• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.369-374
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• 2014

Path generation methods are required for safe and efficient driving in unmanned autonomous vehicles. There are two kinds of paths: global and local. A global path consists of all the way points including the source and the destination. A local path is the trajectory that a vehicle needs to follow from a way point to the next in the global path. In this paper, we propose a novel method for local path generation through machine learning, with an effective curve function used for initializing the trajectory. First, reinforcement learning is applied to a set of candidate paths to produce the best trajectory with maximal reward. Then the optimal steering angle with respect to the trajectory is determined by training an artificial neural network. Our method outperformed existing approaches and successfully found quality paths in various experimental settings, including the cases with obstacles.

• Journal of Ocean Engineering and Technology
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• v.28 no.6
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• pp.560-565
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• 2014

In this study, the problem of trajectory optimization for underwater gliders considering depth constraints is discussed. Typically, underwater gliders are controlled to dive and climb in a saw-tooth pattern at constant gliding angles. This approach is effective and close to optimal for deep water applications. However, the optimal path deviates from the saw-tooth path in shallow water conditions. This study focuses on finding more efficient gliding paths that can minimize the traverse time in the horizontal plane when the water depth is limited. The trajectory optimization problem is formulated into a minimum time control problem with inequality path constraints and hydrodynamic drag effects. A numerical approach based on the pseudo-spectral method is adopted as a solution approach, and the simulation results are presented.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1701-1704
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• 2005

We developed an machine vision method for navigation control of a traveling automatic guided vehicle(AGV) on desired trajectory with guided marks. The formulated EDF accumulates the edge magnitude for edge directions. The EDF has distinctive peak points at the vicinity of trajectory directions due to the directional and the positional continuities of desired trajectory. Examining the EDF by its shape parameters of the local maxima and symmetry axis results in identifying whether or not change in traveling direction of an AGV has occurred. Simulation results show that the presented method is useful for navigation control of AGV.

• Advances in aircraft and spacecraft science
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• v.5 no.5
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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.

• Journal of Mechanical Science and Technology
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• v.20 no.8
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• pp.1159-1168
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• 2006

In this paper, a new revolute mobile robot arm with five degree of freedom (d.o.f) was developed for autonomous moving robots. As a control system for the robot arm, a distributed control system composed of the main controller and five motor controllers for arm joints was developed. The main controller and the motor controllers w ε re developed using the ARM microprocessor and the TMS320c2407 microprocessor, respectively. A new trajectory tracking algorithm for the motor controllers was devised employing pre-generated off-line trajectory data. Also, a 3-D simulator based on the openGL software to simulate the motion of the robot arm was developed. To validate the performance of the robot system, experiments to track a specified trajectory were performed.

• The Journal of Korea Robotics Society
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• v.18 no.2
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• pp.155-163
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• 2023

Auto Guided Vehicle (AGV) equipped with mecanum wheels can move in all directions, unlike ordinary wheeled AGVs. In this paper, we propose a robust trejectory tracking control method for the mecanum wheeled AGVs in the presence of disturbances. It is constructed by combining impedance control with Integral Sliding Mode Control (ISMC), which shows robust performance against disturbances, and adding a disturbance observer (DOB) that estimates and removes disturbances. Simulation result using MATLAB/SIMULINK shows that the proposed control method has robust performance in tracking the reference trajectory under the circumstance with disturbance. The control performance is further improved when the disturbance observer is additionally used. In addition, the performance of the proposed control method was verified through experiment. It shows the result of tracking the set trajectory well.

• Journal of Navigation and Port Research
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• v.42 no.2
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• pp.87-96
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• 2018

A trajectory control system plays an important role in controlling motions of marine vehicle when a series of way points or a path is given. In this paper, a sliding mode control (SMC)-based trajectory tracking controller for marine vehicles is presented. A small-sized unmanned ship is considered as a control object. Both speed and heading angle of a ship should be controlled for tracking control. The common point of related researches was to separate ship's speed and heading angle in control methods. In this research, a new control law from a general sliding mode theory that can be applied to MIMO (multi input multi output) system is derived and both speed and heading angle of a ship can be controlled simultaneously. The propulsion force and rudder force are also applied in modeling stage to achieve accurate simulation. Disturbance induced by wind is also tackled in the dynamics considering robustness of the proposed control scheme. In the simulation, we employed a way-point method to generate ship's trajectory and applied the proposed control scheme to ship's trajectory tracking control. Our results confirmed that the tracking error was converged to zero, thus demonstrating the effectiveness of the proposed method.

• Journal of Astronomy and Space Sciences
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• v.40 no.3
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• pp.123-129
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• 2023

This paper presents an analysis of the trans-lunar trajectory insertion performance of the Korea Pathfinder Lunar Orbiter (KPLO), the first lunar exploration spacecraft of the Republic of Korea. The successful launch conducted on August 4, 2022 (UTC), utilized the SpaceX Falcon 9 rocket from Cape Canaveral Space Force Station. The trans-lunar trajectory insertion performance plays a crucial role in ensuring the overall mission success by directly influencing the spacecraft's onboard fuel consumption. Following separation from the launch vehicle (LV), a comprehensive analysis of the trajectory insertion performance was performed by the KPLO flight dynamics (FD) team. Both orbit parameter message (OPM) and orbit determination (OD) solutions were employed using deep space network (DSN) tracking measurements. As a result, the KPLO was accurately inserted into the ballistic lunar transfer (BLT) trajectory, satisfying all separation requirements at the target interface point (TIP), including launch injection energy per unit mass (C3), right ascension of the injection orbit apoapsis vector (RAV), and declination of the injection orbit apoapsis vector (DAV). The precise BLT trajectory insertion facilitated the smoother operation of the KPLO's remainder mission phase and enabled the utilization of reserved fuel, consequently significantly enhancing the possibilities of an extended mission.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.4
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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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.1
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• pp.74-80
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• 2006

This paper addresses the trajectory optimization of Unmanned Aerial Vehicles(UAVs) under multiple ground threats like enemy's anti-air radar sites. The power of radar signal reflected by the vehicle and the flight time are considered in the performance cost to be minimized. The bank angle is regarded as control input for a 1st-order lag vehicle, and input parameter optimization method based on Sequential Quadratic Programming (SQP) is used for trajectory optimization. The proposed path planning method provides more practical trajectories with enhanced survivability than those of Voronoi diagram method.