• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.256-256
• /
• 2000

In this parer, we present a real-time path planning algorithm which is integrated the artificial potential field(APF) and simulated annealing(SA) methods for mobile robot. The APF method in path planning has gained popularity since 1990's. It doesn't need the modeling of the complex configuration space of robot, and is easy to apply the path planning with simple computation. However, there is a major problem with APF method. It is the formation of local minima that can trap the robot before reaching its goal. So, to provide local minima recovery, we apply the SA method. The effectiveness of the proposed algorithm is verified through simulation.

• The Journal of Korea Robotics Society
• /
• v.2 no.2
• /
• pp.161-167
• /
• 2007

It is dangerous that an inspector overhauls defects and condition of the inner parts of an oil tanker because of many harmful gases, complex structures, and etc. However, these inspections are necessary to many oil tankers over old years. In this study, we proposed the design of mobile robot for inspection of CAS in oil tanker. The developed CAS inspection mobile robot has four modules, a measurement module of oil tanker's thickness, a corrosion inspection module, a climbing module of the surface on a wall, and a monitoring module. In order to get over at a check position, the driving control algorithm was developed. Magnetic wheels are used to move on the surface of a wall. This study constructed a communication network and the monitoring program to operate the developed mobile robot from remote sites. In order to evaluate the inspection ability, the experiments about performance of CAS inspection using the developed mobile robot have been carried out.

• The Journal of Korea Robotics Society
• /
• v.3 no.2
• /
• pp.123-130
• /
• 2008

In this paper, we present a grasp planning method using grasp taxonomy and object primitives. Our grasp taxonomy includes newly defined grasp methods such as thumb supported pinch and palm supported pinch, to enhance grasp robustness. On the target surface, locations of finger-print that will be contacted by the robot fingers are sampled. The sampling is made to be consistent to the grasp taxonomy, called preformed grasps, matched to the target object. We perform simulations to examine the validity and the efficacy of the proposed grasp planning method.

• Proceedings of the KIEE Conference
• /
• 2002.07d
• /
• pp.2827-2830
• /
• 2002

본 논문에서는 청소로봇이 두 점간에 이동할 때 벽면을 안전하게 추적하는 방법과 두 점간의 이동 알고리즘을 제안하고자 한다. 제안한 방법은 각각의 적외선 센서에 다른 가중치 벡터를 부여하여 장애물이나 벽면에 대한 정보를 이용하게 된다. 청소로봇은 벽면정보를 이용하여 벽면 주행하게 했다. 그리고 두 점검간의 이동알고리즘으로 이동 할 경우에 벽면 추적 방법과 각도 오차 값과 거리의 error값이 오차가 0이 되도록 두 점간의 이동 알고리즘의 수식의 대수적인 합으로 안전하게 벽면을 주행하였다. Visual C++기반에서 시뮬레이션 한 결과 안전하게 벽면을 추적하고 벽면을 따라 주행하는 벽면주행 알고리즘을 제안하였다.

• The Journal of Korea Robotics Society
• /
• v.1 no.2
• /
• pp.107-116
• /
• 2006

We propose a planning algorithm to automatically generate a robust behavior plan (RBP) with which mobile robots can achieve their task goal from any initial states under dynamically changing environments. For this, task description space (TDS) is formulated, where a redundant task configuration space and simulation model of physical space are employed. Successful task episodes are collected, where $A^*$ algorithm is employed. Interesting TDS state vectors are extracted, where occurrence frequency is used. Clusters of TDS state vectors are found by using state transition tuples and features of state transition tuples. From these operations, characteristics of successfully performed tasks by a simulator are abstracted and generalized. Then, a robust behavior plan is constructed as an ordered tree structure, where nodes of the tree are represented by attentive TDS state vector of each cluster. The validity of our method is tested by real robot's experimentation for a box-pushing-into-a-goal task.

• The Journal of Korea Robotics Society
• /
• v.6 no.3
• /
• pp.255-262
• /
• 2011

Many intelligent robots have to be given environmental information to perform tasks. In this paper an intelligent robot, that is, a cleaning robot used a sensor fusing method of two sensors: LRF and StarGazer, and then was able to obtain the information. Throughout wall following using laser displacement sensor, LRF, the working area is built during the robot turn one cycle around the area. After the process of wall following, a path planning which is able to execute the work effectively is established using flow network algorithm. This paper describes an algorithm for minimal turning complete coverage path planning for intelligent robots. This algorithm divides the whole working area by cellular decomposition, and then provides the path planning among the cells employing flow networks. It also provides specific path planning inside each cell guaranteeing the minimal turning of the robots. The proposed algorithm is applied to two different working areas, and verified that it is an optimal path planning method.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.5
• /
• pp.444-449
• /
• 2006

Path planning is a key element in navigation of a mobile robot. Several algorithms such as a gradient method have been successfully implemented so for. Although the gradient method can provide the global optimal path, it computes the navigation function over the whole environment at all times, which result in high computational cost. This paper proposes a high-speed path planning scheme, called a gradient method with topological information, in which the search space for computation of a navigation function can be remarkably reduced by exploiting the characteristics of the topological information reflecting the topology of the navigation path. The computing time of the gradient method with topological information can therefore be significantly decreased without losing the global optimality. This reduced path update period allows the mobile robot to find a collision-free path even in the dynamic environment.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.5
• /
• pp.473-479
• /
• 2006

A global path planning algorithm using modified self-organizing feature map(SOFM) which is a method among a number of neural network is presented. The SOFM uses a randomized small valued initial weight vectors, selects the neuron whose weight vector best matches input as the winning neuron, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. On the other hand, the modified method in this research uses a predetermined initial weight vectors of the 2-dimensional mesh, gives the systematic input vector whose position best matches obstacles, and trains the weight vectors such that neurons within the activity bubble are move toward the opposite direction of input vector. According to simulation results one can conclude that the modified neural network is useful tool for the global path planning problem of a mobile robot.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.9
• /
• pp.845-853
• /
• 2012

We propose time-optimal cornering motion trajectory planning and control algorithms for differential wheeled mobile robot with motor actuating voltage constraint, under piecewise constant control input condition. For time-optimal cornering trajectory generation, 1) we considered mobile robot's dynamics including actuator motors, 2) divided the cornering trajectory into one liner section, followed by two cornering section with angular acceleration and deceleration, and finally one liner section, and 3) formulated an efficient trajectory generation algorithm satisfying the bang-bang control principle. Also we proposed an efficient trajectory control algorithm and implemented with an X-bot to prove the performance.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.1
• /
• pp.53-60
• /
• 2010

We propose a motion planning method for autonomous mobile robots. In order to minimize traveling time, a smooth path and a time optimal velocity profile should be generated under kinematic and dynamic constraints. In this paper, we develop an effective and practical method to generate a good solution with lower computation time. The initial path is obtained from voronoi diagram by Dijkstra's algorithm. Then the path is improved by changing the graph and path simultaneously. We apply the dynamic programming algorithm into the stage of improvement. Simulation results are presented to verify the performance of the proposed method.