본 연구에서는 한우 암소와 씨수소의 육종가를 기반으로 연도별 유전적 개량량을 추정하여 현재 한우 축군의 개량 정도를 파악하여 향후 한우 개량 방향을 위한 기초자료로 활용하고자 본 연구를 시행하였다. 본 연구를 위하여 한우농가 4,040호에서 축산물품질평가원에 도축된 970,567두의 도축자료를 이용하여 10번 반복되어 추출된 표본 자료와 한우농가에서 2009년부터 2019년까지 사육되고 도축된 개체 중에서 한국종축개량협회에 혈통등록 되어 있는 거세우를 선별하여 결측치 및 이상치를 제거하고 도축월령이 27~32개월 이외의 기록은 분석에서 제외한 후, 1,391,141두의 도체 자료를 분석에 이용하였다. 이용된 형질은 도체중(Carcass Weight, CW), 등심단면적(Eye Muscle Area, EMA), 등지방두께(Backfat Thickness, BF) 및 근내지방도(Marbling Score, MS)의 4개 형질을 고려하였다. Random Sampling 10 반복되어 추출된 Data 1의 도체중, 등심단면적, 등지방두께 및 근내지방도의 개량추세에 대한 회귀계수는 매년 평균 0.44㎏, 0.197㎠, -0.051㎜ 및 0.034점으로 나타났으며, 도축성적을 보유한 전체 개체의 자료로 구성된 Data 2에서는 각각 0.35㎏, 0.22㎠, 0.06㎜ 및 0.04점의 개량추세를 보였다. Data 2에서 씨수소의 개량추세는 1.54㎏, 0.343㎠, -0.045㎜ 및 0.050점의 추세를 보였으며 암소와 씨수소 간에는 1.19㎏, 0.119㎠, -0.014㎜ 및 0.010점의 차이를 보였다. 유전적 개량량을 확인하기 위하여 육종가의 표준편차를 이용하였으며, 암소의 선발강도는 본 연구에서 보고한 암소의 후대 거세우 기록 빈도 및 비율을 통해 계산하였다. 한우 암소의 선발 시기를 3산차 이전을 기준으로 하는 것과 4산차 이후를 기준으로 하는 것으로 나눠서 선발강도를 적용하였다. 그 결과, 암소의 선발 시기를 3산차 이전으로 했을 때 세대당 유전적 개량량은 도체중, 등심단면적, 등지방두께 및 근내지방도에서 각각 5.04㎏, 1.31㎠, 0.71㎜ 및 0.32점으로 나타났다. 이러한 결과를 바탕으로 현재 한우 암소집단에서 정확한 육종가를 추정하고, 유전적 개량량을 높이기 위해서는 후대의 기록을 높이기 위한 육종 계획이 필요할 것으로 판단된다.

본 연구는 한우농가에서 직접 사육되어 도축되어진 한우 거세우 전체의 도축성적 및 혈통자료를 수집하여 한우 암소의 유전능력평가를 위한 유전모수를 추정하고 농가에서 직접적으로 활용 가능한 유전능력 추정을 위한 기초자료로 제공하고자 하였다. 본 연구를 위해 검증된 970,141두의 도축기록으로부터 60,000두 이상의 표현형 표본을 추출하기 위해 전체 4,040농가 중 600농가를 단순임의추출(Simple Random Sampling)하여 선정된 농가의 도축기록을 모두 추출하는 방식으로 10회 반복하여 표본을 생성하였다. 본 연구에서 추정된 도체형질에 대한 유전력은 도체중에서 0.24-0.30, 등심단면적에서 0.24-0.31, 등지방두께에서 0.31-0.39, 근내지방도에서 0.38-0.58로 추정되었으며, 10회 반복 추정된 유전력의 평균값은 도체중, 등심단면적, 등지방두께 및 근내지방도에서 각각 0.28, 0.28, 0.35 및 0.48로 추정되었다. 추정된 결과가 기존에 한우에서 보고된 유전력에 비해 다소 낮게 추정되었으나 실제 농가에서 사육되어 도축된 전체 자료가 표본이 된 만큼 본 연구 결과는 전국단위의 도축자료를 이용한 결과로서 암소개량을 위해 직접적으로 활용 가능한 자료가 될 수 있을 것으로 기대된다.

