• Advanced Composite Materials
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• v.17 no.1
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• pp.1-23
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• 2008

Robotized filament winding technology involves a robot that winds a roving impregnated by resin on a die along the directions of stresses to which the work-piece is submitted in applications. The robot moves a deposition head along a winding trajectory in order to deposit roving. The trajectory planning is a very critical aspect of robotized filament winding technology, since it is responsible for both the tension constancy and the winding time. The present work shows two original rules to plan the winding trajectory of structural parts, whose shape is obtained by sweeping a full section around a 3D curve that must be closed and not crossing in order to assure a continuous winding. The first rule plans the winding trajectory by approximating the part 3D shape with straight lines; it is called the discretized rule. The second rule defines the winding trajectory simply by offsetting a 3D curve that reproduces the part 3D shape, of a defined distance; it is called the offset rule. The two rules have been compared in terms of roving tension and winding time. The present work shows how the offset rule enables achievement of both the required aims: to manufacture parts of high structural performances by keeping the tension on the roving near to the nominal value and to markedly decrease the winding time. This is the first step towards the optimization of the robotized filament winding technology.

• Advances in aircraft and spacecraft science
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• v.4 no.3
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• pp.237-267
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• 2017

Automatic trajectory re-planning is an integral part of unmanned aerial vehicle mission planning. In order to be able to perform this task, it is necessary to dispose of formulas or tables to assess the flyability of various typical flight segments. Notwithstanding their importance, there exist such data only for some particularly simple segments such as rectilinear and circular sub-trajectories. This article presents an analysis of a new, very efficient, way for an airplane to fly on an inclined circular trajectory. When it flies this way, the only thrust required is that which cancels the drag. It is shown that, then, much more inclined trajectories are possible than when they fly at constant speed. The corresponding equations of motion are solved exactly for the position, the speed, the load factor, the bank angle, the lift coefficient and the thrust and power required for the motion. The results obtained apply to both types of airplanes: those with internal combustion engines and propellers, and those with jet engines. Conditions on the trajectory parameters are derived, which guarantee its flyability according to the dynamical properties of a given airplane. An analytical procedure is described that ensures that all these conditions are satisfied, and which can serve for producing tables from which the trajectory flyability can be read. Sample calculations are shown for the Cessna 182, a Silver Fox like unmanned aerial vehicle, and an F-16 jet airplane.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.951-957
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• 1988

A collision-free trajectory planning algorithm is proposed to optimally coordinate two robots working in a common 3-D workspace. Each link of the two robots is modeled as a line segment and by their motion priority, one of the two robots is chosen as the master and the other the slave. And the one-step-ahead minimum distance between the two robots is computed by moving the master to the next location on its specified trajectory. Then the nominal trajectory of the slave is modified such that the distance between the next locations of the master and the slave must be larger than a prespecified allowable minimum distance. Here the weighted sum of the trajectory error and the joint motions of the slave is minimized by using the linear programming technique under the constraints that joint angle and velocity limits are not violated. To show the validity of the proposed algorithm, a numerical example is illustrated by employing a two dof's and a three dof's planar robots.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.627-634
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• 1989

A collision-free trajectory planning algorithm using the iterative learning concept is proposed for dual robot arms in a 3-D workspace to accurately follow their specified paths with constant velocities. Specifically, a collision-free trajectory minimizing the trajectory error is obtained first by employing the linear programming technique. Then the total operating time is iteratively adjusted based on the maximum trajectory error of the previous iteration so that the collision-free trajectory has no deviation from the specified path and also the operating time is near-minimal.

• 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 Society of Marine Environment & Safety
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• v.29 no.3
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• pp.281-287
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• 2023

Establishing a ship's passage plan is an essential step before it starts to sail. The research related to the automatic generation of ship passage plans is attracting attention because of the development of maritime autonomous surface ships. In coastal water navigation, the land, islands, and navigation rules need to be considered. From the path planning algorithm's perspective, a ship's passage planning is a global path-planning problem. Because conventional global path-planning methods such as Dijkstra and A^* are time-consuming owing to the processes such as environmental modeling, it is difficult to modify a ship's passage plan during a voyage. Therefore, the D^* algorithm was used to address these problems. The starting point was near Busan New Port, and the destination was Ulsan Port. The navigable area was designated based on a combination of the ship trajectory data and grid in the target area. The initial path plan generated using the D^* algorithm was analyzed with 33 waypoints and a total distance of 113.946 km. The final path plan was simplified using the Douglas-Peucker algorithm. It was analyzed with a total distance of 110.156 km and 10 waypoints. This is approximately 3.05% less than the total distance of the initial passage plan of the ship. This study demonstrated the feasibility of automatically generating a path plan in coastal navigation for maritime autonomous surface ships using the D^* algorithm. Using the shortest distance-based path planning algorithm, the ship's fuel consumption and sailing time can be minimized.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.593-597
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• 1993

This paper introduces robust trajectory planner for obstacle and singularity avoidance in a nonresonant robot manipulator. In this work, we propose new trajectory generator in cartesian space by use of Bezier function. Also, SR-inverse is used for obstacle and singularity avoidance of nonredundant robot. This result is verified with 3-D simulator which has been developed to examine the effectiveness of the suggested method.

• The Journal of Korea Robotics Society
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• v.18 no.2
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• pp.143-154
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• 2023

In this study, a fast motion planning method for the swing motion of a 6x6 wheel-legged robot to traverse large obstacles and gaps is proposed. The motion planning method presented in the previous paper, which was based on trajectory optimization, took up to tens of seconds and was limited to two-dimensional, structured vertical obstacles and trenches. A deep neural network based on one-dimensional Convolutional Neural Network (CNN) is introduced to generate keyframes, which are then used to represent smooth reference commands for the six leg angles along the robot's path. The network is initially trained using the behavioral cloning method with a dataset gathered from previous simulation results of the trajectory optimization. Its performance is then improved through reinforcement learning, using a one-step REINFORCE algorithm. The trained model has increased the speed of motion planning by up to 820 times and improved the success rates of obstacle crossing under harsh conditions, such as low friction and high roughness.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.1029-1036
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• 2011

An energy-efficient reference walking trajectory generation algorithm is suggested utilizing allowable ZMP (Zero-Moment-Point) region, which maxmizes the energy efficiency for cyclic gaits, based on three-dimensional LIPM (Linear Inverted Pendulum Model) for biped robots. As observed in natural human walking, variable ZMP manipulation is suggested, in which ZMP moves within the allowable region to reduce the joint stress (i.e., rapid acceleration and deceleration of body), and hence to reduce the consumed energy. In addition, opimization of footstep planning is conducted to decide the optimal step-length and body height for a given forward mean velocity to minimize a suitable energy performance - amount of energy required to carry a unit weight a unit distance. In this planning, in order to ensure physically realizable walking trajectory, we also considered geometrical constraints, ZMP stability condition, friction constraint, and yawing moment constraint. Simulations are performed with a 12-DOF 3D biped robot model to verify the effectiveness of the proposed method.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.1
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• pp.69-77
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• 1991

A collision-free trajectory planning algorithm using an iterative learning concept is proposed for dual robot arms in a 3-D common workspace to accurately follow their specified paths with constant velocities. Specifically, a collision-free trajectory minimizing the trajectory error is obtained first by employing the linear programming technique. Then the total operating time is iteratively adjusted based on the maximum trajectory error of the previous iteration so that the collision-free trajectory has no deviation from the specified path and also that the operating time is near-minimal. To show the validity of the proposed algorithm, a numerical example is presented based on two planar robots.