• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.248-249
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• 2013

This study presents a potential field method for path planning to goal with a mobile robot in unknown environment. The proposed algorithm allows mobile robot to navigate through static obstacles, and find the path in order to reach the target without collision. This algorithm provides the robot with the possibility to move from the initial position to the final position (target). Stage and Player simulator is used to perform the robot motion and implement the potential field algorithm in C/C++ for performance evaluation. Two-dimensional terrain model is used to simulate the ability of robot in motion planning without any collision.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.1
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• pp.9-21
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• 1998

This paper 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 them. 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.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.03a
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• pp.88-93
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• 1998

This paper presents a new solution approach to moving obstacle avoidance problem for 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 them. 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 terns 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 form 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.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.330-330
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• 2000

In this paper, as an entertainment robot the implementation of boxing robot system is presented for mechatronics education. In order for students to learn robot as a mechatronics system, boxing robot is a good model. The boxing robot consists of three parts: two link arms for punching, controller for actuating wheeled mobile robot, infrared rays sensors for the detection of he other robot and ring. The strategic algorithm for playing boxing is presented as wel as simple game rules.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.370-376
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• 2023

Aiming at the problems of low image enhancement accuracy, long enhancement time and poor image quality in the traditional robot sequence motion image enhancement methods, an adaptive enhancement method for robot sequence motion image is proposed. The feature representation of the image was obtained by Karhunen-Loeve (K-L) transformation, and the nonlinear relationship between the robot joint angle and the image feature was established. The trajectory planning was carried out in the robot joint space to generate the robot sequence motion image, and an adaptive homomorphic filter was constructed to process the noise of the robot sequence motion image. According to the noise processing results, the brightness of robot sequence motion image was enhanced by using the multi-scale Retinex algorithm. The simulation results showed that the proposed method had higher accuracy and consumed shorter time for enhancement of robot sequence motion images. The simulation results showed that the image enhancement accuracy of the proposed method could reach 100%. The proposed method has important research significance and economic value in intelligent monitoring, automatic driving, and military fields.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1161-1164
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• 1996

In this paper, a parameter optimization technique for a mobile robot navigation is discussed. Authors already have proposed a navigation algorithm for mobile robots with sonar sensors using fuzzy decision making theory. Fuzzy decision making selects the optimal via-point utilizing membership values of each via-point candidate for fuzzy navigation goals. However, to make a robot successfully navigate through an unknown and cluttered environment, one needs to adjust parameters of membership function, thus changing shape of MF, for each fuzzy goal. Furthermore, the change in robot configuration, like change in sensor arrangement or sensing range, invokes another adjusting of MFs. To accomplish an intelligent way to adjust these parameters, we adopted a genetic algorithm, which does not require any formulation of the problem, thus more appropriate for robot navigation. Genetic algorithm generates the fittest parameter set through crossover and mutation operation of its string representation. The fitness of a parameter set is assigned after a simulation run according to its time of travel, accumulated heading angle change and collision. A series of simulations for several different environments is carried out to verify the proposed method. The results show the optimal parameters can be acquired with this method.

• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.61-69
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• 2010

An autonomous robot must have a global workspace map in order to cover the complete workspace. However, most previous coverage algorithms assume that they have a grid workspace map that is to be covered before running the task. For this reason, most coverage algorithms can not be applied to complete coverage tasks in unknown environments. An autonomous robot has to build a workspace map by itself for complete coverage in unknown environments. Thus, we propose a new DmaxCoverage algorithm that allows a robot to carry out a complete coverage task in unknown environments. This algorithm integrates a SLAM algorithm for simultaneous workspace map building. Experimentally, we verify that DmaxCoverage algorithm is more efficient than previous algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.11
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• pp.1137-1145
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• 2007

Palletizing tasks are necessary to promote efficient storage and shipping of boxed products. These tasks, however, involve some of the most monotonous and physically demanding labor in the factory. Thus, many types of robot palletizing systems have been developed, although many robot motion commands still depend on the teach pendant. That is, the operator inputs the motion command lines one by one. This is very troublesome and, most importantly, the user must know how to type the code. We propose a new GUI(Graphic User Interface) for the palletizing system that is more convenient. To do this, we used the PLP "Fast Algorithm" and 3-D auto-patterning visualization. The 3-D patterning process includes the following steps. First, an operator can identify the results of the task and edit them. Second, the operator passes the position values of objects to a robot simulator. Using those positions, a palletizing operation can be simulated. We chose a widely used industrial model and analyzed the kinematics and dynamics to create a robot simulator. In this paper we propose a 3-D patterning algorithm, 3-D robot-palletizing simulator, and modified trajectory generation algorithm, an "overlapped method" to reduce the computing load.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1977-1978
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• 2006

This paper discusses the method of vision based sensor fusion system for biped robot walking. Most researches on biped walking robot have mostly focused on walking algorithm itself. However, developing vision systems for biped walking robot is an important and urgent issue since biped walking robots are ultimately developed not only for researches but to be utilized in real life. In the research, systems for environment recognition and tele-operation have been developed for task assignment and execution of biped robot as well as for human robot interaction (HRI) system. For carrying out certain tasks, an object tracking system using modified optical flow algorithm and obstacle recognition system using enhanced template matching and hierarchical support vector machine algorithm by wireless vision camera are implemented with sensor fusion system using other sensors installed in a biped walking robot. Also systems for robot manipulating and communication with user have been developed for robot.

• Journal of Advanced Marine Engineering and Technology
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• v.32 no.1
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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.