• Title, Summary, Keyword: motion planning

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Kinodynamic Motion Planning with Artificial Wavefront Propagation

  • Ogay, Dmitriy;Kim, Eun-Gyung
    • Journal of information and communication convergence engineering
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    • v.11 no.4
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    • pp.274-281
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    • 2013
  • 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.

Heuristics for Motion Planning Based on Learning in Similar Environments

  • Ogay, Dmitriy;Kim, Eun-Gyung
    • Journal of information and communication convergence engineering
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    • v.12 no.2
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    • pp.116-121
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    • 2014
  • 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.

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

  • Kim Byoung-Ho
    • International Journal of Control, Automation, and Systems
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    • v.4 no.2
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    • pp.217-226
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    • 2006
  • 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.

Sensor-Based Motion Planning for Mobile Robots

  • Park, Jong-Suk;Lee, Chong-won
    • 제어로봇시스템학회:학술대회논문집
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    • pp.37.3-37
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    • 2002
  • $\textbullet$ Mobile robots $\textbullet$ Sensor-based motion planning $\textbullet$ Potential field $\textbullet$ Local minimum-free motion $\textbullet$ Virtual target point $\textbullet$ Set of linked line segments $\textbullet$ We build a sensor-based motion planning using virtual target point for free of local minimum

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Task and Motion Planning for Grasping Obstructed Object in Cluttered Environment (복잡 환경에서 가로막힌 물체 잡기를 위한 작업-모션 계획의 연계)

  • Lee, Seokjun;Kim, Incheol
    • The Journal of Korea Robotics Society
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    • v.14 no.2
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    • pp.104-113
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    • 2019
  • Object manipulation in cluttered environments remains an open hard problem. In cluttered environments, grasping objects often fails for various reasons. This paper proposes a novel task and motion planning scheme to grasp objects obstructed by other objects in cluttered environments. Task and motion planning (TAMP) aims to generate a sequence of task-level actions where its feasibility is verified in the motion space. The proposed scheme contains an open-loop consisting of three distinct phases: 1) Generation of a task-level skeleton plan with pose references, 2) Instantiation of pose references by motion-level search, and 3) Re-planning task based on the updated state description. By conducting experiments with simulated robots, we show the high efficiency of our scheme.

An Interphalangeal Coordination-based Joint Motion Planning for Humanoid Fingers: Experimental Verification

  • Kim, Byoung-Ho
    • International Journal of Control, Automation, and Systems
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    • v.6 no.2
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    • pp.234-242
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    • 2008
  • The purpose of this paper is to verify the practical effectiveness of an interphalangeal coordination-based joint motion planning method for humanoid finger operations. For the purpose, several experiments have been performed and comparative experimental results are shown. Through the experimental works, it is confirmed that according to the employed joint motion planning method, the joint configurations for a finger's trajectory can be planned stably or not, and consequently the actual joint torque command for controlling the finger can be made moderately or not. Finally, this paper analyzes that the interphalangeal coordination-based joint motion planning method is practically useful for implementing a stable finger manipulation. It is remarkably noted that the torque pattern by the method is well-balanced. Therefore, it is expected that the control performance of humanoid or prosthetic fingers can be enhanced by the method.

Development of 6-DOF Equations of Motion for a Planning Boat Based on the Results of Sea Trial Tests

  • Jeon, Myung-Jun;Lee, Dong-Hyun;Yoon, Hyeon-Kyu
    • Journal of Navigation and Port Research
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    • v.40 no.5
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    • pp.231-239
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    • 2016
  • In general, the attitude of a high-speed planning boat changes following a speed change. Since the hydrodynamic forces acting on a ship differ according to the change of its underwater shape, it is difficult to estimate its hydrodynamic force compared to that of a large commercial ship. In this paper, 6 Degrees Of Freedom (DOF) equations of motion that express the maneuvering motion of a planning boat are modeled by analyzing its motion characteristics based on various sea trial tests. Finally, a maneuvering simulation is carried out and a validation of the equations of motion is confirmed with the results of sea trial tests.

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

  • Kim, Yong-Tae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.10 no.3
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    • pp.203-209
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    • 2010
  • 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.

Repetitive Periodic Motion Planning and Directional Drag Optimization of Underwater Articulated Robotic Arms

  • Jun Bong-Huan;Lee Jihong;Lee Pan-Mook
    • International Journal of Control, Automation, and Systems
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    • v.4 no.1
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    • pp.42-52
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    • 2006
  • In order to utilize hydrodynamic drag force on articulated robots moving in an underwater environment, an optimum motion planning procedure is proposed. The drag force acting on cylindrical underwater arms is modeled and a directional drag measure is defined as a quantitative measure of reaction force in a specific direction in a workspace. A repetitive trajectory planning method is formulated from the general point-to-point trajectory planning method. In order to globally optimize the parameters of repetitive trajectories under inequality constraints, a 2-level optimization scheme is proposed, which adopts the genetic algorithm (GA) as the 1st level optimization and sequential quadratic programming (SQP) as the 2nd level optimization. To verify the validity of the proposed method, optimization examples of periodic motion planning with the simple two-link planner robot are also presented in this paper.

Motion Planning for Legged Robots Using Locomotion Primitives in the 3D Workspace (3차원 작업공간에서 보행 프리미티브를 이용한 다리형 로봇의 운동 계획)

  • Kim, Yong-Tae;Kim, Han-Jung
    • The Journal of Korea Robotics Society
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    • v.2 no.3
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    • pp.275-281
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    • 2007
  • 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 of the 3D workspace is proposed. A global navigation map is obtained using 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.

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