• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.217-225
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• 2016

In this paper, we propose an improved path planning method and obstacle avoidance algorithm for two-wheel mobile robots, which can be effectively applied in an environment where obstacles can be represented by circles. Firstly, we briefly introduce the rapidly exploring random tree (RRT) and single polar polynomial (SPP) algorithm. Secondly, we present additional two methods for applying our proposed method. Thirdly, we propose a global path planning, smoothing and obstacle avoidance method that combines the RRT and SPP algorithms. Finally, we present a simulation using our proposed method and check the feasibility. This shows that proposed method is better than existing methods in terms of the optimality of the trajectory and the satisfaction of the kinematic constraints.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.4
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• pp.375-381
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• 2011

This paper deals with the improvement of visual path following through velocity variation according to the coordinate of feature points. Visual path follow first teaches driving path by selecting milestone images then follows the route by comparing the milestone image and current image. We follow the visual path following algorithm of Chen and Birchfield [8]. In [8], they use fixed translational and rotational velocity. We propose an algorithm that uses different translational velocity according to the driving condition. Translational velocity is adjusted according to the variation of the coordinate of feature points on image. Experimental results including diverse indoor cases show the feasibility of the proposed algorithm.

• International Journal of Control, Automation, and Systems
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• v.2 no.1
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• pp.107-117
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• 2004

A new algorithm for planning a collision-free path based on an algebraic curve as well as the concept of path space is developed. Robot path planning has so far been concerned with generating a single collision-free path connecting two specified points in a given robot workspace with appropriate constraints. In this paper, a novel concept of path space (PS) is introduced. A PS is a set of points that represent a connection between two points in Euclidean metric space. A geometry mapping (GM) for the systematic construction of path space is also developed. A GM based on the 2$^{nd}$ order base curve, specifically Bezier curve of order two is investigated for the construction of PS and for collision-free path planning. The Bezier curve of order two consists of three vertices that are the start, S, the goal, G, and the middle vertex. The middle vertex is used to control the shape of the curve, and the origin of the local coordinate (p, $\theta$) is set at the centre of S and G. The extreme locus of the base curve should cover the entire area of actual workspace (AWS). The area defined by the extreme locus of the path is defined as quadratic workspace (QWS). The interference of the path with obstacles creates images in the PS. The clear areas of the PS that are not mapped by obstacle images identify collision-free paths. Hence, the PS approach converts path planning in Euclidean space into a point selection problem in path space. This also makes it possible to impose additional constraints such as determining the shortest path or the safest path in the search of the collision-free path. The QWS GM algorithm is implemented on various computer systems. Simulations are carried out to measure performance of the algorithm and show the execution time in the range of 0.0008 ~ 0.0014 sec.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.556-559
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• 1997

In this paper, we propose a cooperative multi-robot control algorithm. Specifically, the cooperative task is that two mobile robots should transfer a long rigid object along a predefined path. To resolve the problem, we introduce the master-slave concept for two mobile robots, which have the same structure. According to the velocity of the master robot and the positions of two robots on the path, the velocity of the slave robot is determined. In case that the robots can't move further, the role of the robot is interchanged. The effectiveness of this decentralized algorithm is proved by computer simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.405-411
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• 2011

This paper presents a hierarchical trajectory planning method which can handle a collision-free of the planned path in complex and dynamic environments. A PV (Path & Velocity profile) planning method minimizes a sharp change of orientation and waiting time to avoid a collision with moving obstacle through detour path. The path generation problem is solved by three steps. In the first step, a smooth global path is generated using $A^*$ algorithm. The second step sets up the velocity profile for the optimization problem considering the maximum velocity and acceleration. In the third step, the velocity profile for obtaining the shortest path is optimized using the fuzzy and genetic algorithm. To show the validity and effectiveness of the proposed method, realistic simulations are performed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.2
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• pp.121-128
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• 2021

In this paper, we propose a path generation and tracking algorithm of an unmanned air vehicle in a two-dimensional plane given the initial and final points. The path generation algorithm using the Dubins curve proposed in this work has the advantage that it can be applied in real time to an unmanned air vehicle. The path tracking algorithm is an algorithm similar to the line-of-sight induction algorithm. In order to efficiently control the direction angle, a gain related to the look ahead distance concept is introduced. Most of UAVs have the limited maximum curvature due to the structural constraints. A numerical simulation is conducted to follow the path generated by the sliding mode controller considering the angular velocity limit. The path generation and tracking performance is verified by comparing the suggested controller with conventional control techniques.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.788-793
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• 2015

This paper proposes a path planning algorithm to reduce the inspection time of AOI (Automatic Optical Inspection) machines for SMT (Surface Mount Technology) in-line system. Since the field-of-view of the camera attached at the machine is much less than the entire inspection region of board, the inspection region should be clustered to many groups. The image acquisition time depends on the number of groups, and camera moving time depends on the sequence of visiting the groups. The acquired image is processed while the camera moves to the next position, but it may be delayed if the group includes many components to be inspected. The inspection delay has influence on the overall job time of the machine. In this paper, we newly considers the inspection delay time for path planning of the inspection machine. The unified approach using genetic algorithm is applied to generates the groups and visiting sequence simultaneously. The chromosome, crossover operator, and mutation operator is proposed to develop the genetic algorithm. The experimental results are presented to verify the usefulness of the proposed method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.327-330
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• 1995

If a mobile robot is used in a real situation, robot must face a moving obstacles. In that case, the collision avoidance algorithm for moving obstacle is a indispensible element in mobile robot control. We csrried out a research to find and evaluate the advanced algorithm for mobile robot. At first we generate the continous path for mobi;e robot. Then by creating a curved path for avoidance, the mobile robot can change its path smoothly. Smoothed path made the robot adapt more effectively to the changing of path. Under time-varying condition, computer simulation was performed to show the validation of proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.399-399
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• 2000

In this paper, path generation using the sensor platform is proposed. The sensor platform is composed two electric motors which make panning and tilting motions. An algorithm fur a real path form and an obstacle length is realized using a scanning algorithm to rotating the sensors on the sensor platform. An ARV (Autonomous Robot Vehicle) is able to recognize the given path by adapting this algorithm. In order for the ARV to navigate the path flexibly, a kinematic model needed to be constructed. The kinematic model of the ARV was reformed around its body center through a relative velocity relationship to controllability, which derives from the nonholonomic characteristics. The optimal controller that is based on tile kinematic model is operated purposefully to track a reference vehicle's path. The path generation algorithm is composed of two parks. On e part is the generating path pattern, and the other is used to avoid an obstacle. The optimal controller is used for tracking the reference path which is generated by recognizing the path pattern. Results of simulation show that this algorithm for an ARV is sufficient for path generation by small number of sensors and for low cost controller.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.6
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• pp.74-80
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• 2009

Path tracking of unmanned vehicle is a basis of autonomous driving and navigation. For the path tracking, it is very important to find the exact position of a vehicle. GPS is used to get the position of vehicle and a direction sensor and a velocity sensor is used to compensate the position error of GPS. To detect path lines in a road image, the bird's eye view transform is employed, which makes it easy to design a lateral control algorithm simply than from the perspective view of image. Because the driving speed of vehicle should be decreased at a curved lane and crossroads, so we suggest the speed control algorithm used GPS and image data. The control algorithm is simulated and experimented from the basis of expert driver's knowledge data. In the experiments, the results show that bird's eye view transform are good for the steering control and a speed control algorithm also shows a stability in real driving.