• Journal of Institute of Control, Robotics and Systems
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• v.16 no.10
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• pp.963-968
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• 2010

This paper handles ZMP based control that is inspired by neural networks for humanoid robot walking on varying sloped surfaces. Humanoid robots are currently one of the most exciting research topics in the field of robotics, and maintaining stability while they are standing, walking or moving is a key concern. To ensure a steady and smooth walking gait of such robots, a feedforward type of neural network architecture, trained by the back propagation algorithm is employed. The inputs and outputs of the neural network architecture are the ZMPx and ZMPy errors of the robot, and the x, y positions of the robot, respectively. The neural network developed allows the controller to generate the desired balance of the robot positions, resulting in a steady gait for the robot as it moves around on a flat floor, and when it is descending slope. In this paper, experiments of humanoid robot walking are carried out, in which the actual position data from a prototype robot are measured in real time situations, and fed into a neural network inspired controller designed for stable bipedal walking.

• The Journal of Korea Robotics Society
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• v.3 no.4
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• pp.287-299
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• 2008

People have expected a humanoid robot to move as naturally as a human being does. The natural movements of humanoid robot may provide people with safer physical services and communicate with persons through motions more correctly. This work presented a methodology to generate the natural motions for a humanoid robot, which are converted from human motion capture data. The methodology produces not only kinematically mapped motions but dynamically mapped ones. The kinematical mapping reflects the human-likeness in the converted motions, while the dynamical mapping could ensure the movement stability of whole body motions of a humanoid robot. The methodology consists of three processes: (a) Human modeling, (b) Kinematic mapping and (c) Dynamic mapping. The human modeling based on optimization gives the ZMP (Zero Moment Point) and COM (Center of Mass) time trajectories of an actor. Those trajectories are modified for a humanoid robot through the kinematic mapping. In addition to modifying the ZMP and COM trajectories, the lower body (pelvis and legs) motion of the actor is then scaled kinematically and converted to the motion available to the humanoid robot considering dynamical aspects. The KIST humanoid robot, Mahru, imitated a dancing motion to evaluate the methodology, showing the good agreement in the motion.

• Journal of Mechanical Science and Technology
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• v.20 no.5
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• pp.602-611
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• 2006

This paper proposes a locomotion pattern and a control method for biped robots with curved soles. First, since the contact point of a supporting leg may arbitrarily move back and forth on the ground, we derived the desired trajectory from a model called the Moving. Inverted Pendulum Model (MIPM) where the Zero Moment Point (ZMP) exists at the supporting point and can be moved intentionally. Secondly, a biped robot with curved soles is an under-actuated system since the supporting point contacting with a point on the ground has no actuator during the single supporting phase. Therefore, this paper proposes a computed-torque control for this under-actuated system using decoupled dynamic equations. A series of computer simulations with a 7-DOF biped robot with curved soles shows that the proposed walking pattern and control method are effective and allow the biped robot to walk fast and stably, and move more like human beings. Also, it is shown that the curved sole shape has superior energy consumption compared to flat soles, and greater efficiency in ascending and descending the stairs.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.561-565
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• 2000

This paper deals with dynamic walking and inverse dynamic analysis of the IWR biped walking robot. The system has nine bodies of the multibody dynamics. and all of the .joints of them are made up of the revolute joints at first. The problem of redundant constraint in double support phase is solved by changing the type of the joints considering kinematic relation. To make sure of its dynamic walking, the movement of balancing weight is determined by which satisfies not only the condition of ZMP by applying the principle of D'Alembert but also the contact condition of the ground. The modeling of IWR and dynamic walking are realized using DADS.

