• Proceedings of the Korean Information Science Society Conference
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• 2003.10c
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• pp.199-201
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• 2003

Ad hoc network은 stationary infrastructure의 도움 없이 이동 노드들이 필요 시 network 형태을 구성하여 통신이 이루어지게 하는 network으로 ad hoc network 환경에 맞는 다양한 라우팅 프로토콜들이 개발되었고 크게는 table­driven, on­demand 방식으로 나눌 수 있는데 on­demand 방식의 AODV 프로토콜은 routing overhead가 적다는 장점이 있는 반면 single path로 data forwarding을 진행하여 중간노드의 이동에 의한 path가 broken되는 경우 local routing을 하거나 새로이 source­initialed route rediscovery을 수행하여 전송 delay 및 control traffic overhead 등을 높이는 결과를 발생 시켰다. 본 논문은 single path로 구성되는 AODV 프로토콜의 route failures시 문제점을 보완한 Associativity Based Redundancy path Routing(ABRR) 및 Alternate Redundancy path Routing(ARR) schemes을 제안한다. 첫째, ABRR은 main path상에 있는 각 노드들은 associativity based stable node 정보를 이용하여 path broken 이전에 local redundancy path을 구성하여 path broken시 local routing없이 route을 복구할 수 있게 하고 둘째, ARR은 source­initialed route discovery에 의해 alternate path을 구성하여 ABRR 그리고 local routing에 의해 main route recovery 실패 시 alternate path을 main path로 전환하여 control traffic overhead 및 전송 delay을 줄이게 한다.

• International Journal of Control, Automation, and Systems
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• v.4 no.3
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• pp.318-324
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• 2006

The mobile manipulator is expected to work in partially defined or unstructured environments. In our global/local approach to path planning, joint trajectories are generated for a desired Cartesian space path, designed by the global path planner. For a local path planner, inverse kinematics for a redundant system is used. Joint displacement limit for the manipulator links is considered in the motion planner. In an event of failure to obtain feasible trajectories, the task cannot be accomplished. At the point of failure, a deviation in the Cartesian space path is obtained and a replanner gives a new path that would achieve the goal position. To calculate the deviation, a nonlinear optimization problem is formulated and solved by standard Sequential Quadratic Programming (SQP) method.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.664-668
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• 2012

Hierarchical IPP (Integrated Path Planning) combining the GPP (Global Path Planner) and the LPP (Local Path Planner) is interesting the researches who study about the mobile vehicle in recent years. However, in this study, there is the path mismatch problem caused by the difference in the map information available to both path planners. If ever a part of the path that was found by the GPP is available to mobile vehicle, the part may be unavailable when the mobile vehicle generates the local path with its built-in sensors while the vehicle moves. This paper proposed the TWR (Temporal Waypoint Reviser) to solve the path mismatch problem of the hierarchical IPP. The results of simulation provide the performance of the IPP with the TWR by comparing with other path planners.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.11
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• pp.1175-1180
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• 2014

This paper proposes a new technique that produces improved local information using a low-cost GPS/INS system combined with Extended Kalman Filter and Path Planning when a Quad-rotor flies. In the research, a low-cost GPS is combined with INS by Extended Kalman Filter to improve local information. However, this system has disadvantages in that estimation accuracy is getting worsens when the Quad-rotor flies through the air in a curve and precision of location information is influenced by performance of the used GPS. An algorithm based on Path Planning is adopted to deal with these weaknesses. When the Quad-rotor flies outdoors, a short moving path can be predicted because all short moving paths of quad-rotor can be assumed to be straight. Path planning is used to make the short moving path and determine the closest local information of data of the GPS/INS system to location determined by path planning. Through the foregoing process, improved local data is obtained when the quad-rotor flies, and the performance of the proposed system is verified from various outdoor experiments.

• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.25-28
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• 2002

The path planning of autonomous mobile robot use two method. One is global path planning and another is local path planning. In this paper, We study the local path planning of autonomous mobile robot move in unknown enviroment. This local path planning is based on neural network using the direction indicator rules learning. also the system is made up of sensor system. The motion control system for real-time execution. The experimental results show that the developed direction indicator system operates properly and strongly at circumstance.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.133-136
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• 1996

The nozzle dam task is essentially needed to maintain and repair nuclear power plants. For this task, an 8-dof redundant robot is studied with a local path-planning method[l] which is effective to find the optimal joint path in the constrained environment. In this paper, the method[l] is improved practically with the weight matrix and efficient algorithm to find working set. The effectiveness of the proposed method is demonstrated by simulation and animation.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.471-478
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• 2011

This UGV (Unmanned Ground Vehicle) is not only widely used in various practical applications but is also currently being researched in many disciplines. In particular, obstacle avoidance is considered one of the most important technologies in the navigation of an unmanned vehicle. In this paper, we introduce a simple algorithm for path planning in order to reach a destination while avoiding a polygonal-shaped static obstacle. To effectively avoid such an obstacle, a path planned near the obstacle is much shorter than a path planned far from the obstacle, on the condition that both paths guarantee that the robot will not collide with the obstacle. So, to generate a path near the obstacle, we have developed an algorithm that combines an edge detection method and a limit-cycle navigation method. The edge detection method, based on Hough Transform and IR sensors, finds an obstacle's edge, and the limit-cycle navigation method generates a path that is smooth enough to reach a detected obstacle's edge. And we proposed novel algorithm to solve local minima using the virtual wall in the local vision. Finally, we verify performances of the proposed algorithm through simulations and experiments.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1140-1143
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• 1996

A new approach based on artificial potential function is proposed for the obstacle avoidance of redundant manipulators. Unlike the so-called "global" path planning method, which requires expensive computation for the path search before the manipulator starts to move, this new approach, "local" path planning, researches the path in real-time using the local distance information. Previous use of artificial potential function has exhibited local minima in some complex environments. This thesis proposes a potential function that has no local minima even for a cluttered environment. This potential function has been implemented for the collision avoidance of a redundant robot in Simulation. The simulation also employ an algorithm that eliminates collisions with obstacles by calculating the repulsive potential exerted on links, based on the shortest distance to object.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.3
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• pp.200-208
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• 1996

This paper describes the mechanism, guidance, sensor system, and navigation algorithm of METRO, a free ranging mobile robot. METRO is designed for use in structured surroundings or factory environments rather than unstructured natural environments. An overview of the physical configuration of the mobile robot is presented as well as a description of its sensor system, an omnidirectional laser range finder. Except for the global path planning algorithm, a guidance and a navigation algorithm with a local path planning algorithm are used to navigate the mobile robot. In METRO the computer support is divided into a supervisor with image processing and local path planning and a slave with motor control. The free ranging mobile robot is self-controlled and all processing being performed on board.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2325-2330
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• 2005

A potential field method for solving the problem of path planning based on global and local information for a mobile robot moving among a set of stationary obstacles is described. The concept of various method used path planning is used design a planning strategy. A real human living area is constructed by many moving and imminence obstacles. Home service mobile robot must avoid many obstacles instantly. A path that safe and attraction towards the goal is chosen. The potential function depends on distance from the goal and heuristic function relies on surrounding environments. Three additional combined methods are proposed to apply to human living area, calibration robots position by measured surrounding environment and adapted home service robots. In this work, we proposed the application of various path planning theory to real area, human living. First, we consider potential field method. Potential field method is attractive method, but that method has great problem called local minimum. So we proposed intermediate point in real area. Intermediate point was set in doorframe and between walls there is connect other room or other area. Intermediate point is very efficiency in computing path. That point is able to smaller area, area divided by intermediate point line. The important idea is intermediate point is permanent point until destruction house or apartment house. Second step is move robot with sensing on front of mobile robot. With sensing, mobile robot recognize obstacle and judge moving obstacle. If mobile robot is reach the intermediate point, robot sensing the surround of point. Mobile robot has data about intermediate point, so mobile robot is able to calibration robots position and direction. Third, we gave uncertainty to robot and obstacles. Because, mobile robot was motion and sensing ability is not enough to control. Robot and obstacle have uncertainty. So, mobile robot planed safe path planning to collision free. Finally, escape local minimum, that has possibility occur robot do not work. Local minimum problem solved by virtual obstacle method. Next is some supposition in real living area.