• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.1
• /
• pp.77-83
• /
• 2005

This paper deals with determination of motions of a humanoid robot using genetic algorithm. A humanoid robot has some problems of the structural instability basically. So, we have to consider the stable walking gait in gait planning. Besides, it is important to make the smoothly optimal gait for saving the electric power. A mobile robot has a battery to move autonomously. But a humanoid robot needs more electric power in order to drive many joints. So, if movements of walking joints don't maintain optimally, it is difficult for a robot to have working time for a long time. Also, if a gait trajectory doesn't have optimal state, the expected life span of joints tends to be decreased. To solve these problems, the genetic algorithm is employed to guarantee the optimal gait trajectory. The fitness functions in a genetic algorithm are introduced to find out optimal trajectory, which enables the robot to have the less reduced jerk of joints and get smooth movement. With these all process accomplished by a PC-based program, the optimal solution could be obtained from the simulation. In addition, we discuss the design consideration for the joint motion and distributed computation of the humanoid, ISHURO, and suggest its result such as the structure of the network and a disturbance observer.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.1181-1184
• /
• 1996

As usual systems, robot manipulators have also physical constraints for operating. It is a difficult problem that we operate manipulator in the minimal time under these constraints. In this paper, we solve this problem dividing it into two steps. In the first step, we find the minimal time trajectories by optimizing qubic polynomial joint trajectories using evolutionary algorithms. In the second step, we optimize controller for robot manipulator to track precisely trajectories optimized in the previous step.

• Advances in aircraft and spacecraft science
• /
• v.6 no.5
• /
• pp.391-407
• /
• 2019

Flight trajectory optimization has become an important factor not only to reduce the operational costs (e.g.,, fuel and time related costs) of the airliners but also to reduce the environmental impact (e.g.,, emissions, contrails and noise etc.) caused by the airliners. So far, these factors have been dealt with in the context of 2D and 3D trajectory optimization, which are no longer efficient. Presently, the 4D trajectory optimization is required in order to cope with the current air traffic management (ATM). This study deals with a cubic spline approximation method for solving 4D trajectory optimization problem (TOP). The state vector, its time derivative and control vector are parameterized using cubic spline interpolation (CSI). Consequently, the objective function and constraints are expressed as functions of the value of state and control at the temporal nodes, this representation transforms the TOP into nonlinear programming problem (NLP). The proposed method is successfully applied to the generation of a minimum length optimal trajectories along 4D waypoints, where the method generated smooth 4D optimal trajectories with very accurate results.

• 제어로봇시스템학회:학술대회논문집
• /
• 1990.10a
• /
• pp.394-399
• /
• 1990

We develop an automatic trajectory planning system (ATPS) for painting robots by proposing a new trajectory planning scheme. The new scheme considers geometric modeling, painting mechanics, and robot dynamics to output an optimal trajectory (in the sense of coating thickness and painting time) based on the CAD data describing the shape of objects, The new scheme is implemented in SUN/4 workstation to develop an ATPS for painting robots. To test the validity of the new scheme and to illustrate the developed system, numerous runs are performed and analyzed.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.6
• /
• pp.915-923
• /
• 2008

This paper focuses on optimal tuning of nonlinear parameters of a dual-input power system stabilizer(dual-input PSS), which can improve the system damping performance immediately following a large disturbance. Until recently, various PSS models have developed to bring stability and reliability to power systems, and some of these models are used in industry applications. However, due to non-smooth nonlinearities from the interaction between linear parameters(gains and time constants of linear controllers) and nonlinear parameters(saturation output limits), the output limit parameters cannot be determined by the conventional tuning methods based on linear analysis. Only ad hoc tuning procedures('trial and error' approach) have been used. Therefore, the steepest descent method is applied to implement the optimal tuning of the nonlinear parameters of the dual-input PSS. The gradient required in this optimization technique can be computed from trajectory sensitivities in hybrid system modeling with the differential-algebraic-impulsive-switched(DAIS) structure. The optimal output limits of the dual-input PSS are evaluated by time-domain simulation in both a single machine infinite bus(SMIB) system and a multi-machine power system in comparison with those of a single-input PSS.

