 얻기 위해 장애물 근처에 노드를 생성한다. 또한 경로가 장애물을 휘감는 경우 변경된 재연결 방법을 통해 빠르게 직선화된 경로를 얻는다. 기존의 알고리즘과 제안하는 방법을 비교 분석하여 성능을 검증하고, 무인항공기의 운동학 모델을 도입하여 생성된 경로를 추적할 수 있음을 확인한다.

• 응용통계연구
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• 제28권1호
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• pp.75-82
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• 2015

본 연구에서는 민감한 이항특성에 대한 신뢰구간 추정에 직접질문법과 간접질문법을 사용한다. 간접질문법으로 응답자들의 응답부담을 줄여주기 위해서 확률장치를 사용하는 Warner (1965)의 확률화응답기법(RRT)을 고려한다. 두 방법에 의한 신뢰구간을 비교하기 위해서 평가기준으로 평균포함확률(MCP), 평균제곱오차의 제곱근(RMSE), 그리고 평균기대폭(MEW)을 사용한다. 수치적 비교 결과 RRT의 MCP가 명목수준()을 크게 초과하여 보수적이고 MEW도 매우 크다. 따라서 이들을 보완해 주어야 실제적으로 간접질문법의 유용성을 높일 수 있다.

• 비파괴검사학회지
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• 제29권3호
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• pp.248-255
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• 2009

After several damages by PWSCC were found in the world, USNRC and PNNL(Pacific Northwest National Laboratory) started the research on PWSCC under the project name of PINC. The aim of the project was 1) to fabricate representative NDE mock-ups with flaws to simulate PWSCCs, 2) to identify and quantitatively assess NDE methods for accurately detecting, sizing and characterizing PWSCCs, 3) to document the range of locations and morphologies of PWSCCs and 4) to incorporate results with other results of ongoing PWSCC research programs, as appropriate. Korea nuclear industries have also been participating in the project. Thermally and mechanically cracked-four mockups were prepared and phased array and manual ultrasonic testing(UT) techniques were applied. The results and lessons learned from the preliminary RRT are summarized as follows: 1) Korea RRT teams performed the RRT successfully. 2) Crack detection probability of the participating organizations was an average 87%, 80% and 80% respectively. 3) RMS error of the crack sizing showed comparatively good results. 4) The lessons learned may be helpful to perform the PINC RRT and PSI /ISI in Korea in the future.

• 한국항행학회논문지
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• 제27권4호
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• pp.365-373
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• 2023

무인 항공기는 다양한 분야에서 널리 활용되고 있으며, 실시간 경로 재계획은 이들 기기의 안전성과 효율성을 향상하는 핵심 요소이다. 본 논문에서는 RRT*와 LOSPO를 기반으로 한 실시간 경로 재계획 기법을 제안한다. 제안된 기법은 먼저 RRT* 알고리즘을 활용하여 초기 경로를 생성하고, LOSPO를 이용하여 경로를 최적화한다. 또한 최적화된 경로를 궤적으로 변경하여 실제 시간과 항공기의 동적한계를 고려할 수 있다. 이 과정에서 환경 변화와 충돌 위험을 실시간으로 감지하고, 필요한 경우 경로를 재계획함으로써 안전한 운행을 유지한다. 이 방법은 시뮬레이션을 통한 실험을 통해 검증되었다. 본 논문의 결과는 무인 항공기의 실시간 경로 재계획에 관한 연구에 중요한 기여할 것으로 기대한다. 또한 이 기법을 다양한 상황에 적용함으로써 무인 항공기의 안전성과 효율성을 향상시킬 수 있다.