• 한국산업융합학회 논문집
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• 제19권2호
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• pp.75-80
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• 2016

This study proposes a efficient technology to control the optimal trajectory planning and real-time implementation method which can perform autonomous travelling for unmaned factory automation. 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 Route planning and control algorithm, we suggested representation of edge cost, heuristic function, and priority queue management, to make a modified Route planning algorithm. Performance of the proposed algorithm is verified by simulation test.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.223-225
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• 2006

A ball moving on a beam is a typical nonlnear dynamic system, which is often adopted to proof test diverse control schemes. Ball and plate system is the extension of the traditional ball and beam problem that moves a metal ball on a rigid plate. In this paper, a trajectory planning and tracking problem is proposed for ball and plate system, which is to control the ball from a point to another without hitting the obstacles. Our scheme is composed of three controllers, TS type optimal path tracking controller, mandani type obstacle avoidance controller and trajectory planning controller that determines the desired trajectory. But this type of construction can give rise to chattering executions. Because the difference of contributions from concurrent controllers can cause behaviors unsmoothly. We propose fuzzy pid supervision control1er to handle this problem.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.1760-1763
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• 2003

In this paper, we propose a new weaving trajectory algorithm for the are welding of a articulated manipulator. The algorithm uses the theory of Bezier spline. We make a comparison between the conventional algorithms using Catmull-Rom curve and the new algorithms rising Bezier spline. The proposed algorithm has been evaluated based on the MATLAB environment in order to illustrate its good performance. The algorithm has been implemented on to the industrial manipulator of DR6 so as to show its real possibility. Through simulations and real implementations, the proposed algorithm can result in high-speed and flexible weaving trajectory planning and can reduce the processing time because it needs one-half calculation compared to the conventional algorithm using Catmull-Rom curve.

• 제어로봇시스템학회논문지
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• 제13권9호
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• pp.875-882
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• 2007

In order for a vehicle to follow a predetermined trajectory accurately, its position must be estimated accurately and reliably. In this thesis, we propose trajectory tracking control methods for unmanned vehicle and a positioning system using ultrasonic wave. The positioning problem is an important part of control problem for unmanned navigation of a vehicle. Dead Reckoning is widely used for positioning of vehicle. However this method has problems because it accumulates estimation errors. We propose a new method to increase the accuracy of position estimation using the Ultrasonic Satellite System (USAT). It is shown that we will be able to estimate the position of vehicle precisely, in which errors are not accumulated. And proposed trajectory tracking control methods include both a new path planning method and a lateral control method for vehicle. The experimental results show that the proposed methods enables exact vehicle trajectory tracking even under various environmental factors.

• Advances in aircraft and spacecraft science
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• 제5권5호
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• pp.551-579
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• 2018

This work is concerned with the motion of propeller driven airplanes, flying at constant velocity on ascending or descending rectilinear trajectories. Its purpose is to provide important features of rectilinear flights that are required for airplane trajectory planning but that cannot be found already published. It presents a method for calculating the amount of fuel used, the restrictions on the trajectory parameters, as inclination and speed, which result from the load factor, the lift coefficient, the positivity and upper boundedness of the power available. It presents a complete discussion of both ascending and descending flights, including gliding. Some original remarks are made about the parameters of gliding. It shows how to construct tables of parameters allowing to identify rapidly flyable trajectories. Sample calculations are shown for the Cessna 182 and a Silver Fox like unmanned aerial vehicle.

• 한국정밀공학회지
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• 제27권1호
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• pp.76-83
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• 2010

There have been many studies regarding development of autonomous excavation system which is helpful in construction sites where repetitive jobs are necessary. Unfortunately, bucket trajectory planning was excluded from the previous studies. Since, the best use of excavator is to dig efficiently; purpose of this research was set to determine an optimized bucket trajectory in order to get best digging performance. Among infinite ways of digging any given path, criterion for either optimal or efficient bucket moves is required to be established. One method is to adopt work know-how from experienced excavator operator; However the work pattern varies from every worker to worker and it is hard to be analyzed. Thus, other than the work pattern taken from experienced operator, we developed an efficiency model to solve this problem. This paper presents a method to derive a bucket trajectory from optimization theory with empirical CLUB soil model. Path is greatly influenced by physical constraints such as geometry, excavator dimension and excavator workspace. By minimizing a energy function under these constraints, an optimal bucket trajectory could be obtained.

