A Joint Motion Planning Based on a Bio-Mimetic Approach for Human-like Finger Motion

Byoung-Ho Kim 대한전기학회 2006 International Journal of Control, Automation, and Vol.4 No.2

Grasping and manipulation by hands can be considered as one of inevitable functions to achieve the performances desired in humanoid operations. When a humanoid robot manipulates an object by his hands, each finger should be well-controlled to accomplish a precise manipulation of the object grasped. So, the trajectory of each joint required for a precise finger motion is fundamentally necessary to be planned stably. In this sense, this paper proposes an effective joint motion planning method for humanoid fingers. The proposed method newly employs a bio-mimetic concept for joint motion planning. A suitable model that describes an interphalangeal coordination in a human finger is suggested and incorporated into the proposed joint motion planning method. The feature of the proposed method is illustrated by simulation results. As a result, the proposed method is useful for a facilitative finger motion. It can be applied to improve the control performance of humanoid fingers or prosthetic fingers.

Robust Near Optimal Sub-Motions for Differentially-Driven Mobile Robots

Mohammadhassan Behroozi,Khalil Alipour,Behrouz Mashhadi,Samaneh Arabi 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10

In the present study, the main concern regarding application requirements was to devise and introduce a motion planning method to guarantee system robustness against uncertainties due to any disturbances or inaccuracies in the system dynamics. The robot motion planning has been divided in two different problems: path planning and velocity planning. In the former, use was made of a odular”path planner, each module consisting of pure displacement and pure rotation. In the latter, the velocity planning problem was transformed into an integrated planning and control one. Care is taken for energy being conserved as much as possible within each module of the path. Since an open-loop optimal control may suffer from the lack of robustness, and owing to the fact that the two-point-boundary-value problem that it leads to may not be solvable, a Neural Network system has been introduced to close the control loop. The Ritz method as a direct approach in the calculus of variations is proposed to train the neural network, thus introducing a robust closed-loop control. In this study, optimization of the sub-motions of the total motion was addressed. Furthermore, a combination of optimal Ritz-based method and neural network was suggested as a robust motion planning approach for differentially-driven mobile robots.

Motion planning of a steam generator mobile tube-inspection robot

Biying Xu,Ge Li,Kuan Zhang,Hegao Cai,Jie Zhao,Jizhuang Fan 한국원자력학회 2022 Nuclear Engineering and Technology Vol.54 No.4

Under the influence of nuclear radiation, the reliability of steam generators (SGs) is an important factorin the efficiency and safety of nuclear power plant (NPP) reactors. Motion planning that remotely manipulates an SG mobile tube-inspection robot to inspect SG heat transfer tubes is the mainstream trendof NPP robot development. To achieve motion planning, conditional traversal is usually used for baseposition optimization, and then the A* algorithm is used for path planning. However, the proposedapproach requires considerable processing time and has a single expansion during path planning andplan paths with many turns, which decreases the working speed of the robot. Therefore, to reduce thecalculation time and improve the efficiency of motion planning, modifications such as the matrixmethod, improved parent node, turning cost, and improved expanded node were proposed in this study. We also present a comprehensive evaluation index to evaluate the performance of the improved algorithm. We validated the efficiency of the proposed method by planning on a tube sheet with square-typetube arrays and experimenting with Model SG.

Hierarchical Fuzzy Motion Planning for Humanoid Robots Using Locomotion Primitives and a Global Navigation Path

Yong-Tae Kim 한국지능시스템학회 2010 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.10 No.3

This paper presents a hierarchical fuzzy motion planner for humanoid robots in 3D uneven environments. First, we define both motion primitives and locomotion primitives of humanoid robots. A high-level planner finds a global path from a global navigation map that is generated based on a combination of 2.5 dimensional maps of the workspace. We use a passage map, an obstacle map and a gradient map of obstacles to distinguish obstacles. A mid-level planner creates subgoals that help the robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. We use a local obstacle map to find the subgoals along the global path. A low-level planner searches for an optimal sequence of locomotion primitives between subgoals by using fuzzy motion planning. We verify our approach on a virtual humanoid robot in a simulated environment. Simulation results show a reduction in planning time and the feasibility of the proposed method.

