• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2492-2497
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• 2003

This paper presents optimal walking trajectory generation for a quadruped robot with genetic-fuzzy algorithm. In order to move a quadruped robot smoothly, both generations of optimal leg trajectory and free walking are required. Generally, making free walking is difficult to realize for a quadruped robot, because the patterned trajectory may interfere in the free walking. In this paper, we suggest the generation method for the leg trajectory satisfied with free walking pattern so as to avoid obstacle and walk smoothly. We generate via points of leg with respect to body motion, and then we use the genetic-fuzzy algorithm to search for the optimal via velocity and acceleration information of legs. All these methods are verified with PC simulation program, and implemented to SERO-V robot.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.450-453
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• 2002

This paper is concerned with smooth walking robot using genetic algorithm. The new walking algorithm is proposed and we simulated and experimented the algorithm. We suggested the leg trajectory algorithm and balancing trajectory algorithm by applying genetic algorithm. First the leg trajectory algorithm generated the smooth trajectory. Also the balancing trajectory generated the optimal trajectory. We compared results with the previous walking algorithm. It showed that the new proposed algorithm generated the better walking trajectory.

• Journal of Mechanical Science and Technology
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• 제20권5호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.169-172
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• 2002

This paper is concerned with walking trajectory generation by applying the genetic algorithm. The walking trajectory is generated though three via-points and genetic algorithm is employed to find velocity and acceleration at each via-point. Also genetic algorithm is applied for balancing joint trajectory. Fitness function is used for minimizing the trajectory. As a result, new algorithm generated the smooth trajectory. The proposed algorithm is verified by the experiment of biped walking robot developed in our Control laboratory, and we compared the result with the previous walking algorithm. It showed that the new proposed algorithm generated the better walking trajectory.

• 동력기계공학회지
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• 제21권5호
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• pp.41-47
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• 2017

To implement Argentina tango dancer-like walking of the humanoid robot, a new trajectory generation scheme based on particle swarm optimization of the blending polynomial is presented. Firstly, the characteristics of Argentina tango walking are derived from observation of tango dance. Secondly, these are reflected in walking pose conditions and cost functions of particle swarm optimization to determine the coefficients of blending polynomial. For the stability of biped walking, zero moment point and reference trajectory of swing foot are also included in cost function. Thirdly, after tango walking cycle is divided into 3 stages with 2 postures, optimal trajectories of ankles, knees and hip of lower body, which include 6 sagittal and 4 coronal angles, are derived in consequence of optimization. Finally, the feasibility of the proposed scheme is validated by simulating biped walking of humanoid robot with derived trajectories under the 3D Simscape environment.

• 로봇학회논문지
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• 제8권2호
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• pp.92-103
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• 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.

• 한국정밀공학회지
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• 제23권7호
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• pp.84-92
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• 2006

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 battery to move autonomously. But a humanoid robot needs more electric power in order to drive many joints. So, if movements of walking joint don't maintain optimally, it is hard to sustain the battery power during the working period. Also, if a gait trajectory doesn't have optimal state, the expected lift span of joints tends to be decreased. Also, if a gait trajectory doesn't have optimal state, the expected lift 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 PC-based program, the optimal solution could be obtained from the simulation. In addition, we discuss the design consideration fur the joint motion and distributed computation of tile humanoid, ISHURO, and suggest its result such as structure of the network and a disturbance observer.

• 한국정밀공학회지
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• 제15권3호
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• pp.157-167
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• 1998

In this paper it is purpose that reduces joint torques and their rate of change through optimizing trajectory planning of biped walking machine. The motion of biped walking machine is divided into leg motion for walking and body motion for keeping balance. The leg motion is planned by three phases, that are deploy, swing, and place phases, in terms of the state of foot against floor. The distribution of time assigned to each phase is optimized and that causes leg joint torques and their rate of change to minimize. The body notion is produced by using optimal control theory which minimizes body joint torques and satisfies Z.M.P. constraints defined as region of each phase.

• Journal of Mechanical Science and Technology
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• 제19권spc1호
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• pp.452-460
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• 2005

Based on an introduced optimal trajectory planning method, this paper mainly deals with the accuracy analysis during the function approximation process of the optimal trajectory planning method. The basis functions are composed of Hermit polynomials and Fourier series to improve the approximation accuracy. Since the approximation accuracy is affected by the given orders of each basis function, the accuracy of the optimal solution is examined by changing the combinations of the orders of Hermit polynomials and Fourier series as the approximation basis functions. As a result, it is found that the proper approximation basis functions are the $5^{th}$ order Hermit polynomials and the $7^{th}-10^{th}$ order of Fourier series.

• 한국정밀공학회지
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• 제21권7호
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• pp.115-123
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• 2004

This paper deals with the gait optimization of via points on biped robot. ZMP(Zero Moment point) is the most important index in a biped robot's dynamic walking stability. To stable walking of a biped robot, leg's trajectory and a desired ZMP trajectory is required, balancing motion is solved by FDM(Finite Difference Method). In this paper, optimal index is defined to dynamically stable walking of a biped robot, and genetic algorithm is applied to optimize gait trajectory and balancing motion of a biped robot. By genetic algorithm, the index of walking parameter is efficiently optimized, and dynamic walking stability is verified by ZMP verification equation. Genetic algorithm is only applied to balancing motion, and is totally applied to whole trajectory. All of the suggested motions of biped robot are investigated by simulations and verified through the real implementation.