• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.256-261
• /
• 2005

In this research, we propose a path-planning algorithm for an autonomous mobile robot using geographical information, under the condition that the robot moves in unknown environment. All image inputted by camera at every sampling time are analyzed and geographical elements are recognized, and the geographical information is embedded in environmental map. The geographical information was transformed into 1-dimensional evaluation value that expressed the difficulty of movement for the robot. The robot goes toward the goal searching for path that minimizes the evaluation value at every sampling time. Then, the path is updated by integrating the exploited information and the prediction on unexploited environment. We used a sensor fusion method for improving the mobile robot dead reckoning accuracy. The experiment results that confirm the effectiveness of the proposed algorithm on the robot's reaching the goal successfully using geographical information are presented.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.105.5-105
• /
• 2001

This paper describes a fuzzy steering controller for an autonomous mobile robot with MR sensor. Using the magnetic field(Bx, By, Bz) obtained from the MR sensor, we designed fuzzy controller for driving on the road center. Fuzzy rule base was built to magnetic field(Bx, By, Bz). To develop an autonomous mobile robot simulation program, we have done modeling MR sensor, dynamic model of mobile robot and coordinate transformation. A computer simulation of the robot including mobile robot dynamics and steering was used to verify the steering performance of the mobile robot controller using the fuzzy logic Good results were obtained by computer simulation. So, we confirmed the robustness of the proposed fuzzy controller by computer ...

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.281-281
• /
• 2000

This paper presents an implementation of speech recognition system for teaching an autonomous mobile robot. The use of human speech as the teaching method provides more convenient user-interface for the mobile robot. In this study, for easily teaching the mobile robot, a study on the autonomous mobile robot with the function of speech recognition is tried. In speech recognition system, a speech recognition algorithm using HMM(Hidden Markov Model) is presented to recognize Korean word. Filter-bank analysis model is used to extract of features as the spectral analysis method. A recognized word is converted to command for the control of robot navigation.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.1
• /
• pp.108-114
• /
• 2014

This paper proposes a generation method of a navigation guidance direction and a fuzzy controller to achieve the autonomous navigation of a mobile robot using a particle swarm optimization(PSO) scheme in unknown environments. The proposed navigation guidance direction is the direction that leads a mobile robot to arrive a target point simultaneously with avoiding obstacles efficiently according to the surrounding local informations. It is generated by selecting the most suitable direction of the many directions in the surrounding environment using a particle swarm optimization scheme. Also, a robot can reach a target point with avoiding the various obstacles by controlling the robot so that it can move from its current orientation to the navigation guidance direction using the proposed fuzzy controller. Simulation results are presented to show the feasibility and validity of the proposed robot navigation scheme.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.855-858
• /
• 2003

The trends of recent developed a pet robot which interacts with people are increased gradually. There are a few pet robots that are a robot dog, robot cat, and robot fish. The pet robot is featured that it is possible to sympathize and give pleasure to human. The pet robots express delight, sorrow, surprise, and hunger through the artificial intelligence. Previously, the pet robot has to exchange the battery when it is exhausted. Commercialized robots have a self-recharging function, which express hunger. Robot dog AIBO, SONY in Japan, checks the battery for expressing hunger. They find an energy station for recharge. While operation time of AIBO is 1 hour 30 minutes, recharging time is 2 hours. Recharging time is longer than operation time. During the recharge, they don't operate. We obtain a motivation for eating the battery when find the problem. In this paper, introduce an Autonomous Eating Pet Robot and propose a design for realization. The Autonomous Eating Pet Robot has a function that is the most basic instinct that is finding a food and evacuating.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.152-152
• /
• 2000

In this paper, we propose a new approach to intelligent motion and autonomous maneuvering of mobile robots using hybrid system. In high Level, the discrete states are defined by using the sensor-based search windows and the reference motions of a mobile robot as a low vevel are specified in the abstracted motions, The mobile robots can perform both the motion planning and autonomous maneuvering with obstacle avoidance in indoor navigation problem. Simulation and experimental results show that hybrid system approach is an effective method for the autonomous maneuvering in indoor environments.

• Journal of the Institute of Convergence Signal Processing
• /
• v.9 no.3
• /
• pp.230-237
• /
• 2008

Recently, lots of interest and competition in developments related to the autonomous-vehicle robot are being further increased. However, the absence of the standard architectures for effectively controlling the autonomous-vehicle robot led to many difficulties such as the long duration of development and the uncompatibility with other autonomous-vehicle robots. Accordingly, we implemented a mobile autonomous-vehicle robot system based on JAUS standard architecture. The mobile robot communicates with the remote-control system by using wireless LAN UDP/IP JAUS command massages. Its effectiveness is showed through the experimental results related to the navigation of implemented robot.

• The Journal of Korea Robotics Society
• /
• v.5 no.2
• /
• pp.110-119
• /
• 2010

This paper aims to add the autonomous driving capability to the inverted pendulum system which maintains the inverted pendulum upright stably. For the autonomous driving from the starting position to the goal position, the motion control algorithm is proposed based on the dynamics of the inverted pendulum robot. To derive the dynamic model of the inverted pendulum robot, a three dimensional robot coordinate is defined and the velocity jacobian is newly derived. With the analysis of the wheel rolling motion, the dynamics of inverted pendulum robot are derived and used for the motion control algorithm. To maintain the balance of the inverted pendulum, the autonomous driving strategy is derived step by step considering the acceleration, constant velocity and deceleration states simultaneously. The driving experiments of inverted pendulum robot are performed while maintaining the balance of the inverted pendulum. For reading the positions of the inverted pendulum and wheels, only the encoders are utilized to make the system cheap and reliable. Even though the derived dynamics works for the slanted surface, the experiments are carried out in the standardized flat ground using the inverted pendulum robot in this paper. The experimental data for the wheel rolling and inverted pendulum motions are demonstrated for the straight line motion from a start position to the goal position.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.6 no.1
• /
• pp.148-156
• /
• 2011

This paper presents an implementation of autonomous navigation of a mobile robot indoors. It explains methods for map building, localization, obstacle avoidance and path planning. Geometric map is used for localization and path planning. The localization method calculates sensor data based on the map for comparison with the real sensor data. Monte Carlo Localization(MCL) method is adopted for estimation of the robot position. For obstacle avoidance, an artificial potential field generates repulsive and attractive force to the robot. Dijkstra algorithm plans the shortest distance path from a start position to a goal point. The methods integrate into autonomous navigation method and implemented for indoor navigation. The experiments show that the proposed method works well for safe autonomous navigation.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.1177-1180
• /
• 1996

In this paper, we propose an algorithm that realizes cooperative behavior by construction of autonomous mobile robot system. Each robot is able to sense other robots and obstacles, and it has the rule of behavior to achieve the goal of the system. In this paper, to improve performance of the whole system, we use Genetic Programming based on Natural Selection. Genetic Programming's chromosome is a program of tree structure and it's major operators are crossover and mutation. We verify the effectiveness of the proposed scheme from the several examples.