Kinodynamic Motion Planning with Artificial Wavefront Propagation

Ogay, Dmitriy,Kim, Eun-Gyung The Korea Institute of Information and Commucation 2013 Journal of information and communication convergen Vol.11 No.4

In this study, we consider the challenges in motion planning for automated driving systems. Most of the existing online motion-planning algorithms, which take dynamics into account, find it difficult to operate in an environment with narrow passages. Some of the existing algorithms overcome this by offline preprocessing if environment is known. In this work an online algorithm for motion planning with dynamics in an unknown cluttered environment with narrow passages is presented. It utilizes an idea of hybrid planning with sampling- and discretization-based motion planners, which run simultaneously in a full configuration space and a derived reduced space. The proposed algorithm has been implemented and tested with a real autonomous vehicle. It provides significant improvements in computational time performance over basic planning algorithms and allows the generation of smoother paths than those generated by the recently developed hybrid motion planners.

Design and Analysis of Decoupled Parallel Mechanism with Redundant Actuator

김선호,김선호,전동수,신현표,인우성,김종원 한국정밀공학회 2009 International Journal of Precision Engineering and Vol. No.

This paper presents a redundantly actuated six degrees-of-freedom parallel kinematic mechanism with a partially decoupled architecture in its rotational motion. This mechanism is developed to eliminate kinematic complexity of original Eclipse-II known as a redundant parallel mechanism. Since the original Eclipse-II mechanism use kinematic redundancy of parallel mechanism to achieve an advantage in enlarging the workspace of the system, it needs a motion planning algorithm to choose the specific control inputs to determine the desired motion trajectory. This motion planning algorithm causes difficulty in achieving real-time control performance due to its structural complexity. However the redundant parallel mechanism presented in this paper is a redundant parallel mechanism with partially decoupled architecture in its rotational motion. Therefore modified Eclipse-II redundant parallel mechanism can realize effective real-time control performances and continuous 360-degree rotational motion in any direction of the moving platform with six degrees of freedom.

Heuristics for Motion Planning Based on Learning in Similar Environments

Ogay, Dmitriy,Kim, Eun-Gyung The Korea Institute of Information and Commucation 2014 Journal of information and communication convergen Vol.12 No.2

This paper discusses computer-generated heuristics for motion planning. Planning with many degrees of freedom is a challenging task, because the complexity of most planning algorithms grows exponentially with the number of dimensions of the problem. A well-designed heuristic may greatly improve the performance of a planning algorithm in terms of the computation time. However, in recent years, with increasingly challenging high-dimensional planning problems, the design of good heuristics has itself become a complicated task. In this paper, we present an approach to algorithmically develop a heuristic for motion planning, which increases the efficiency of a planner in similar environments. To implement the idea, we generalize modern motion planning algorithms to an extent, where a heuristic is represented as a set of random variables. Distributions of the variables are then analyzed with computer learning methods. The analysis results are then utilized to generate a heuristic. During the experiments, the proposed approach is applied to several planning tasks with different algorithms and is shown to improve performance.

