본 연구는 보행로에서 주행하는 자율주행로봇의 경로 최적화를 위한 D*알고리즘 수정에 중점을 두고 있다. 기존의 D*알고리즘은 자율주행 로봇이 장애물을 인식하고 회피하는 방식으로 설계되었지만, 실제 보행환경에서는 보행로를 통행하는 사람들이 로봇을 인지 하고 스스로 회피하는 경향이 관찰되었다. 라이다 센서를 통해 수집된 사람들의 궤적 데이터를 분석하여, 사람들이 자율주행 로봇을 회피하기 시작하는 평균 거리와 회피 각도를 파악하였다. 이를 바탕으로, 사람들이 로봇을 회피할 의사가 있을 때 로봇이 기존 최적경 로를 유지하도록 하고, 그렇지 않은 경우에만 회피 경로를 채택하는 수정된 D*알고리즘을 제안하였다. 실험 결과, 수정된 D*알고리즘 을 적용한 자율주행 로봇은 운행 효율과 주행 시간 측면에서 기존 방식 대비 우수한 성능을 보였다. 이러한 연구는 제한된 배터리 용 량 하에서도 효율적인 주행이 가능하도록 하여 자율주행 로봇의 보행로 사용을 최적화하는 데 기여할 것으로 기대된다.

The calculation of the optimal trajectory of the stepped top-down robot was made using a genetic algorithm and a computational torque controller. First, the total energy efficiency was minimized using the Red-Cold Generic Algorithm (RCGA) consisting of reproductive, cross, and mutation. The reproducibility condition related to the position assembly of the start and end of the stride and the joints, angles, and angular velocities are linear constraints. Next, the unequal constraint accompanies the condition for preventing the collision of the swing leg at the corner with the outer surface of the stairs, the condition of the knee joint for preventing kinematic peculiarity, and the condition of no moment in safety in the traveling direction. Finally, the angular trajectory of each joint is defined by fourth-order polynomial whose coefficient is to approximate chromosomes. This is to approximate walking. In this study, the energy efficiency of the optimal trajectory was analyzed by computer simulation through a biped robot with seven degrees of freedom composed of seven links.

Crawling robots are advantageous in overcoming obstacles. These robots have characteristics such as light weight and outstanding mobility. In case of large robots, they have difficulties passing narrow gaps or entering the cave. In this paper, we propose a milli-scale hexapedal robot using 4-bar linkages. Two conditions are necessary to enable efficient walking. In short, the trajectory of the foot must be elliptical, and the lowest point of the foot should be the same. These conditions are satisfied with a novel leg design. The robot has a pair of three legs and the legs are coupled to operate simultaneously. Each set of the legs are installed to robot’s both sides and the legs satisfy the equal lowest foot point and elliptical trajectory. As a result, this hexapedal robot can crawl with 0.56m/s speed.

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.

Robot-assisted rehabilitation therapy has been used to increase physical function in post-stroke patients. The aim of this meta-analysis was to identify whether robot-assisted gait training can improve patients’ functional abilities. A comprehensive search was performed of PubMed, Cochrane Central Register of Controlled Trials (CENTRAL), Physiotherapy Evidence Database (PEDro), Academic Search Premier (ASP), ScienceDirect, Korean Studies Information Service System (KISS), Research Information Sharing Service (RISS), Korea National Library, and the Korean Medical Database up to April, 2014. Fifteen eligible studies researched the effects of robot-assisted gait training to a control group. All outcome measures were classified by International Classification of Functioning, Disability, and Health (ICF) domains (body function and structures, activity, and participation) and were pooled for calculating the effect size. The overall effect size of the robot-assisted gait training was .356 [95% confidence interval (CI): .186∼.526]. When the effect was compared by the type of electromechanical robot, Gait Trainer (GT) (.471, 95% CI: .320∼.621) showed more effective than Lokomat (.169, 95% CI: .063∼.275). In addition, acute stroke patients showed more improvement than others. Although robot-assisted gait training may improve function, but there is no scientific evidence about the appropriate treatment time for one session or the appropriate duration of treatment. Additional researchers are needed to include more well-designed trials in order to resolve these uncertainties.

