• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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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.

• The Journal of Korea Robotics Society
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• v.6 no.4
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• pp.301-307
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• 2011

Based on the stability criteria of ZMP (Zero Moment Point), this paper proposes an adjusting algorithm that modifies walking trajectory of a bipedal robot for stable walking by analyzing ZMP trajectory of it. In order to maintain walking balance of the bipedal robot, ZMP should be located within a supporting polygon that is determined by the foot supporting area with stability margin. Initially tilting imposed to the trajectory of the upper body is proposed to transfer ZMP of the given walking trajectory into the stable region for the minimum stability. A neural network method is also proposed for the stable walking trajectory of the biped robot. It uses backpropagation learning with angles and angular velocities of all joints with tilting to get the improved walking trajectory. By applying the optimized walking trajectory that is obtained with the neural network model, the ZMP trajectory of the bipedal robot is certainly located within a stable area of the supporting polygon. Experimental results show that the optimally learned trajectory with neural network gives more stability even though the tilting of the pelvic joint has a great role for walking stability.

• Proceedings of the KIEE Conference
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• 2002.11c
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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.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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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.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.546-548
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• 1998

This paper deals with ZMP trajectory generation in multi step walking of IWR-III(Inha Walking Robot) Biped Walking Robot. Biped walking is realized by combining 6-types of pre-defined steps and the actual ZMP can be used as a stability index of a robot. For the good tracking of actual ZMP, desired ZMP trajectory is generated during the whole walking time not for each step. Trajectory generation is performed considering velocities and accelerations of given via points using 5-th order polynomial interpolation method. As a result, balancing joints have a more smooth and continuous motion and actual ZMP has a better tracking ability. Numerical simulator is done by MATLAB to guarantee the walking of a robot satisfying the ZMP stability.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.7
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• pp.659-667
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• 2011

The study of bipedal robot is towards similar shape and function with human. In this paper, we propose a human-like walking pattern compatible to the flexible foot with toe and heel structure. The new walking pattern for a bipedal robot consists of ZMP, center of mass (CoM), and ankle trajectory and is drawn by considering human kinesiology. First, the ZMP trajectory moves forward without stopping at a point even in the single support phase. The corresponding CoM trajectory to the ZMP one is derived by solving differential equations. As well, a CoM trajectory for the vertical axis is added by following the idea of human motion. The ankle trajectory closely mimics the rotational motion of human ankles during taking off and landing on the ground. The advantages of the proposed walking pattern are demonstrated by showing improved stability, decreased ankle torque, and the longer step length capability. Specifically, it is interesting to know that the vertical CoM motion is able to compensate for the initial transient response.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.7
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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.

• The Journal of Korea Robotics Society
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• v.8 no.2
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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.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.4 s.97
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• pp.138-147
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• 1999

For autonomous navigation, a legged robot should be able to walk over irregular terrain and adapt itself to variation of supporting surface. Walking through slope is one of the typical tasks for such case. Robot needs not only to change foot trajectory but also to adjust its configuration to the slope angle for maintaining stability against gravity. This paper suggests such adaptation algorithm for stable walking which uses feedback of reaction forces at feet. Adjusting algorithm of foot trajectory was studied with the estimated angel of slope without visual feedback. A concept of virtual slope angle was introduced to adjust body configuration against slope change of the supporting terrain. Regeneration of foot trajectory also used this concept for maintaining its stable walking against unexpected landing point.

• Journal of Power System Engineering
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• v.21 no.5
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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.