• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.689-693
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• 1996

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.361-364
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• 1997

The re-enty guidance design involves trajectory optimization, generation of a reference drag acceleration profile with the satisfaction of trajectory constraints. This reference drag acceleration profile can be considered as the reference trajectory. This paper proposes the atmospheric re-entry system which is composed of longitudinal, later and range control. This paper shows the a performance of a re-entry guidance and control system using feedback linearization control and predictive control.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.4 s.175
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• pp.1007-1015
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• 2000

This paper proposes an adaptive trajectory generation strategy of using on-line ZMP information and an impedance control method for biped robots. Since robots experience various disturbances during their locomotion, their walking mechanism should have the robustness against those disturbances, which requires an on-line adaptation capability. In this context, an on-line trajectory planner is proposed to compensate the required moment for recovering stability. The ZMP equation and sensed ZMP information are used in this trajectory generation strategy. In order to control a biped robot to be able to walk stably, its controller should guarantee stable footing at the moment of feet contacts with the ground as well as maintaining good trajectory tracking performance. Otherwise, the stability of robot will be significantly compromised. To reduce the magnitude of an impact and guarantee a stable footing when a foot contacts with the ground, this paper. proposes to increase the damping of the leg drastically and to modify the reference trajectory of the leg. In the proposed control scheme, the constrained leg is controlled by impedance control using the impedance model with respect to the base link. Computer simulations performed with a 3-dof environment model that consists of combination of a nonlinear and linear compliant contact model show that the proposed controller performs well and that it has robustness against unknown uneven surface. Moreover, the biped robot with the proposed trajectory generator can walk even when it is pushed with a certain amount of external force.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.101-106
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• 2003

In the area of tracking control, it is important to design not only the controllers but also the trajectories to which a system has to follow. $5^{th}$ order polynomial is often used with constraints of initial and final states. Smooth ending with possible minimum time is important for many systems because of vibration or jerky motions. Examples are increased with development of technology in smaller, more accurate systems. On the base of a polynomial like trajectory generation method from a paper in ACC2002 and RIC(Robust Internal-loop Compensator) control scheme of Robotics and Bio-mechanics lab. of POSTECH, generalized and expanded polynomial like trajectory generation method is showed.

• International Journal of Aeronautical and Space Sciences
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• v.8 no.2
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• pp.107-120
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• 2007

Coordination of multiple UAVs is an essential technology for various applications in robotics, automation, and artificial intelligence. In general, it includes 1) waypoints assignment and 2) trajectory generation. In this paper, we propose a new method for this problem. First, we modify the concept of the standard visibility graph to greatly improve the optimality of the generated trajectories and reduce the computational complexity. Second, we propose an efficient stochastic approach using simulated annealing that assigns waypoints to each UAV from the constructed visibility graph. Third, we describe a method to detect collision between two UAVs. FinallY, we suggest an efficient method of controlling the velocity of UAVs using A* algorithm in order to avoid inter-UAV collision. We present simulation results from various environments that verify the effectiveness of our approach.

• 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 Mechanical Science and Technology
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• v.20 no.5
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• pp.612-620
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• 2006

This paper proposes an optimal trajectory generation method for biped robots for walking up-and-down stairs using a Real-Coded Genetic Algorithm (RCGA). The RCGA is most effective in minimizing the total consumption energy of a multi-dof biped robot. Each joint angle trajectory is defined as a 4-th order polynomial of which the coefficients are chromosomes or design variables to approximate the walking gait. Constraints are divided into equalities and inequalities. First, equality constraints consist of initial conditions and repeatability conditions with respect to each joint angle and angular velocity at the start and end of a stride period. Next, inequality constraints include collision prevention conditions of a swing leg, singular prevention conditions, and stability conditions. The effectiveness of the proposed optimal trajectory is shown in computer simulations with a 6-dof biped robot model that consists of seven links in the sagittal plane. The optimal trajectory is more efficient than that generated by the Modified Gravity-Compensated Inverted Pendulum Mode (MGCIPM). And various trajectories generated by the proposed GA method are analyzed from the viewpoint of the consumption energy: walking on even ground, ascending stairs, and descending stairs.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.7 s.172
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• pp.112-121
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• 2005

This paper is concerned with smooth trajectory generation of biped robot which has inverted pendulum type balancing weight. Genetic algorithm is used to generate the trajectory of the leg and balancing weight. Balancing trajectory can be determined by solving the second order differential equation under the condition that the reference ZMP (Zero moment point) is settled. Reference ZMP effect on gait pattern absolutely but the problem is how to determine the reference ZMP. Genetic algorithm can find optimal solution under the high order nonlinear situation. Optimal trajectory is generated when use genetic algorithm which has some genes and a fitness function. In this paper, minimization of balancing joints motion is used for the fitness function and set the weight factor of the two balancing joints at the fitness function. Inverted pendulum type balancing weight is very similar with human and this model can be used fur humanoid robot. Simulation results show ZMP trajectory and the walking experiment made on the real biped robot IWR-IV.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.75-76
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• 2008

In oder for the robot to walk with stability, trajectory generation method for the biped robot is important. In this paper proposed the genetic algorithm to optimize biped robot motion parameters. Because most of trajectory generation, the walking parameters determined arbitrarily. Formulating the constraints of the motion parameters, and the trajectory is derived by cubic spline function. Finally walking patterns are described through simulation studies. When the ZMP(zero moment point) and DSM(dynamic stability margin) are satisfied, the walking pattern is chosen.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.65-68
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• 1995

This paper describes trajectory generation of a riobot arm by self-organizing neural networks. These neural networks are based on competitive learning without a teacher and this algorithm which is suitable for problems in which solutions as teaching signal cannot be defined-e.g. inverse dynamics analysis-is adopted to the trajectory generation problem of a robot arm. Utility of unsupervised learning algorithm is confirmed by applying the approximated solution of each joint calculated through learning to an actual robot arm in giving the experiment of tracking for reference trajectory.