• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.168-173
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• 2003

In this paper, we will present a deeper look on optimal design methods that are related to path-planning for a mobile robot. To control the motion of a mobile robot in a clustered environment, it's necessary to know a suitable trajectory assuming certain start and goal point. Up to now, there are many literatures that concern optimal path planning for an obstacle avoided mobile robot. Among those literatures, we have chosen 2 novel methods for our further analysis. The first approach [4] is based on HJB(Hamilton-Jacobi-Bellman) equation whose solution is the return-function that helps to generate a shortest path to the goal. The later [5] is called polynomial-path-planning approach, in this method, a shortest polynomial-shape path would become a solution if it was a collision-free path. The camera network plays the role as sensors to generate updated map which locates the static and dynamic objects in the space. Therefore, the exhibition of both path planning and dynamic obstacle avoidance by the updated map would be accomplished simultaneously. As we mentioned before, our research will include the motion control of a true mobile robot on those optimal planned paths which were generated by above algorithms. Base on the kinematic and dynamic simulation results, we can realize the affection of moving speed to the stable of motion on each generated path. Also, we can verify the time-optimal trajectory through velocity tuning. To simplify for our analysis, we assumed the obstacles are cylindrical circular objects with the same size.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.5
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• pp.593-599
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• 1999

A mobile robot in FMS environment should be able to nevigate itself. Therefore, path planning is necessary for the mobile robot to perform its tasks without being lost. Path planning using a network model gives oprimal paths to every pair of nodes but building this model demands accurate information of environments. In this paper, a method to build a network model using sonar sensors is presented. The main idea is to build a quad tree model by using sonar sensors and convert the model to a network model for path planning. The new method has been implemented on a mobile robot. Experimental results show that the mobile robot constructs an accurate network model using inaccurate sonar data.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.137-143
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• 2005

Autonomous mobile robot has an ability to navigate using both map in known environment and sensors for detecting obstacles in unknown environment. In general, autonomous mobile robot navigates by global path planning on the basis of already made map and local path planning on the basis of various kinds of sensors to avoid abrupt obstacles. This paper provides a global path planning method using self-organizing feature map which is a method among a number of neural network. The self-organizing feature map 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, 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 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
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• v.10 no.8
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• pp.711-717
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• 2004

We propose a path planning method to improve the productivity of SMT (surface mount technology) inspection machines with an area camera. A unified method is newly proposed to determine the FOV clusters and camera sequence simultaneously. The proposed method is implemented by a hybrid genetic algorithm to increase the convergence speed. Comparative simulation results are then presented to verify the usefulness of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.7
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• pp.651-658
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• 2011

An efficient modified $D^*$ lite algorithm is suggested, which can perform online path planning for mobile robots in dynamic indoor environment. Online path planning should plan and execute alternately in a short time, and hence it enables the robot avoid unknown dynamic obstacles which suddenly appear on robot's path. Based on $D^*$ Lite algorithm, we improved representation of edge cost, heuristic function, and priority queue management, to build a modified $D^*$ Lite algorithm. Performance of the proposed algorithm is revealed via extensive simulation study.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.416-422
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• 2013

This paper suggests a hybrid path planning method of multi-robots, where a path deviation prevention for maintaining a specific formation is implemented by using repulsive function, $A^*$ algorithm and UKF (Unscented Kalman Filter). The repulsive function in potential field method is used to avoid collision among robots and obstacles. $A^*$ algorithm helps the robots to find optimal path. In addition, error estimation based on UKF guarantees small path deviation of each robot during navigation. The simulation results show that the swarm robots with designated formation successfully avoid obstacles and return to the assigned formation effectively.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.896-899
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• 1996

A new algorithm for planning a collision free path is developed based on linear parametric curve. A collision-free path is viewed as a connected space curve in which the path consists of two straight curve connecting start to target point. A single intermediate connection point is considered in this paper and is used to manipulate the shape of path by organizing the control point in polar coordinate (.theta.,.rho.). The algorithm checks interference with obstacles, defined as GM (Geometry Mapping), and maps obstacles in Euclidean Space into images in CPS (Connection Point Space). The GM for all obstacles produces overlapping images of obstacle in CPS. The clear area of CPS that is not occupied by obstacle images represents collision-free paths in Euclidean Space. Any points from the clear area of CPS is a candidate for a collision-free path. A simulation of GM for number of cases are carried out and results are presented including mapped images of GM and performances of algorithm.

• Nuclear Engineering and Technology
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• v.53 no.11
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• pp.3505-3516
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• 2021

During nuclear facility decommissioning, workers are continuously exposed to high-level radiation. Hence, adequate path planning is critical to protect workers from unnecessary radiation exposure. This work discusses recent development in radioactive path planning and the algorithms recommended for the task. Specifically, we review the conventional methods for nuclear decommissioning path planning, analyze the techniques utilized in developing algorithms, and enumerate the decision factors that should be considered to optimize path planning algorithms. As a major contribution, we present the quantitative performance comparison of different algorithms utilized in solving path planning problems in nuclear decommissioning and highlight their merits and drawbacks. Also, we discuss techniques and critical consideration necessary for efficient application of robots and robotic path planning algorithms in nuclear facility decommissioning. Moreover, we analyze the influence of obstacles and the environmental/radioactive source dynamics on algorithms' efficiency. Finally, we recommend future research focus and highlight critical improvements required for the existing approaches towards a safer and cost-effective nuclear-decommissioning project.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.9
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• pp.1461-1467
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• 2001

This paper proposes a new approach for the ant-swing control of overhead cranes. The proposed control consists of a model-based anti-swing control scheme and a practical path planning scheme. The anti-swing control scheme is designed based on the Lyapunov stability theorem; the proposed control does not require the usual constraints of small load mass, small load swing, slow hoisting speed, and small hoisting distance, but guarantees asymptotic stability while keeping all internal signals bounded. The path planning scheme is designed based on the concepts of minimum-time control and anti-swing control; the proposed path planning generates near-minimum-time trajectories independently of hoisting speed and distance. The effectiveness of the proposed control is shown by computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.722-725
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• 1990

This paper proposes a new path planning method for obstacle avoidance of mobile robot. In order to achieve easy planning of the path, a simple representation of the empty space is achieved based on thinning algorithm. The proposed Planning technique facilitates the direct use of information obtained by camera. Comparing to the V-graph method, the task of determining the shortest path from the resulting skeleton of empty space is optimized in terms of number of computation steps. The usefulness of the proposed method is ascertained by simulation.