• 한국항공우주학회지
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• 제38권2호
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• pp.150-159
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• 2010

재진입 비행체의 Approach & Landing단계는 Steep Glideslope 단계, Circular Flare 단계, Flare Maneuver 단계로 이루어지며, 본 논문에서는 실시간 경로 생성을 위하여 기하학적 조건을 이용한 기준궤적 생성 알고리즘을 사용하였다. 이를 통하여 재진입비행체의 착륙 안정성을 고려한 기준궤적을 빠른 시간 안에 생성할 수 있다. 그리고 본 논문에서는 비선형 시스템에 대하여 강건성을 가지는 Mamdani Fuzzy PD Controller를 통한 종방향 및 횡방향 제어기를 설계하였다. 또한 Downrange 와 Crossrange의 초기 오차를 포함하는 시뮬레이션을 수행하여, 제안된 Fuzzy 제어기의 우수한 성능을 확인하였다.

• 제어로봇시스템학회논문지
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• 제11권1호
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• pp.58-66
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• 2005

Usual human gait can be modeled as continual impact phenomenon that happens due to the topological change of the kinematic structure of the two feet. The human being adapts his own control algorithm to minimize the ill effect due to the collision with the environment. In order to operate a Humanoid robot like the human being, it is necessary to understand the physics of the impact and to derive an analytical model of the impact. In this paper, specially, we focus on impact analysis of the kicking motion in playing soccer. At the instant of impact, the external impulse exerted on the ball by the foot is an important property. Initially, we introduce the complete external impulse model of the lower-extremity of the human body and analyze the external impulses for several kicking postures of the lower-extremity. Secondly, a trajectory-planning algorithm of a ball, in which the initial velocity and the launch angle of the ball are calculated for a desired trajectory of the ball, will be introduced. The aerodynamic effect such as drag force and lift force is also considered. We carry out numerical simulation and experimentation to verify the effectiveness of the proposed analytical methodology.

• EDISON SW 활용 경진대회 논문집
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• 제5회(2016년)
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• pp.389-396
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• 2016

In order to maximize the speed of Theo Jansen Mechanism in an given design space and prototyping material, the trajectory path was maximized according to several literature reviews, and the lower leg was elongated maximally in order to minimize the shift between support phase and transfer phase.

• International Journal of Aeronautical and Space Sciences
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• 제11권4호
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• pp.326-337
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• 2010

This work addresses problems regarding trajectory planning for unmanned aerial vehicle sensors. Such sensors are used for taking measurements of large nonlinear systems. The sensor investigations presented here entails methods for improving estimations and predictions of large nonlinear systems. Thoroughly understanding the global system state typically requires probabilistic state estimation. Thus, in order to meet this requirement, the goal is to find trajectories such that the measurements along each trajectory minimize the expected error of the predicted state of the system. The considerable nonlinearity of the dynamics governing these systems necessitates the use of computationally costly Monte-Carlo estimation techniques, which are needed to update the state distribution over time. This computational burden renders planning to be infeasible since the search process must calculate the covariance of the posterior state estimate for each candidate path. To resolve this challenge, this work proposes to replace the computationally intensive numerical prediction process with an approximate covariance dynamics model learned using a nonlinear time-series regression. The use of autoregressive time-series featuring a regularized least squares algorithm facilitates the learning of accurate and efficient parametric models. The learned covariance dynamics are demonstrated to outperform other approximation strategies, such as linearization and partial ensemble propagation, when used for trajectory optimization, in terms of accuracy and speed, with examples of simplified weather forecasting.