• International Journal of Fuzzy Logic and Intelligent Systems
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• 제15권1호
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• pp.12-19
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• 2015

In order to guide the robots move along a collision-free path efficiently and reach the goal position quickly in the unknown multi-obstacle environment, this paper presented the navigation problem of a wheel mobile robot based on proximity sensors by fuzzy logic controller. Then a genetic algorithm was applied to optimize the membership function of input and output variables and the rule base of the fuzzy controller. Here the environment is unknown for the robot and contains various types of obstacles. The robot should detect the surrounding information by its own sensors only. For the special condition of path deadlock problem, a wall following method named angle compensation method was also developed here. The simulation results showed a good performance for navigation problem of mobile robots.

• 한국정밀공학회지
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• 제20권11호
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• pp.79-90
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• 2003

In this paper, we propose a multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using multi-ultrasonic sensor. Instead of using “sensor fusion” method which generates the trajectory of a robot based upon the environment model and sensory data, “command fusion” method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as experiments with IRL-2002. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• 한국산업융합학회 논문집
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• 제21권3호
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• pp.125-131
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• 2018

In this paper, we propose a homogeneous multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments with moving obstacles using multi-ultrasonic sensor. Instead of using "sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data, "command fusion" method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as real experiments with mobile robot, AmigoBot. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.252-254
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• 2005

Completer coverage path planning requires the robot path to cover every part of the workspace, which is an essential issue in cleaning robots and many other robotic applications such as vacuum robots and painter robots. In this paper, a novel Water Flowing Algorithm (WFA) is proposed for cleaning robots to complete coverage path planning in unknown environment without obstacles. The robot covers the whole workspace just like that water fills up a container. First the robot goes to the lowest point in the workspace just like water flows to the bottom of the container. At last the robot will come to highest point in the workspace just like water overflows from the container and simultaneously the robot has covered the whole workspace. The computer simulation results show that the proposed algorithm enable the robot to plan complete coverage paths.

• Journal of Advanced Marine Engineering and Technology
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• 제32권1호
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• pp.192-199
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• 2008

In order for a mobile robot to move under unknown or uncertain environment. it is very important to collect environmental information. This paper suggests a traveling algorithm which leads to the map building algorithm and the $A^*$ algorithm under the assumption that environmental information should already be collected. In order to apply the proposed traveling algorithm to a real mobile robot. this paper additionally discusses a path amendment algorithm. For the purpose of verifying the proposed algorithms, several simulations are executed based on a UI host program-based simulation interface and an experiment is executed using a mobile robot under a real unknown environment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.25-28
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• 1999

In this article, a new performance index is proposed to re-duce the collision impulsive force by controlling the null motion of redundant manipulators. First, we define the normalized impact ellipsoid in the viewpoint of instantaneous velocity change. Then, we propose a new impact performance index based on velocity direction for null motion to reduce initial impulsive effects. It gives some advantage for the case of unknown environment. The optimization of this index is that the successional impact forces are reduced. The performance of the proposed index is demonstrated by simulation study.

• Journal of Mechanical Science and Technology
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• 제14권10호
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• pp.1081-1088
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• 2000

In this paper, a compliance control strategy for robot manipulators that employs a self-adjusting stiffiness function is proposed. Based on the contact force, each entry of the diagonal stiffness matrix corresponding to a task coordinate in the operational space is adaptively adjusted during contact along the corresponding axis. The proposed method can be used for both the unconstrained and constrained motions without any switching mechanism which often causes undesirable instability and/or vibrational motion of the end-effector. The experimental results involving a two-link direct drive manipulator interacting with an unknown environment demonstrates the effectiveness of the proposed method.

• 대한임베디드공학회논문지
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• 제13권2호
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• pp.53-63
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• 2018

A novel real-time path planning algorithm suitable for implementation on a small mobile robot is introduced. The algorithm can be used as the basis for mapping unknown or partially known environments and is tested in a specially developed simulation environment in Matlab(R). Simulations results are presented demonstrating that the algorithm can readily be implemented to allow a small robot to navigate in various unknown and partially known environments. The main characteristics of the algorithm include simplicity, ease of implementation, speed, and efficiency, thereby being especially suitable for small robots. Furthermore, for partially known environments, another algorithm is proposed to predefine an optimal path taking into account information provided regarding the environment.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2840-2842
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• 2000

This paper describes sensor-based occupancy grid map construction method through complete coverage navigation algorithm in unknown environment. In this paper, we use the updated Baysian model for probabilistic grid map. For map construction, complete coverage navigation method in which mobile robot can navigate complete field through as short path as possible in unknown environment, is used. The computer simulations result show that map construction method using complete coverage algorithm is efficient.

• 한국대기환경학회지
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• 제15권6호
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• pp.703-712
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• 1999

In order to determine the number concentration of asbestos, it is initially necessary to develop a method to identify the type of asbestos. Thus a SEM/EDX was used to obtain both physical and chemical information from known asbestos samples as reference samples. Based on these information, we could make a source profile matrix consisted of a glass fiber and 3 other types of asbestos such as chrysotile, crocidolite, and tremolite. After collinearity test was performed for these sources, we could successfully develop an expert system by C-language to separate and to identify various unknown types of fiber particles. The expert system was perfectly self-verified with original reference data. Then the program was extensively applied to survey indoor and outdoor environment such as a residential area, an elementary school, and underground store, and an auto junkyard. As a result for surveying, a total of 442 individual fibrous particles were well classified into 4 types of particle classes above mentioned; 5.4% of chrysotile, 4.1% of crocidolite, 3.6% of glass fiber, and 86.9% of unknown fibers in terms of number concentration. However, tremolite was not detected in the study sites. All the samples were satisfied with the recommendation level of 0.01 f/cc.