• 한국산업융합학회 논문집
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• 제21권6호
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• pp.379-388
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• 2018

In this study, we propose a new approach to impliment autonomous travelling of mobile robot based on obstacle avoidance and voice command. Obstacle Avoidance technology of mobile robpot. It has been used in wide range of different robotics areas to minimize the risk of collisions. Obstacle avoidance of mobile robots are mostly applied in transportation systems such as aircraft traffic control, autonomous cars etc. Collision avoidance is a important requirement in mobile robot systems where they all featured some kind of obstacle detection techniques in order to avoid colliding. In this paper it was illustrated the reliability of voice command and obstacle avoidance for autonomous travelling of mobile robot with two wheels as the purpose of application to the manufacturing process by simulation and experiments.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.490-492
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• 2004

This paper presents an obstacle avoidance of a mobile robot by the subgoal generation using infrared sensors. When an obstacle appears on the path which the robot is moving forward the robot has to get information, such as distance between the robot and the obstacle and the shape of the obstacle for avoidance behavior. Our collision avoidance algorithm needs the only distance between the robot and the obstacles. The distances are used for subgoal generation. Simulation results show that a robot can go to the goal, carrying out subgoal generation and avoiding obstacles.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권2호
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• pp.124-130
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• 2005

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.

• 제어로봇시스템학회논문지
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• 제15권2호
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• pp.192-197
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• 2009

In this paper, we proposed the obstacle avoidance system using a single camera image and LM(Levenberg-Marquart) neural network fuzzy controller. According to a robot technology adapt to various fields of industry and public, the robot has to move using self-navigation and obstacle avoidance algorithms. When the robot moves to target point, obstacle avoidance is must-have technology. So in this paper, we present the algorithm that avoidance method based on fuzzy controller by sensing data and image information from a camera and using the LM neural network to minimize the moving error. And then to verify the system performance of the simulation test.

• 전기학회논문지
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• 제58권4호
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• pp.824-831
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• 2009

This paper proposes an obstacle avoidance algorithm for an autonomous mobile robot. The proposed method based on the circular navigation with probability distribution finds local-paths to avoid collisions. Futhermore, it makes mobile robots to achieve obstacle avoidance and optimal path planning due to the accurate decision of the final goal. Simulation results are included to show the feasibility of the proposed method.

• 제어로봇시스템학회논문지
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• 제3권2호
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• pp.169-178
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• 1997

This paper presents a new solution approach to moving obstacle avoidance problem of a 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 three state variables: the distance from the obstacle to the robot, outward speed of the obstacle relative to the robot, and outward speed of the robot relative to the obstacle. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terms of the VDF, an artificial potential 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 a moving obstacle in real time. Since the algorithm considers the mobility of the obstacle and robot 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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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.487-490
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• 2003

In this research, we will devise an obstacle avoidance algorithm for a previously unmanned vehicle. Whole systems consist mainly of the vehicle system and the control system. The two systems are separated; this system can communicate with the vehicle system and the control system through wireless RF (Radio Frequency) modules. These modules use wireless communication. And the vehicle system is operated on PIC Micro Controller. Obstacle avoidance method for unmanned vehicle is based on the Virtual Force Field (VFF) method. An obstacle exerts repulsive forces and the lane center point applies an attractive force to the unmanned vehicle. A resultant force vector, comprising of the sum of a target directed attractive force and repulsive forces from an obstacle, is calculated for a given unmanned vehicle position. With resultant force acting on the unmanned vehicle, the vehicle's new driving direction is calculated, the vehicle makes steering adjustments, and this algorithm is repeated.

• 제어로봇시스템학회논문지
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• 제18권12호
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• pp.1132-1138
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• 2012

The MPC (Model Predictive Control) is one of the techniques that can be used to control an unmanned vehicle. It predicts the future vehicle trajectory using the dynamic characteristic of the vehicle and generate the control value to track the reference path. If some obstacles are detected on the reference paths, the MPC can generate control value to avoid the obstacles imposing the inequality constraints on the MPC cost function. In this paper, we propose an obstacle modeling algorithm for MPC with inequality constraints for obstacle avoidance and a method to set selective constraint on the MPC for stable obstacle avoidance. Simulations with the field test data show successful obstacle avoidance and way point tracking performance.

• 로봇학회논문지
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• 제4권2호
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• pp.105-111
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• 2009

In this paper, we provide experimental results and verification for obstacle avoidance algorithm 'ELA(Emergency Level Around)', which is applicable to rescue robots. ELA is a low level intelligence-based obstacle avoidance algorithm, so can be used in fast mobile robots requiringhigh speed in operation with little computational load. Constructed system for experiments consist of laptop, sensors, peripheral devices and mobile robot platform VSTR(Variable Single-tracked Robot) to realize predetermined scenarios. Finally, experiment was conducted in indoor surroundings including miscellaneous things as well as dark environment to show fitness and robustness of ELA for rescue, and it is shown that VSTR navigates endowed area well with real-time obstacle avoidance based on ELA. Therefore, it is concluded that ELA can be a candidate algorithm to increase mobility of rescue robots in real situation.

• 제어로봇시스템학회논문지
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• 제15권1호
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• pp.89-93
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• 2009

This paper deals with obstacle avoidance for unmanned vehicle using stereo system. The "DARPA Grand Challenge 2005" shows that the robot can move autonomously under given waypoint. RADAR, IMS (Inertial Measurement System), GPS, camera are used for autonomous navigation. In this paper, we focus on stereo system for autonomous navigation. Our approach is based on Singh et. al. [5]'s approach that is successfully used in an unmanned vehicle and a planetary robot. We propose an improved algorithm for obstacle avoidance by modifying the cost function of Singh et. al. [5]. Proposed algorithm gives more sharp contrast in choosing local path for obstacle avoidance and it is verified in experimental results.