• Advances in robotics research
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• v.2 no.2
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• pp.151-159
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• 2018

The evolution of bipedal robots was the foundation stone for development of Humanoid robots. The highly complex and non-linear dynamic of human walking made it very difficult for researchers to simulate the gait patterns under different conditions. Simple controllers were developed initially using basic mechanics like Linear Inverted Pendulum (LIP) model and later on advanced into complex control systems with dynamic stability with the help of high accuracy feedback systems and efficient real-time optimization algorithms. This paper illustrates a number of significant mathematical models and controllers developed so far in the field of bipeds and humanoids. The key facts and ideas are extracted and categorized in order to describe it in a comprehensible structure.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.358-364
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• 2007

Intelligent walking modeling of humanoid robot using learning based neuro-fuzzy system is presented in this paper. Walking pattern, trajectory of the zero moment point (ZMP) in a humanoid robot is used as an important criterion for the balance of the walking robots but its complex dynamics makes robot control difficult. In addition, it is difficult to generate stable and natural walking motion for a robot. To handle these difficulties and explain empirical laws of the humanoid robot, we are modeling practical humanoid robot using neuro-fuzzy system based on the two types of natural motions which are walking trajectories on a t1at floor and on an ascent. Learning based neuro-fuzzy system employed has good learning capability and computational performance. The results from neuro-fuzzy system are compared with previous approach.

• Journal of Electrical Engineering and Technology
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• v.11 no.3
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• pp.751-758
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• 2016

The modifiable walking pattern generation (MWPG) algorithm can handle dynamic walking commands by changing the walking period, step length, and direction independently. When an infeasible command is given, the algorithm changes the command to a feasible one. After the feasibility of the navigational command is checked, it is translated into the desired center of mass (CM) state. To achieve the desired CM state, a reference CM trajectory is generated using predefined zero moment point (ZMP) functions. Based on the proposed algorithm, various complex walking patterns were generated, including backward and sideways walking. The effectiveness of the patterns was verified in dynamic simulations using the Webots simulator.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2368-2375
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• 2015

To accommodate various navigational commands, a humanoid should be able to change its walking motion in real time. Using the modifiable walking pattern generation (MWPG) algorithm, a humanoid can handle dynamic walking commands by changing its walking period, step length, and direction independently. If the humanoid is given a command to perform an infeasible movement, the algorithm substitutes the infeasible command with a feasible one using binary search. The feasible navigational command is subsequently translated into the desired center-of-mass (CM) state. Every sample time CM reference is generated using a zero-moment-point (ZMP) variation scheme. Based on this algorithm, various complex walking patterns can be generated, including backward and sideways walking, without detailed consideration of the feasibility of the navigational commands. In a previous study, the effectiveness of the MWPG algorithm was verified by dynamic simulation. This paper presents experimental results obtained using the small-sized humanoid robot platform DARwIn-OP.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1937-1938
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• 2006

최근 들어 안정적인 보행 패턴 생성을 위해서 많은 방법들이 제안 되고 있다. 대부분의 논문에서 주기적인 보행에 대한 연구는 이루어지고 있으나 첫 보행 구간과 마지막 보행 구간에 대한 분석은 이루어지지 않고 있다. 본 논문은 첫 보행 구간과 마지막 보행 구간에 대한 분석을 통해 기존의 역 진자 모델(Inverted pendulum model)을 기반으로 부드러운 무게 중심의 궤적을 생성하는 해석적 방법을 제안한다. 이를 위해 먼저 정현파 함수를 이용해 영 모멘트 위치(ZMP, Zero Moment Point) 궤적을 설계한다. 영 모멘트 위치 궤적 설계 시 첫 보행 구간과 마지막 보행 구간에 대해 영 모멘트 위치와 무게 중심 간의 비 최소 위상(non-minimum phase) 시스템의 특성을 이용한다. 제안된 방법을 이용하여 주기적인 보행 구간 및 첫 보행 구간과 마지막 보행 구간에서 부드러운 무게 중심 궤적이 생성됨을 시뮬레이션을 통해 구현하여 제안된 방법의 유효성을 보인다.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2406-2410
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• 2004

2족 보행로봇은 그 구조적인 특성상 인간 생활환경에 적용이 용이하며 바퀴형 로봇이 이동하기 어려운 환경에서도 이동이 가능하다. 그러나 2족 보행로봇은 높은 자유도와 직렬형 링크 구조로 인해 안정도 해석과 제어가 어려운 점이 있으며 이는 로봇을 제작하는데 있어 난점으로 작용한다. 본 연구에서는 로봇의 발바닥에 압력센서를 설치하여 ZMP(Zero moment point)를 측정하여 안정도를 판별하고 신경망 이론을 이용하여 보행 안정도를 개선하도록 로봇의 자세를 제어하였다.