• Journal of the Korean Society for Precision Engineering
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• v.15 no.1
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• pp.78-86
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• 1998

This paper presents a numerical method of the minimum-time trajectory planning for a robot manipulator amid obstacles. Each joint displacement is represented by the linear combination of the finite-term quintic B-splines which are the known functions of the path parameter. The time is represented by the linear function of the same path parameter. Since the geometric path is not fixed and the time is linear to the path parameter, the coefficients of the splines and the time-scale factor span a finite-dimensional vector space, a point in which uniquely represents the manipulator motion. The displacement, the velocity and the acceleration conditions at the starting and the goal positions are transformed into the linear equality constraints on the coefficients of the splines, which reduce the dimension of the vector space. The optimization is performed in the reduced vector space using nonlinear programming. The total moving time is the main performance index which should be minimized. The constraints on the actuator forces and that of the obstacle-avoidance, together with sufficiently large weighting coefficients, are included in the augmented performance index. In the numerical implementation, the minimum-time motion is obtained for a planar 3-1ink manipulator amid several rectangular obstacles without simplifying any dynamic or geometric models.

• ICROS
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• v.1 no.1
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• pp.16-16
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• 1995

Like the usual systems, the industrial robot manipulator has some constraints for motion. Usually we hope that the manipulators move fast to accomplish the given task. The problem can be formulated as the time-optimal control problem under the constraints such as the limits of velocity, acceleration and jerk. But it is very difficult to obtain the exact solution of the time-optimal control problem. This paper solves this problem in two steps. In the first step, we find the minimum time trajectories by optimizing cubic polynomial joint trajectories under the physical constraints using the modified evolution strategy. In the second step, the controller is optimized for robot manipulator to track precisely the optimized trajectory found in the previous step. Experimental results for SCARA type manipulator show that the proposed method is very useful.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.16-20
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• 1999

Like the usual systems, the industrial robot manipulator has some constraints for motion. Usually we hope that the manipulators move fast to accomplish the given task. The problem can be formulated as the time-optimal control problem under the constraints such as the limits of velocity, acceleration and jerk. But it is very difficult to obtain the exact solution of the time-optimal control problem. This paper solves this problem in two steps. In the first step, we find the minimum time trajectories by optimizing cubic polynomial joint trajectories under the physical constraints using the modified evolution strategy. In the second step, the controller is optimized for robot manipulator to track precisely the optimized trajectory found in the previous step. Experimental results for SCARA type manipulator show that the proposed method is very useful.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.1
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• pp.89-94
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• 2013

Electro Otical Tracking System(EOTS) is required for a rapid movement as well as the stabilization of Line-Of-Sight(LOS). In order to achieve these two goals, this paper presents a position and velocity driving profile generation method from the constant acceleration and deceleration profile according to the current state, enabling a fast and smooth trajectory even if the target position changes during the movement of LOS. Simulation and experimental results reveal that the settling time could be reduced significantly by adopting the present position control scheme.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.5
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• pp.357-368
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• 1991

Collision-free trajectory planning for two robots is considered. The two robot system handled in the paper is given specified geometric paths for two robots, and the task is repeating. Then, the robot dynamics is transformed as a function of the traveled lengths along the paths, and the bounds on acceleration and velocity are described in the phase plane be taking the constraints on torques and joint velocities into consideration. Collision avoidance and time optimality are considered simultaneously in the coordination space and the phase plane, respectively. The proof for the optimality of the proposed algorithm is given, and a simulation result is included to show the usefulness of the proposed method.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.119-124
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• 2005

Decision of operation performance mode to minimize the energy consumption of urban rail vehicle. This paper analyses how much acceleration and deceleration of urban rail vehicle should be applied andhow to choose an operation mode to minimize energy consumption when train runs between station within the fixed operation time. The decided operation pattern satisfying the minimum energy consumption becomes a target trajectory and a basis for the controller design criteria. To make this goal it grasps the characteristics of urban rail vehicle, realize operation energy model of urban rail vehicle and verify the accuracy of embodied model the Matlab simulation with the same operation result of real route. It searches for operation pattern to minimize operation energy by changing the acceleration and deceleration on the imaginative route and proposes operation pattern minimizing energy consumption by applying real operation data between Dolgogee-Sukgye section of Seoul Metropolitan Subway Line 6.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.1
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• pp.56-64
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• 2013