• International Journal of Control, Automation, and Systems
• /
• v.6 no.2
• /
• pp.194-203
• /
• 2008

Iterative learning control (ILC) is a simple and effective method for the control of systems that perform the same task repetitively. ILC algorithm uses the repetitiveness of the task to track the desired trajectory. In this paper, we propose a PID (proportional plus integral and derivative) type ILC update law for control discrete-time single input single-output (SISO) linear time-invariant (LTI) systems, performing repetitive tasks. In this approach, the input of controlled system in current cycle is modified by applying the PID strategy on the error achieved between the system output and the desired trajectory in a last previous iteration. The convergence of the presented scheme is analyzed and its convergence condition is obtained in terms of the PID coefficients. An optimal design method is proposed to determine the PID coefficients. It is also shown that under some given conditions, this optimal iterative learning controller can guarantee the monotonic convergence. An illustrative example is given to demonstrate the effectiveness of the proposed technique.

• Proceedings of the KIEE Conference
• /
• 1993.07a
• /
• pp.395-398
• /
• 1993

This paper proposes an algorithm to find an optimal trajectory for unspecified paths of the tips of two arms of a dual arm robot. The effective handling a specified object of a dual arm robot closely depends on the effective collision avoidance between parts of robot and the object. For time optimal trajectory without collision, a graphical method is applied for a robot with two degree of freedom. The effectiveness of the proposed method is demonstrated by some simulation results.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.1
• /
• pp.358-377
• /
• 2015

In this paper, we propose a novel approach for trajectory recovery. Our system uses a triangulation procedure for skeletonization and graph theory to extract the trajectory. Skeletonization extracts the polyline skeleton according to the polygonal contours of the handwritten characters, and as a result, the junction becomes clear and the characters that are touching each other are separated. The approach for the trajectory recovery is based on graph theory to find the optimal path in the graph that has the best representation of the trajectory. An undirected graph model consisting of one or more strokes is constructed from a polyline skeleton. By using the polyline skeleton, our approach accelerates the process to search for an optimal path. In order to evaluate the performance, we built our own dataset, which includes testing and ground-truth. The dataset consist of thousands of handwritten characters and word images, which are extracted from five handwritten documents. To show the relative advantage of our skeletonization method, we first compare the results against those from Zhang-Suen, a state-of-the-art skeletonization method. For the trajectory recovery, we conduct a comparison using the Root Means Square Error (RMSE) and Dynamic Time Warping (DTW) in order to measure the error between the ground truth and the real output. The comparison reveals that our approach has better performance for both the skeletonization stage and the trajectory recovery stage. Moreover, the processing time comparison proves that our system is faster than the existing systems.

• IE interfaces
• /
• v.3 no.2
• /
• pp.23-38
• /
• 1990

The use of robots for painting operations is a powerful alternative as a means for automation and quality improvement. A typical method being used for motion planning of the painting robot is to guide the robot along the desired path : the "lead-through" method. Although this method is simple and has been widely used, it has several drawbacks a) The robot cannot be used during the teaching period, b) A human is exposed to a hostile environment, c) The motions taught are, at best, human's skill level. To deal with the above problems, an integrated robot-trajectory planning scheme is presented. The new scheme takes CAD data describing the shape and geometry of the objects, and outputs an optimal trajectory in the sense of coating thickness and painting time. The purpose of this paper is to investigate theoretical backgrounds for such a scheme including geometric modeling, painting mechanics and robot trajectory planning, and develop algorithms for generating spray gun paths and minimum-time robot trajectories. Future study is to implement these algorithms on an workstation to develop an integrated software system ; ATPS(Automatic Trajectory Planning System) for spray painting robots.

• The Journal of Korea Robotics Society
• /
• v.8 no.2
• /
• pp.92-103
• /
• 2013

Humanoid robot is the most intimate robot platform suitable for human interaction and services. Biped walking is its basic locomotion method, which is performed with combination of joint actuator's rotations in the lower extremity. The present work employs humanoid robot simulator and numerical optimization method to generate optimal joint trajectories for biped walking. The simulator is developed with Matlab based on the robot structure constructed with the Denavit-Hartenberg (DH) convention. Particle swarm optimization method minimizes the cost function for biped walking associated with performance index such as altitude trajectory of clearance foot and stability index concerning zero moment point (ZMP) trajectory. In this paper, instead of checking whether ZMP's position is inside the stable region or not, reference ZMP trajectory is approximately configured with feature points by which piece-wise linear trajectory can be drawn, and difference of reference ZMP and actual one at each sampling time is added to the cost function. The optimized joint trajectories realize three phases of stable gait including initial, periodic, and final steps. For validation of the proposed approach, a small-sized humanoid robot named DARwIn-OP is commanded to walk with the optimized joint trajectories, and the walking result is successful.