• Title/Summary/Keyword: 6 DOF Trajectory

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A Deep Convolutional Neural Network Based 6-DOF Relocalization with Sensor Fusion System (센서 융합 시스템을 이용한 심층 컨벌루션 신경망 기반 6자유도 위치 재인식)

  • Jo, HyungGi;Cho, Hae Min;Lee, Seongwon;Kim, Euntai
    • The Journal of Korea Robotics Society
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    • v.14 no.2
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    • pp.87-93
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    • 2019
  • This paper presents a 6-DOF relocalization using a 3D laser scanner and a monocular camera. A relocalization problem in robotics is to estimate pose of sensor when a robot revisits the area. A deep convolutional neural network (CNN) is designed to regress 6-DOF sensor pose and trained using both RGB image and 3D point cloud information in end-to-end manner. We generate the new input that consists of RGB and range information. After training step, the relocalization system results in the pose of the sensor corresponding to each input when a new input is received. However, most of cases, mobile robot navigation system has successive sensor measurements. In order to improve the localization performance, the output of CNN is used for measurements of the particle filter that smooth the trajectory. We evaluate our relocalization method on real world datasets using a mobile robot platform.

Trajectory Optimization for Biped Robots Walking Up-and-Down Stairs based on Genetic Algorithms (유전자 알고리즘을 이용한 이족보행 로봇의 계단 보행)

  • Jeon Kweon-Soo;Kwon O-Hung;Park Jong-Hyeon
    • Journal of the Korean Society for Precision Engineering
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    • v.23 no.4 s.181
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    • pp.75-82
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    • 2006
  • In this paper, we propose an optimal trajectory for biped robots to move up-and-down stairs using a genetic algorithm and a computed-torque control for biped robots to be dynamically stable. First, a Real-Coded Genetic Algorithm (RCGA) which of operators are composed of reproduction, crossover and mutation is used to minimize the total energy. Constraints are divided into equalities and inequalities: Equality constraints consist of a position condition at the start and end of a step period and repeatability conditions related to each joint angle and angular velocity. Inequality constraints include collision avoidance conditions of a swing leg at the face and edge of a stair, knee joint conditions with respect to the avoidance of the kinematic singularity, and the zero moment point condition with respect to the stability into the going direction. In order to approximate a gait, each joint angle trajectory is defined as a 4-th order polynomial of which coefficients are chromosomes. The effectiveness of the proposed optimal trajectory is shown in computer simulations with a 6-dof biped robot that consists of seven links in the sagittal plane. The trajectory is more efficient than that generated by the modified GCIPM. And various trajectories generated by the proposed GA method are analyzed in a viewpoint of the consumption energy: walking on even ground, ascending stairs, and descending stairs.

Linear Model Predictive Control of 6-DOF Remotely Operated Underwater Vehicle Using Nonlinear Robust Internal-loop Compensator (비선형 강인 내부루프 보상기를 이용한 6자유도 원격조종 수중로봇의 선형 모델예측 제어)

  • Junsik Kim;Yuna Choi;Dongchul Lee;Youngjin Choi
    • The Journal of Korea Robotics Society
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    • v.19 no.1
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    • pp.8-15
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    • 2024
  • This paper proposes a linear model predictive control of 6-DOF remotely operated underwater vehicles using nonlinear robust internal-loop compensator (NRIC). First, we design a integrator embedded linear model prediction controller for a linear nominal model, and then let the real model follow the values calculated through forward dynamics. This work is carried out through an NRIC and in this process, modeling errors and external disturbance are compensated. This concept is similar to disturbance observer-based control, but it has the difference that H optimality is guaranteed. Finally, tracking results at trajectory containing the velocity discontinuity point and the position tracking performance in the disturbance environment is confirmed through the comparative study with a traditional inverse dynamics PD controller.

Launch Trajectory Analysis of a Spacecrafta (위성발사체의 발사궤적 해석)

  • 최재원;이장규;이달호
    • 제어로봇시스템학회:학술대회논문집
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    • 1988.10a
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    • pp.614-619
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    • 1988
  • In this paper, an arbitrary mission of a spacecraft from launch to orbit injection is investigated for some launch trajectories. Launch sites are selected arbitrarily from various locations in Korea. For this study, a general purpose simulation program is developed. In this program, the Earth is assumed to be a rotating ellipsold. The launch vehicle is treated as a 3-D, 6-DOF rigid body. The developed program has been evaluated by calibrating it to the 3-stage N-1 rocket developed in Japan and launched at Tanegasima. The simulated trajectory from the first-stage ignition to burnout of third-stage main engine is compared with the previously tested N-1 rocket trajectory in Japan. The result shows that the program works properly. Using the proven program, we have investigated possible launch locations in Korea, namely Marado, Sungsan and Kuryongpo. The problem of polar orbit injection is also examined.