본 연구는 부모의 혈통정보를 모두 아는 혈통 및 고등등록우로 등록된 한우 암소 25,516두의 선형 및 외모심사형질에 대해 유전모수를 추정하였다. 각 심사형질에 영향을 주는 것으로 판단되는 주요인을 선 정하여 다형질 개체모형에 적용하여 EM-REML 알고리즘 분석방법을 통해 각 형질에 대한 유전력과 유 전상관과 표현형상관을 추정하였다. 한우 암소의 17개 선형심사형질 및 10개 외모심사형질(종합점수 포 함)의 유전력 추정치의 범위는 0.03(유두배열)에서 0.42(체장)까지로 추정되었다. 체고, 체장, 강건성, 체심, 윤곽성, 정강이두께, 피모의 색, 엉덩이기울기, 고장, 좌골폭, 넓적다리의 두께, 유방용적, 유두길 이, 유두배열, 발굽기울기, 뒷다리 비절기울기, 뒤에서 본 뒷다리자세, 체적․균형, 자질․품위, 머리․목, 전구, 중구, 엉덩이, 넓적다리, 유기, 지제보양 및 종합점수의 유전력은 각각 0.4, 0.42, 0.27, 0.25, 0.06, 0.14, 0.22, 0.31, 0.19, 0.17, 0.29, 0.04, 0.07, 0.02, 0.11, 0.03, 0.16, 0.27, 0.08, 0.15, 0.14, 0.14, 0.19, 0.16, 0.05, 0.08 및 0.3으로 추정되었다. 한편, 다형질개체모형에 의해 추정된 17개 선형심사형질과 종합점수에 대한 유전상관추정 결과는 다음과 같다. 고장과 좌골폭간에 0.96의 가장 강 한 양(+)의 유전적 관계를 나타내었다. 반면 발굽기울기와 뒷다리 비절기울기간에는 -0.57의 가장 큰 음(-)의 유전상관을 보였다. 전체외모 형질인 체고, 체장, 간겅성 및 체심은 각 형질간에, 그리고 기타 형 질들과 강한 양(+)의 유전상관관계를 나타내었다. 특히 체고 및 체심과 고장 및 좌골폭간에 높은 양(+)의 상관관계를 나타내었으며, 체고와 엉덩이기울기간에는 0.32의 양(+)의 상관을 나타내었다.

This paper describes an alignment algorithm that estimates the initial heading angle of AUVs (Autonomous Underwater Vehicle) for starting navigation in a sea area. In the basic dead reckoning system, the initial orientation of the vehicle is very important. In particular, the initial heading value is an essential factor in determining the performance of the entire navigation system. However, the heading angle of AUVs cannot be measured accurately because the DCS (Digital Compass) corrupted by surrounding magnetic field in pointing true north direction of the absolute global coordinate system (not the same to magnetic north direction). Therefore, we constructed an experimental constraint and designed an algorithm based on extended Kalman filter using only inertial navigation sensors and a GPS (Global Positioning System) receiver basically. The value of sensor covariance was selected by comparing the navigation results with the reference data. The proposed filter estimates the initial heading angle of AUVs for navigation in a sea area and reflects sampling characteristics of each sensor. Finally, we verify the performance of the filter through experiments.

For a mobile robot that travels along a terrain consisting of various geology, information on tire force and friction coefficient between ground and wheel is an important factor. In order to estimate the lateral force between ground and wheel, a lot of information about the model and the surrounding environment of the vehicle is required in conventional method. Therefore, in this paper, we are going to estimate lateral force through simple model (Minimal Argument Lateral Slip Curve, MALSC) using only minimum data with high estimation accuracy and to improve estimation reliability of the friction coefficient by using the estimated lateral force data. Simulation is carried out to analyze the correlation between the longitudinal and transverse friction coefficients and slip angles to design the simplified lateral force estimation model by analysing simulation data and to apply it to the actual field environment. In order to verify the validity of the equation, estimation results are compared with the conventional method through simulation. Also, the results of the lateral force and friction coefficient estimation are compared from both the conventional method and the proposed model through the actual robot running experiments.