We propose an efficient minimum-time cornering motion planning algorithms for differential-driven wheeled mobile robots with motor control input constraint, under piecewise constant control input sections. First, we established mobile robot's kinematics and dynamics including motors, divided the cornering trajectory for collision-free into one translational section, followed by one rotational section with angular acceleration, and finally the other rotational section with angular deceleration. We constructed an efficient motion planning algorithm satisfying the bang-bang principle. Various simulations and experiments reveal the performance of the proposed algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.4
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• pp.2370-2378
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• 2015

This paper proposes an algorithm using Lagrange interpolation method to realize trajectory planning for torque minimization of robot manipulators. For the algorithm, position constraints of robot manipulators should be given and the stability of robot manipulators should be satisfied. In order to avoid Runge's phenomenon, we set up time interpolation points using Chebyshev interpolation points. After that, we found suitable angle which corresponds to the points and then we got trajectories of joint's angle, velocity, acceleration using Lagrange interpolation method. We selected performance index for torque consumption optimization of robot manipulator. The method went through repetitive computation process to have minimum value of the performance index by calculated trajectory. Through the process, we could get optimized trajectory to minimize torque and performance index and guarantee safety of the motion for manipulator performance.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.1
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• pp.38-48
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• 2007

this paper analyses how much acceleration and deceleration of urban rail vehicle should be applied and how to choose an operation mode to minimize energy consumption when train runs between stations within the fixed operation time. The decided operation pattern satisfying the minimum energy consumption becomes a target trajectory and a basis for the controller design criteria. To make this goal it grasps the characteristics of urban rail vehicle, realize operation energy model of urban rail vehicle and verity the accuracy of embodied model the Matlab simulation with the same operation result of real route. It searches for operation pattern to minimize operation energy by changing the acceleration and deceleration on the imaginative route and proposes operation pattern minimizing energy consumption by applying real operation data between stations of Seoul Metropolitan Subway Line 6.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.330-339
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• 2008

Ground-based interceptors(GBI) comprise a major element of the strategic defense against hostile targets like Intercontinental Ballistic Missiles(ICBM) and reentry vehicles(RV) dispersed from them. An optimum design of the subsystems is required to increase the performance and reliability of these GBI. Propulsion subsystem design and optimization is the motivation for this effort. This paper describes an effort in which an entire GBI missile system, including a multi-stage solid rocket booster, is considered simultaneously in a Genetic Algorithm(GA) performance optimization process. Single goal, constrained optimization is performed. For specified payload and miss distance, time of flight, the most important component in the optimization process is the booster, for its takeoff weight, time of flight, or a combination of the two. The GBI is assumed to be a multistage missile that uses target location data provided by two ground based RF radar sensors and two low earth orbit(LEO) IR sensors. 3Dimensional model is developed for a multistage target with a boost phase acceleration profile that depends on total mass, propellant mass and the specific impulse in the gravity field. The monostatic radar cross section (RCS) data of a three stage ICBM is used. For preliminary design, GBI is assumed to have a fixed initial position from the target launch point and zero launch delay. GBI carries the Kill Vehicle(KV) to an optimal position in space to allow it to complete the intercept. The objective is to design and optimize the propulsion system for the GBI that will fulfill mission requirements and objectives. The KV weight and volume requirements are specified in the problem definition before the optimization is computed. We have considered only continuous design variables, while considering discrete variables as input. Though the number of stages should also be one of the design variables, however, in this paper it is fixed as three. The elite solution from GA is passed on to(Sequential Quadratic Programming) SQP as near optimal guess. The SQP then performs local convergence to identify the minimum mass of the GBI. The performance of the three staged GBI is validated using a ballistic missile intercept scenario modeled in Matlab/SIMULINK.