• Journal of Institute of Control, Robotics and Systems
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• v.19 no.7
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• pp.599-604
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• 2013

Path planning of mobile robots has a purpose to design an optimal path from an initial position to a target point. Minimum driving time, minimum driving distance and minimum driving error might be considered in choosing the optimal path and are correlated to each other. In this paper, an efficient driving trajectory is planned in a real situation where a mobile robot follows a moving object. Position and distance of the moving object are obtained using a web camera, and the rotation angular and linear velocities are estimated using Kalman filters to predict the trajectory of the moving object. Finally, the mobile robot follows the moving object using a single curvature trajectory by estimating the trajectory of the moving object. Using the estimation by Kalman filters and the single curvature in the trajectory planning, the total tracking distance and time saved amounts to about 7%. The effectiveness of the proposed algorithm has been verified through real tracking experiments.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.3
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• pp.143-148
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• 2001

A lot of robot trajectory tracking methods are proposed to enhance the tracking error, but irregular tracking errors are always accompanied and very hard to reduce it. Up to now, these irregular tracking errors are reduced by introducing more complicated control algorithms. But, it is intuitively obvious to reduce only the big errors selectively in the irregular ones for the better performance instead of using more complicated control algorithms. By the characteristics of the robot, big tracking errors of the end-effector are generated mostly due to the fast moving of joint. So, in this paper, we introduce a new method which reduce the big tracking errors by clippings the joint velocity with the constraint of given path. Using this method, desired trajectory tracking is obtained within the far reduced error bound. Also, this method is successfully applied to generate the path-constrained error reducing trajectories for 2-axis SCARA type robot.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.52-57
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• 2014

This paper presents an implementation of a smooth path planning method considering physical limits on a real time operating system for a two-wheel mobile robot. A Bezier curve is utilized to make a smooth path considering a robot's position and direction angle through the defined path. A convolution operator is used to generate the center velocity trajectory to travel the distance of the planned path while satisfying the physical limits. The joint space velocity is computed to drive the two-wheel mobile robot from the center velocity. Trajectory planning, velocity command according to the planned trajectory, and monitoring of encoder data are implemented with a multi-tasking system. And the synchronization of tasks is performed with a real-time mechanism of Event Flag. A real time system with multi-tasks is implemented and the result is compared with a non-real-time system in terms of path tracking to the designed path. The result shows the usefulness of a real-time multi-tasking system to the control system which requires real-time features.

• 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.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.4
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• pp.374-385
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• 2015

In this paper, effective and user friendly CAM software is presented that automatically generates any three dimensional complex toolpaths according to a CAD drawing. In advanced manufacturing, often it is essential to scan the sample following a complex trajectory which consists of short (few microns) and multidirectional moves. The reported CAM software offers constant velocity for all short trajectory elements and provides an efficient shift of tool path direction in sharp corners of a tool trajectory, which is vital for any laser, based precision machining. The software also provides fast modification of tool path, automatic and efficient sequencing of path elements in a complicated tool trajectory, location of reference point and automatic fixing of geometrical errors in imported drawing exchange files (DXF) or DWG format files.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1402-1407
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• 2004

Moving a fragile object from an initial point to a goal location in minimum time without damage is pursued in this paper. In order to achieve the goal, first of all, the range of maximum acceleration and velocity are specified, which the manipulator can generate dynamically on the path that is planned a priori considering the geometrical constraints. Later, considering the impulsive force constraint of the object, the range of maximum acceleration and velocity are going to be obtained to keep the object safe while the manipulator is carrying it along the curved path. Finally, a time-optimal trajectory is planned within the maximum allowable range of the acceleration and velocity. This time optimal trajectory planning can be applied for real applications and is suitable for not only a continuous path but also a discrete path.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.12
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• pp.1238-1243
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• 2008

This paper presents an HILS(Hardware in the Loop Simulations) based experimental study for the UAV's flight trajectory planning/generation algorithms and guidance/control laws. For the various mission that is loaded on each waypoint, proper trajectory planning and generation algorithms are applied to achieve best performances. Specially, the 'smoothing path' generation and the 'tangent orbit path' guidance laws are presented for the smooth path transitions and in-circle loitering mission, respectively. For the control laws that can minimize the effects of side wind, side slip angle($\beta$) feedback to the rudder scheme is implemented. Finally, being implemented on real hardwares, all the proposed algorithms are validated with integrations of hardware and software altogether via HILS.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.2
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• pp.145-153
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• 2006

An optimal capturing trajectory for a moving object is proposed in this paper based on the observation that a single-curvature path is more accurate than double-or triple-curvature paths. Moving distance, moving time, and trajectory error are major factors considered in deciding an optimal path for capturing the moving object. That is, the moving time and distance are minimized while the trajectory error is maintained as small as possible. The three major factors are compared for the single and the double curvature trajectories to show superiority of the single curvature trajectory. Based upon the single curvature trajectory, a kinematics model of a mobile robot is proposed to follow and capture the moving object, in this paper. A capturing scenario can be summarized as follows: 1. Motion of the moving object has been captured by a CCD camera., 2. Position of the moving object has been estimated using the image frames, and 3. The mobile robot tries to follow the moving object along the single curvature trajectory which matches positions and orientations of the moving object and the mobile robot at the final moment. Effectiveness of the single curvature trajectory modeling and capturing algorithm has been proved, through simulations and real experiments using a 2-DOF wheel-based mobile robot.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.1
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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.