This paper describes a study on posture control of the multi-legged biomimetic underwater robot (CALEB10). Because the underwater environment has a feature that all degrees of freedom are coupled to each other, we designed the posture control algorithm by separating each degree of freedom. Not only should the research on posture control of underwater robots be a precedent study for position control, but it is also necessary to compensate disturbance in each direction. In the research on the yaw directional posture control, we made the drag force generated by the stroke of the left leg and the right leg occur asymmetrically, in order that a rotational moment is generated along the yaw direction. In the composite swimming controller in which the controllers in each direction are combined, we designed the algorithm to determine the control weights in each direction according to the error angle along the yaw direction. The performance of the proposed posture control method is verified by a dynamical simulator and underwater experiments.

The CALEB10 is a multi-legged biomimetic underwater robot. In the last research, we developed a swimming pattern named ESPG (Extended Swimming Pattern Generator) by observing diving beetle’s swimming actions and experimented with a positive buoyancy state in which CALEB10 floats on the water. In this paper, however, we have experimented with CALEB10 in a neutral buoyancy state where it is completely immersed in water for pitch motion control experiment. And we found that CALEB10 was unstably swimming in the pitch direction in the neutral buoyancy state and analyzed that the reason was due to the weight proportion of the legs. In this paper, we propose a pitch motion control method to mimic the pitch motion of diving beetles and to solve the problem of CALEB10 unstably swimming in the pitch direction. To control the pitch motion, we use the method of controlling additional joints while swimming with the ESPG. The method of obtaining propulsive force by the motion of the leg has a problem of giving propulsive force in the reverse direction when swimming in the surge direction, but this new control method has an advantage that a propulsive moment generated by a swimming action only on a target pitch value. To demonstrate validity this new control method, we designed a dynamics-based simulator environment. And the control performance to the target pitch value was verified through simulation and underwater experiments.

For articulated swimming robots, there have been no researches about controlling the motion or trajectory following. A control method for articulated swimming robot is suggested by extending a previous algorithm, ESPG (Extended Swimming Pattern Generator). The control method focuses on the situation that continuous pre-determined swimming pattern is applied for long range travelling. In previous studies, there has not been a way to control the propulsive force when a swimming pattern created by ESPG was in progress. Hence, no control could be made unless the swimming pattern was completed even though an error occurred while the swimming pattern was in progress. In order to solve this problem, this study analyzes swimming patterns and suggests a method to control the propulsive force even while the swimming pattern was in progress. The angular velocity of each link is influenced and this eventually modifies the propulsive force. However, The angular velocity is changed, a number of problems can occur. In order to resolve this issue, phase compensation method and synchronization method were suggested. A simple controller was designed to confirm whether the suggested methods are able to control and a simulation has affirmed it. Moreover, it was applied to CALEB 10 (a biomimetic underwater articulated robot) and the result was verified.

Most of outdoor mobile robots have a suspension on each wheel in order to relieve the shock by ground obstacles and to improve the driving stability. Typically, in the actual operations, the suspensions have been used under a given set of conditions as all the damping and spring coefficients of the suspensions are fixed. However, it is necessary to readjust the coefficients of the suspensions according to surface conditions that may cause the unstable shaking of a robot body at high speed driving. Therefore, this paper is focused on the mobility analysis of an outdoor robot when the coefficients of suspensions (in particular, damping coefficients) are changed while driving on an uneven road surface. In this paper, a semi-active suspension with twelve damping coefficient levels was used and a small sized vehicle with the suspensions was employed to analyze the mobility dependent on a change of the damping coefficient. And the mobility was evaluated through driving experiments on a bumped slope.

The robot mechanisms that were previously researched had only been conducted for the purpose of overcoming the obstacles stably at low speed driving and enhancing the stability against high speed circuitous driving, and yet, the mechanism satisfying two purposes. However, in order to stably drive with high speed on rough terrain, there is a need for satisfying both of these purposes, as well as testing the efficiency of the mechanisms at high speed driving. There, this paper simulated some of the passive mechanisms and focused on checking the performances of passive mechanisms through simulations and analyzing each mechanism on the basis of an evaluation index. The simulation was conducted by Adams (The Multi-body Dynamics Simulation Solution) and used various types of passive mechanisms which were introduced in the robotics field. As a result, the study confirmed that passive mechanisms have a number of situations that affect the driving stability on each direction of roll and pitch. Further study is needed about active mechanism.

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.