모션 면적을 이용한 버추얼 카메라의 자동 제어 기법

권지용,이인권 (사)한국컴퓨터그래픽스학회 2008 컴퓨터그래픽스학회논문지 Vol.14 No.2

We propose a method to determine camera parameters for character motion, which considers the motion by itself. The basic idea is to approximately compute the area swept by the motion of the character’s links that are orthogonally projected onto the image plane, which we call “Motion Area”. Using the motion area, we can determine good fixed camera parameters and camera paths for a given character motion in the off-line or real-time camera control. In our experimental results, we demonstrate that our camera path generation algorithms can compute a smooth moving camera path while the camera effectively displays the dynamic features of character motion. Our methods can be easily used in combination with the method for generating occlusion-free camera paths. We expect that our methods can also be utilized by the general camera planning method as one of heuristics for measuring the visual quality of the scenes that include dynamically moving characters. 본 논문에서는 캐릭터의 모션을 고려한 카메라의 파라미터를 결정하는 방법을 제안한다. 기본적인 아이디어는 캐릭터의 각각의 링크가 화면상의 평면에 투영되었을 때의 움직임을 면적으로 계산하여 이를 활용하는 것이다. 우리는 이러한 면적을 ‘모션면적’이라고 정의하였다. 모션 면적을 이용하면 실시간 혹은 오프라인 상에서 캐릭터의 모션에 대한 적절한 카메라 경로 혹은 고정된 카메라의 위치를 결정할 수 있다. 우리는 실험을 통해서 제안하는 방법으로 만들어진 카메라 경로가 부드럽게 움직임과 동시에 캐릭터의 모션을 보다 역동적으로 보이게끔 한다는 사실을 관측하였다. 또한 제안하는 방법은 카메라의 시선이 장애물과 충돌하지 않도록 하는 제어 기법과 쉽게 합쳐져서 사용될 수 있다. 우리는 또한 제안하는 방법이 역동적으로 움직이는 캐릭터를 포함하는 장면에서의 시각적 품질을 측정하는 도구로써 다른 일반적인 카메라 제어 기법과 함께 쓰일 수 있을 것으로 기대한다.

Probabilistic Prediction based Automated Driving Motion Planning Algorithm for Lane Change

Heungseok Chae,Myungsu Lee,Kyongsu Yi 제어로봇시스템학회 2017 제어로봇시스템학회 국제학술대회 논문집 Vol.2017 No.10

This paper describes design and evaluation of a motion planning algorithm of automated vehicle for lane change. Autonomous lane change is necessary for highway automated driving. In a perception part, surrounding vehicles’ states are estimated and predicted. The motion of ego vehicle is also predicted and these prediction information is utilized in motion planning. In motion planning part, driving mode, which is lane keeping or lane change, target states and constraints are decided. Lane change mode decision is determined based on surrounding vehicles states and ego vehicle states. Lane change availability is decided by the safety distance that considers relative velocity and relative position of subject and surrounding vehicles. If the ego vehicle do not perform to lane change, the most proper position is selected considering the probabilistic prediction information and the safety distance. And the longitudinal control is applied to move desired merge position. A safety driving envelope is defined based on information of surrounding vehicles behaviors and is used for control constraints. In control part, the controller is designed to obtain the desired steering angle and longitudinal acceleration using a model predictive control (MPC) with constraints. The proposed automated driving algorithm has been evaluated via computer simulation studies.

Adaptive RRT 를 사용한 고 자유도 다물체 로봇 시스템의 효율적인 경로계획

김동형(Dong-Hyung Kim),최윤성(Youn-Sung Choi),염서군(Rui-Jun Yan),라로평(Lu-Ping Luo),이지영(Ji Yeong Lee),한창수(Chang-Soo Han) 제어로봇시스템학회 2015 제어·로봇·시스템학회 논문지 Vol.21 No.3

This paper proposes an adaptive RRT (Rapidly-exploring Random Tree) for path planning of high DOF multibody robotic system. For an efficient path planning in high-dimensional configuration space, the proposed algorithm adaptively selects the robot bodies depending on the complexity of path planning. Then, the RRT grows only using the DOFs corresponding with the selected bodies. Since the RRT is extended in the configuration space with adaptive dimensionality, the RRT can grow in the lower dimensional configuration space. Thus the adaptive RRT method executes a faster path planning and smaller DOF for a robot. We implement our algorithm for path planning of 19 DOF robot, AMIRO. The results from our simulations show that the adaptive RRTbased path planner is more efficient than the basic RRT-based path planner.