본 논문에서는 보행로봇의 일종인 TITAN-VIII라 불리는 로봇을 이용하여 가장 짧은 경로를 탐색하여 이동하는 방법에 관한 연 구를 나타낸다. 보행로봇의 경우 바퀴구동 로봇에 비해 불규칙한 지면 위를 자유로이 이동 가능한 장점 등을 가지고 있는데 반해 이동속 도는 바퀴구동 로봇에 비해 느린 편이다. 따라서 본 논문에서는 목적지에 도달하기까지 시간을 최소화하는 최적경로 탐색 제어방법을 제 시하였다. 경로를 탐색하기 위해 Dijkstra’s algorithm라 불리는 알고리즘을 기반으로 하여 적용하였다. 또한 로봇이 항상 정적인 자세를 유 지하는 로봇의 다양한 자세에 대해서도 다루었다. 로봇의 자세제어와 알고리즘을 통하여 로봇의 관절각 결정에 필요한 여러 수학방정식 을 제시하였다. 그 후 원하는 궤적으로 로봇이 이동하고 탐색하는 알고리즘을 고안하였고, 제안한 방법의 결과를 실험으로 확인하였다.

Walking method based zero moment position algorithms that can guarantee the stability of the biped walking robot while walking, but it moves the legs for the stability of the walking in a way that is not related to energy conservation. Walking method using ZMP can cause low battery efficiency and load on leg joints. The walking method using the passive walking, which is a natural and efficient method of walking, can reduce the load on the joints of the robot by using the method without using the inertia that occurs when walking and reduced control elements and efficient use of battery. In this paper, a biped robot with an actuator based on the principle of passive dynamic walker mechanism is applied to a passive walking algorithm. In order to solve the problem of stabilization of the posture during walking, the posture was stabilized by using the swing motion of the arm. and the walking movement of the robot was observed using the AHRS sensor applied to the robot .It was confirmed that the posture can be stabilized based on measured values using AHRS.

Driving mechanism, the central part of a robot, was designed in this study. Power for the motive drive was acquired by directly connecting the motor shaft in worm shape of the low-end DC motor, car window motor, to a decelerator. The decelerator consists of a worm gear to receive power from the motor shaft, a pinion gear to be connected in line with the worm gear, and an output shaft to be engaged to the pinion gear. Motion driving is achieved by the power from the motor shaft with the designed gears, transferred to the deceleration mechanism and to the output gear

본 논문에서는 ATMEGA128칩을 사용하여 소형 2족 보행로봇의 제어기를 설계 및 구현하였다. 로봇 제 어기는 빠른 연산속도 및 안정된 보행상태를 유지하기 위해 다양한 센서가 필요하다. 본 논문에서는 관절의 구동부로 22개의 RC서보모터를 사용한 소형 2족 보행로봇의 제어기 구조를 제안하고 설계 구현하였다. ATMEGA128칩을 이용하여 각각의 서보모터를 제어하고 호스트컴퓨터와 블루투스통신을 통한 실시간 제어가 가능하도록 설계하였다. 또한 음성인식칩을 사용하여 인간의 명령을 로봇에 전달할 수 있도록 구현하였으며 다양한 실험을 통하여 제안된 2족 로봇제어기의 성능을 고찰하였다.

This paper describes the design concept of a bio-inspired legged underwater and estimating its performance by implementing simulations. Especially the leg structure of an underwater organism, diving beetles, is fully adopted to our designing to employ its efficiency for swimming. To make it possible for the robot to both walk and swim, the transformable kinematic model according to applications of the leg is proposed. To aid in the robot development and estimate swimming performance of the robot in advance, an underwater simulator has been constructed and an approximated model based on the developing robot was set up in the simulation. Furthermore, previous work that we have done, the swimming locomotion produced by a swimming patten generator based on the control parameters, is briefly mentioned in the paper and adopted to the simulation for extensive studies such as path planning and control techniques. Through the results, we established the strategy of leg joints which make the robot swim in the three dimensional space to reach effective controls.

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.

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.

In order to produce a convenient robot for the aged and the lower limb disabled, it is needed for the research detecting implicit walking intention and controlling robot by a user's intention. In this study, we developed sensor module system to control the walking- assist robot using FSR sensor and tilt sensor, and analyzed the signals being acquired from two sensors. The sensor module system consisted of the assist device control unit, communication unit by wire/wireless, information collection unit, information operation unit, and information processing PC which handles integrated processing of assist device control. The FSR sensors attached user's the palm and the soles of foot are sensing force/pressure signals from these areas and are used for detecting the walking intention and states. The tilt sensor acquires roll and pitch signal from area of vertebrae lumbales and reflects the pose of the upper limb. We could recognize the more detailed user's walking intention such as 'start walking', ''start of right or left foot forward', and 'stop walking' by the combination of FSR and tilt signals can recognize.

This paper proposes the trot gait pattern generation and online control methods for a quadruped robot to carry heavy loads and to move fast on uneven terrain. The trot pattern is generated from the frequency modulated pattern generation method based on the frequency modulated oscillator in order for the legged robots to be operated outdoor environment with the static and dynamic mobility. The efficiency and performance of the proposed method are verified through computer simulations and experiments using qRT-1/-2. In the experiments, qRT-2 which has two front legs driven by hydraulic linear actuators and two rear casters is used. The robot can trot at the speed up to 1.3 m/s on even surface, walk up and down the 20 degree inclines, and walk at 0.7 m/s on uneven surface. Also it can carry over 100 kg totally including 40 kg payload.

In this research, a comprehensive study is performed upon the design of a quadruped walking robot. In advance, the walking posture and skeletal configuration of the vertebrate are analyzed to understand quadrupedal locomotion, and the roles of limbs during walking are investigated. From these, it is known that the forelimbs just play the role of supportingtheir body anbd help vault forward, while most of the propulsive force is generated by hind limbs. In addition, with the study of the stances on walking and energy efficiency, design criteria and control method for a quadruped walking robot are derived. The proposed controller, though it is simple, provides a useful framework for controlling a quadruped walking robot. In particular, introduction of a new rhythmic pattern generator relieves the heavy computational burden because it does not need any computation on kinematics. Finally, the proposed method is validated via dynamic simulations and implementing in a quadruped walking robot, called AiDIN(Artificial Digitigrade for Natural Environment)

We present the synergy effect of humanoid robot walking down on a slope and support vector machines in this paper. The biped robot architecture is highly suitable for the working in the human environment due to its advantages in obstacle avoidance and ability to be employed as human substitutes. But the complex dynamics in the robot and ground makes robot control difficult. The trajectory of the zero moment point (ZMP) in a biped walking robot is an important criterion used for the balance of the walking robots. The ZMP trajectory as dynamic stability of motion will be handled by support vector machines (SVM). Three kinds of kernels are also employed, and each result from these kernels is compared to one another.