Methods for measuring or estimating of ground shape by a laser range finder and a vision sensor(exteroceptive sensors) have critical weakness in terms that these methods need prior database built to distinguish acquired data as unique surface condition for driving. Also, ground information by exteroceptive sensors does not reflect the deflection of ground surface caused by the movement of UGVs. Thereby, UGVs have some difficulties regarding to finding optimal driving conditions for maximum maneuverability. Therefore, this paper proposes a method of recognizing exact and precise ground shape using Inertial Measurement Unit(IMU) as a proprioceptive sensor. In this paper, firstly this method recognizes attitude of a robot in real-time using IMU and compensates attitude data of a robot with angle errors through analysis of vehicle dynamics. This method is verified by outdoor driving experiments of a real mobile robot.

This paper focuses on development of a testbed for analysis of robot-terrain interaction on rough terrain and also, through one wheel driving experiments using this testbed, prediction of maximum velocity and acceleration of UGV. Firstly, from the review regarding previous researches for terrain modeling, the main variables for measurement are determined. A testbed is developed to measure main variables related to robot-terrain interaction. Experiments are performed on three kinds of rough terrains (grass, gravel, and sand) and traction-slip curves are obtained using the data of the drawbar pull and slip ratio. Traction-slip curves are used to predict driving performance of UGV on rough terrain. Maximum velocity and acceleration of UGVs are predicted by the simple kinematics and dynamics model of two kinds of 4-wheel mobile robots. And also, driving efficiency of UGVs is predicted to reduce energy consumption while traversing rough terrains.

Recently, development of underwater robot has actively been in progress in the world as ROV(Remotely Operator Vehicle) and AUV(Autonomous Unmmanded Vehicle) style. But KIOST(Korea Institute of Ocean Science and Technology), beginning in 2010, launched the R&D project to develop the robot, dubbed CRABSTER(Crab + (Lob)ster) in a bid to enhance the safety and efficiency of resource exploration. CRABSTER has been designed to be able to walk and swim with its own legs without screws. Among many research subjects regarding CRABSTER, optimal swimming patterns are handled in this paper. In previous studies, drag forces during one period with different values for angle of each joint were derived. However kinematics of real-robot and fluid-dynamics are not considered. We conducted simulations with an optimization algorithm for swimming by considering simplified fluid dynamics in this paper. Drag-coefficients applied to the simulation were approximated values calculated by CFD(Computational Fluid Dynamics : Tecplot 360, ANSYS). In addition, optimized swimming patterns were applied to a real robot. The experiments with the real robot were conducted in circumstances in the water. As a result, when the experiments were carried out in the water, a regular pattern of drag force output came out depending on the movement of the robot. We confirmed the fact that the drag forces from the simulation and the experiment has a high similarity.

In these days, researches about underwater robots have been actively in progress for the purposes of ocean detection and resource exploration. Unlike general underwater robots such as ROV(Remotely Operated Vehicle) and AUV(Autonomous Underwater Vehicle) which have propellers, an articulated underwater robot which is called Crabster has been being developed in KORDI(Korea Ocean Research & Development Institute) with many cooperation organizations since 2010. The robot is expected to be able to walk and swim under the sea with its legs. Among many researching fields of this project, we are focusing on a swimming section. In order to find effective swimming locomotion for the robot, we approached this subject in terms of Biomimetics. As a model of optimized swimming organism in nature, diving beetles were chosen. In the paper, swimming motions of diving beetles were analyzed in viewpoint of robotics for applying them into the swimming motion of the robot. After modeling the kinematics of diving beetle through robotics engineering technique, we obtained swimming patterns of the one of living diving beetles, and then compared them with calculated optimal swimming patterns of a robot leg. As the first trial to compare the locomotion data of legs of the diving beetle with a robot leg, we have sorted two representative swimming patterns such as forwarding and turning. Experimental environment has been set up to get the motion data of diving beetles. The experimental equipment consists of a transparent aquarium and a high speed camera. Various swimming motions of diving beetles were recorded with the camera. After classifying swimming patterns of the diving beetle, we can get angular data of each joint on hind legs by image processing software, Image J. The data were applied to an optimized algorithm for swimming of a robot leg which was designed by robotics engineering technique. Through this procedure, simulated results which show trajectories of a robot leg were compared with trajectories of a leg of a diving beetle in desired directions. As a result, we confirmed considerable similarity in the result of trajectory and joint angles comparison.

