• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.275-281
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• 2007

This paper presents a motion planning strategy for legged robots using locomotion primitives in the complex 3D environments. First, we define configuration, motion primitives and locomotion primitives for legged robots. A hierarchical motion planning method based on a combination of 2.5 dimensional maps of the 3D workspace is proposed. A global navigation map is obtained using 2.5 dimensional maps such as an obstacle height map, a passage map, and a gradient map of obstacles to distinguish obstacles. A high-level path planner finds a global path from a 2D navigation map. A mid-level planner creates sub-goals that help the legged robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. A local obstacle map that describes the edge or border of the obstacles is used to find the sub-goals along the global path. A low-level planner searches for a feasible sequence of locomotion primitives between sub-goals. We use heuristic algorithm in local motion planner. The proposed planning method is verified by both locomotion and soccer experiments on a small biped robot in a cluttered environment. Experiment results show an improvement in motion stability.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.31-40
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• 2009

The most common cleaning methods of cleaning robot can be divided into two categories: the random and the boustrophedon method. A cleaning robot using the random method moves straight until it bumps into an obstacle. If it collides with an obstacle, the cleaning robot turns a specific angle and continues moving straight. Therefore, the random method often tends to clean the already clean area repeatedly. In addition, it takes a long time to complete cleaning. A cleaning robot using the boustrophedon method moves straight until it collides with an obstacle. If it meets an obstacle, the cleaning robot moves to the next uncleaned space through turning and moving ahead. when resuming cleaning from the new region, a cleaning robot moves in the direction opposite to the direction of the previous cleaning. Because the boustrophedon method cleans a cleaning space more densely, its performance is excellent in an obstacle-free space or a small space. However, In a space with obstacles or a complex structure, it takes a long time to complete the cleaning work. Cleaning should be systematically approached with a good understanding of the work area. The virtual map-based cleaning robot proposed in this paper cleaned a work space efficiently. The efficiency of the proposed method was measured through simulation.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1499-1502
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• 2002

A method for acquiring an environmental map by integrating distance data obtained by sonars of a moving robot with web interface is proposed. Sonar data contains outliers in some cases such as ultrasonic beam is projected onto a corner of an object. Therefore, the influence of the outliers should be reduced by detecting outliers. In our method, the outliers are detected by two ways: (i) a method considering geometrical .elation among the observed surface and the projected ultrasonic beau, and (ii) a method considering consistency with data obtained by other sonars. By measurement by the sonar, the distance from the sonar to the obstacle is obtained. Assuming the two dimensional space we can know that the inside of the sector, whose renter coincide with the sonar and whose radius is equal to the obtained distance, is the free area, and a part of the arc of this sector is the obstacle area. The generation of the environmental map is done by integrating the free area and the obstacle area obtained by each measurement by the sonars. Before the integration, the outliers detection is done by two ways mentioned above. Experimental results show that obtained maps obtained by our methods with outliers defection are much better than those by a method without outliers detection.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1127-1130
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• 2003

This paper introduces histogramic in-motion mapping for real-time map building with the Eyebot in motion. A histogram grid used in HIMM is updated through three PSD sensors. HIMM makes it possible to make fast map-building and avoid obstacles in real-time. Fast map-building allows the robot to immediately use the mapped information in real-time obstacle-avoidance algorithms. HIMM has been tested on the Eyebot. The Eyebot sends PSD data to computer and computer builds a 3D-Map based on PSD data.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.809-817
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• 2008

This paper describes an obstacle detecting system of an unmanned ground vehicle (UGV). The unmanned ground vehicle is consists of several systems such as vehicle control system, navigation system, obstacle detecting system and integration system. Among these systems, the obstacle detecting system is a driving assistance system of UGV. Through the UGV is driving, the system detects obstacles such as cars, human, tree, curb and hills and then send information of obstacles position to integration system for safety driving. In this research, the obstacle detecting system is composed of 5 laser scanners and develop algorithms of detecting obstacles, curb, uphill and downhill road.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.105.1-105
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• 2002

$\textbullet$ This paper deals with obstacle avoidance of a quadruped robot with a vision system and a PSD sensor. $\textbullet$ The vision system needs for obstacle recognition toward robot. $\textbullet$ Ths PSD sensor is also important element for obstacle recognition. $\textbullet$ We propose algorithm that recognizes obstacles with one vision and PSD sensor. $\textbullet$ We also propose obstacle avoidance algorithm with map from obstacle recognition algorithm. $\textbullet$ Using these algorithm, Quadruped robot can generate gait trajectory. $\textbullet$ Therefore, robot can avoid obstacls, and can move to target point.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.398-398
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• 2000

Since there is a blind zone in driver's view around the excavator, industrial accidents between the equipment and the workers within the zone have been occurred frequently. The purpose of this paper is to develop a obstacle recognition system which can prevent such an accident by providing the driver with the information on direction and distance of the obstacle within the blind zone. We designed the ultrasonic sensor based obstacle recognition system which consists of sensor arrays and a control unit connected via CAN(controller area network). The Cross-correlation technique and histogramic probability distribution method are used as a reliable obstacle detection algorithms to remove the environmental noise. The experimental results using a real excavator show the effectiveness of the system.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.2
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• pp.21-34
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• 2002

Different from ordinary mobile robots used in a well-structured industrial workspace, a guide mobile robot for the visually impaired should be designed in consideration of a moving obstacle, which mostly refers to pedestrians in intentional motions. Thus, the navigation of the guide robot can be facilitated if the intention of each detected obstacle can be known in advance. In this paper, we propose an inference method to understand an intention of a detected obstacle. In order to represent the environment with ultrasonic sensors, the fuzzy grid-type map is first constructed. Then, we detect the obstacle and infer the intention for collision avoidance with the CLA(Centroid of Largest Area) point of the fuzzy grid-type map. To verify the proposed method, some experiments are performed.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1168-1171
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• 2003

The visuo-motor map is based on the Kohonen's self-organizing map. The map is learned the relation of the end effecter coordinates and the joint angles. In this paper, a 3 d-o-fmanipulator which moves in the 2D space is targeted. A CCD camera is set beside the manipulator, and the end effecter coordinates are given from the image of a manipulator. As a result of learning, the end effecter can be moved to the destination without exact teaching.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.5
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• pp.549-556
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• 2009

One of the basic technology for implementing the autonomy of UGV(Unmanned Ground Vehicle) is a path planning algorithm using obstacle and raw terrain information which are gathered from perception sensors such as stereo camera and laser scanner. In this paper, we propose a generation method of DVGM(Directional Velocity Grid Map) which have traverse speed of UGV for the five heading directions except the rear one. The fuzzy system is designed to generate a resonable traveling speed for DVGM from current patch to the next one by using terrain slope, roughness and obstacle information extracted from raw world model data. A simulation is conducted with world model data sampled from real terrain so as to verify the performance of proposed fuzzy inference system.