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A Study on the Circular Error Probability of Short-Range Rocket with Parachute (낙하산을 갖는 단거리 발사체의 오차분석)

  • 김찬수;조요한
    • Journal of the Korea Institute of Military Science and Technology
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    • v.2 no.2
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    • pp.218-225
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    • 1999
  • This paper contains the computational simulation of a free rocket with a parachute and the development of a firing table for each range. To obtain the trajectory of the rocket, 6 DOF model of rocket with parachute was generated and the wind tunnel test was done for the input parameters. Good agreement was obtained between the analysis of trajectory and the flight test result. Also the trajectory error analysis was performed by the Monte Carlo simulation. As a result of simulation, the CEP(Circular Error Probability) of the firing table was calculated.

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A STUDY ON THE STORE SEPARATION PREDICTION TECHNIQUE USING GRID SURVEY METHOD (GRID SURVEY 방법을 이용한 무장분리예측 기법 연구)

  • Kim, Sang-Jin;Kang, In-Mo;Kim, Myung-Seong
    • 한국전산유체공학회:학술대회논문집
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    • 2006.10a
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    • pp.136-141
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    • 2006
  • A prediction of store separation trajectory using grid survey method has been conducted. For the grid survey method, store's aerodynamic flowfield data such as freestream and grid data is needed to solve 6 degree of freedom(6-DOF) equations of motion. In the presented study, aerodynamic flowfield data was generated by Euler solver instead of CTS wind tunnel test. The predicted trajectories shows good agreement with CTS test results.

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PREDICTION OF SEPARATION TRAJECTORY FOR TSTO LAUNCH VEHICLE USING DATABASE BASED ON STEADY STATE ANALYSIS (정상 해석 기반의 데이터베이스를 이용한 TST 비행체의 분리 궤도 예측)

  • Jo, J.H.;Ahn, S.J.;Kwon, O.J.
    • Journal of computational fluids engineering
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    • v.19 no.2
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    • pp.86-92
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    • 2014
  • In this paper, prediction of separation trajectory for Two-stage-To-Orbit space launch vehicle has been numerically simulated by using an aerodynamic database based on steady state analysis. Aerodynamic database were obtained for matrix of longitudinal and vertical positions. The steady flow simulations around the launch vehicle have been made by using a 3-D RANS flow solver based on unstructured meshes. For this purpose, a vertex-centered finite-volume method was adopted to discretize inviscid and viscous fluxes. Roe's finite difference splitting was utilized to discretize the inviscid fluxes, and the viscous fluxes were computed based on central differencing. To validate this flow solver, calculations were made for the wind-tunnel experiment model of the LGBB TSTO vehicle configuration on steady state conditions. Aerodynamic database was constructed by using flow simulations based on test matrix from the wind-tunnel experiment. ANN(Artificial Neural Network) was applied to construct interpolation function among aerodynamic variables. Separation trajectory for TSTO launch vehicle was predicted from 6-DOF equation of motion based on the interpolated function. The result of present separation trajectory calculation was compared with the trajectory using experimental database. The predicted results for the separation trajectory shows fair agreement with reference[4] solution.

Locomotion Control of Biped Robots with Serially-Linked Parallel Legs (이중 병렬형 다리 구조를 가진 2족보행로봇의 보행제어)

  • Yoon, Jung-Han;Park, Jong-Hyeon
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.34 no.6
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    • pp.683-693
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    • 2010
  • In this paper, we propose a new parallel mechanism for the legs of biped robots and the control of the robot's locomotion. A leg consists of two 3-DOF parallel platforms linked serially: one is an orientation platform for a thigh and the other is the 3-DOF asymmetric parallel platform for the shank. The desired locomotion trajectory is generated on the basis of the Gravity-Compensated Inverted Pendulum Mode (GCIPM) in the sagittal direction and the Linear Inverted Pendulum Mode (LIPM) in the lateral direction, respectively. In order to simulate the ground reaction force, a 6-DOF elastic pad model is used underneath each of the soles. The performance and effectiveness of the proposed parallel mechanism and locomotion control are shown by the results of computer simulations of a 12-DOF parallel biped robot using $SimMechanics^{(R)}$.

Hardware-in-the-loop simulation of RPV autopilot using strapdown AHRS (스트랩다운 AHRS를 이용한 무인항공기(RPV) 자동조종장치의 실시간 실물 모의시험)

  • 홍성경;김태연;탁민제
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10a
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    • pp.135-140
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    • 1992
  • This paper presents the configuration, HILS procedure and performance simulation results of the RPV autopilot including a strapdown AHRS. Real time hardware-in-the-loop simulation was performed by using a 3 axis flight motion simulator alonged assumed flight trajectory of the RPV. Being compared with the result of the 6 DOF simulation, the HILS results showed that the performance of the autopilot was satisfactory.

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DNN-Based Adaptive Optimal Learning Controller for Uncertain Robot Systems (동적 신경망에 기초한 불확실한 로봇 시스템의 적응 최적 학습제어기)

  • 정재욱;국태용;이택종
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.6
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    • pp.1-10
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    • 1997
  • This paper presents an adaptive optimal learning controller for uncertian robot systems which makes use fo simple DNN(dynamic neural network) units to estimate uncertain parameters and learn the unknown desired optimal input. With the aid of a lyapunov function, it is shown that all that error signals in the system are bounded and the robot trajectory converges to the desired one globally exponentially. The effectiveness of the proposed controller is hsown by applying the controller to a 2-DOF robot manipulator.

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