Outdoor mobile robots are faced with various terrain types having different characteristics. To run safely and carry out the mission, mobile robot should recognize terrain types, physical and geometric characteristics and so on. It is essential to control appropriate motion for each terrain characteristics. One way to determine the terrain types is to use non‐contact sensor data such as vision and laser sensor. Another way is to use contact sensor data such as slope of body, vibration and current of motor that are reaction data from the ground to the tire. In this paper, we presented experimental results on terrain classification using contact sensor data. We made a mobile robot for collecting contact sensor data and collected data from four terrains we chose for experimental terrains. Through analysis of the collecting data, we suggested a new method of terrain feature extraction considering physical characteristics and confirmed that the proposed method can classify the four terrains that we chose for experimental terrains. We can also be confirmed that terrain feature extraction method using Fast Fourier Transform (FFT) typically used in previous studies and the proposed method have similar classification performance through back propagation learning algorithm. However, both methods differ in the amount of data including terrain feature information. So we defined an index determined by the amount of terrain feature information and classification error rate. And the index can evaluate classification efficiency. We compared the results of each method through the index. The comparison showed that our method is more efficient than the existing method.

This paper proposes how to improve the performance of CSS-based indoor localization system. CSS based localization utilizes signal flight time between anchors and tag to estimate distance. From the distances, the 3-dimensional position is calculated through trilateration. However the error in distance caused from multi-path effect transfers to the position error especially in indoor environment. This paper handles a problem of reducing error in raw distance information. And, we propose the new localization method by pattern matching instead of the conventional localization method based on trilateration that is affected heavily on multi-path error. The pattern matching method estimates the position by using the fact that the measured data of near positions possesses a high similarity. In order to gain better performance of localization, we use EKF(Extended Kalman Filter) to fuse the result of CSS based localization and robot model.

This paper presents a method to optimize motion planning for industrial manipulators with redundancy. For optimal motion planning, first of all, particular inverse kinematic solution is needed to improve efficiency for manipulators with redundancy working in various environments. In this paper, we propose three kinds of methods for solving inverse kinematics problems; numerical and combined approach. Also, we introduce methods for optimal motion planning using potential function considering the order of priority. For efficient movement in industrial settings, this paper presents methods to plan motions by considering colliding obstacles, joint limits, and interference between whole arms. To confirm improved performance of robot applying the proposed algorithms, we use two kinds of robots with redundancy. One is a single arm robot with 7DOF and another is a dual arm robot with 15DOF which consists of left arm, right arm with each 7DOF, and a torso part with 1DOF. The proposed algorithms are verified through several numerical examples as well as by real implementation in robot controllers.

This paper proposes a technique of indoor localization for mobile robot by so called indoor GPS and EKF. Basically the concept of indoor GPS is similar outdoor GPS, and the indoor GPS gets distances between Anchors and Tag by a ranging method of CSS and then estimates the coordinate by distances and known Anchor positions. After we performed performance test of indoor GPS system in ideal and multipath environment, we configured that the indoor GPS has internal error factors and external error factors. This paper handled a multipath problem belonging to external error factors. At first various direct physical method are introduced to fix the multipath problems, and as expected we got errors corrected considerably. And then the method of selective anchors for indoor GPS is applied. With these two level improvement of indoor GPS performance, EKF(Extended Kalman Filter) is applied to mobile robot in indoor environment. The usefulness of the proposed methods are shown by a series of experiments in a environment giving contaminated data by multipath.

One of the requirements for autonomous vehicles on off-road is to move stably in unstructured environments. Such capacity of autonomous vehicles is one of the most important abilities in consideration of mobility. So, many researchers use contact and/or non-contact methods to determine a terrain whether the vehicle can move on or not. In this paper we introduce an algorithm to classify terrains using visual information(one of the non-contacting methods). As a pre-processing, a contrast enhancement technique is introduced to improve classification of terrain. Also, for conducting classification algorithm, training images are grouped according to materials of the surface, and then Bayesian classification are applied to new images to determine membership to each group. In addition to the classification, we can build Traversability map specified by friction coefficients on which autonomous vehicles can decide to go or not. Experiments are made with Load-Cell to determine real friction coefficients of various terrains.