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.

Snake robots are slower than wheeled robots or legged robots, while they have an excellent terrainability in a disastrous area. Considering their advantages and disadvantages, a legged robot whose legs are snake robots, ‘Quadnake’ was proposed in this research. Five motions of the snake were analyzed. Applying these motions, Quadnake could implement eight kinds of motions which snake robots and quadruped walking robots can implement. As a result of it, Quadnake can have the advantages of both a snake robot and a walking robot. It is expected to move stably in a harsh terrain with snake’s motion and move fast with walking.

This paper presents about design efforts of a human-sized quadruped robot leg for high energy efficiency, and verifications. One of the representative index of the energy efficiency is the Cost of Transport (COT), but increased in the energy or work done is not calculated in COT. In this reason, the input to the output energy efficiency should be also considered as a very important term. By designing the robot with customized motor housing, small rotational inertia, and low gear ratio to reduce friction, high energy efficiency was achieved. Squatting motion of one leg was performed and simulation results were compared to the experimental results for validation. The developed 50 kg robot can lift the weight up to 200 kg, and during squatting, it showed high energy efficiency. The robot showed 71% input to output energy efficiency in positive work. Peak current during squatting only appears to be 0.3 A.

An important characteristic of people with partially impaired walking ability, such as incomplete paraplegics, is that they are able to generate voluntary motion of lower-limbs. Therefore, wearable robots for the incomplete paraplegic patients require a different assistance method compared to those of complete paraplegics. First, the wearable robot should be controlled to not resist wearer’s motion. Second, it should be able to generate assistive torque accurately when needed. In this paper, a wearable robot, called EROWA, for the incomplete paraplegic patients is introduced. EROWA utilizes compact rotary series elastic actuators (cRSEAs) and a control method called the zero impedance control to reduce the mechanical resistance. An assistive torque trajectory is proposed to assist gait in this paper. The proposed method is verified by simulation and experimental studies.

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.

One of the important issues for structural and electrical specifications in developing a robot is to determine lengths of links and motor specifications, which need to be appropriate to the purpose of robot. These issues become more critical for a gait rehabilitation robot, since a patient wears the robot. Prior to developing an entire gait rehabilitation robot, designing of a 1DOF assistive knee joint of the robot is considered in this paper. Human gait motions were used to determine an allowable range of knee joint that was rotated with a linear type actuator (ball-screw type) and links. The lengths of each link were determined by using an optimization process, minimizing the stroke of actuator and the total energy (kinetic and potential energy). Kinetic analysis was performed in order to determine maximum rotational speed and maximum torque of the motor for tracking gait trajectory properly. The prototype of 1 DOF assistive knee joint was built and examined with a impedance controller.

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 work deals with an intuitive method for a planar biped to walk, which is named Relative Trajectory Control (RTC) method. A key feature of the proposed RTC method is that feet of the robot are controlled to track a given trajectory, which is specially designed relative to the base body of the robot. The trajectory of feet is presumed from analysis of the walking motion of a human being. A simple method to maintain a stable posture while the robot is walking is also introduced in RTC method. In this work, the biped is modeled as a free-floating robot, of which dynamic model is obtained in the Cartesian space. Using the obtained dynamic model, the robot is controlled by a model-based feedback control scheme. The author shows a preliminary experimental result to verify that the biped robot with RTC method can walk on the even or uneven surfaces.

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.

This paper presents a motion planning strategy for legged robots using locomotion primitives in the complex 3D environments. First, we define configuration, motion primitives and locomotion primitives for legged robots. A hierarchical motion planning method based on a combination of 2.5 dimensional maps such as an obstacle height map, a passage map, and a gradient map of obstacles to distinguish obstacles. A high-level path planner finds a global path from a 2D navigation map. A mid-level planner creates sub-goals that help the legged robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. A local obstacle map that describes the edge or border of the obstacles is used to find the sub-goals along the global path. A low-level planner searches for a feasible sequence of locomotion primitives between sub-goals. We use heuristic algorithm in local motion planner. The proposed planning method is verified by both locomotion and soccer experiments on a small biped robot in a cluttered environment. Experiment results show an improvement in motion stability.