• Title/Summary/Keyword: 3-D Path Planning

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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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Collision-Free Path Planning of Articulated Robot using Configuration Space (형상 공간을 이용한 다관절 로보트의 충돌 회피 경로 계획)

  • Kim, J.H.;Choi, J.S.;Kang, H.Y.;Kim, Dong-Won;Yang, S.M.
    • Transactions of the Korean Society of Automotive Engineers
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    • v.2 no.6
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    • pp.57-65
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    • 1994
  • A collision-free path planning algorithm between an articulated robot and polyhedral obstacles using configuration space is presented. In configuration space, a robot is treated as a point and obstacles are treated as grown forbidden regions. Hence path planning problem is transformed into moving a point from start position to goal position without entering forbidden regions. For mapping to 3D joint space, slice projection method is used for first revolute joint and inverse kinematics is used for second and third revolute joint considering kinematic characteristics of industrial robot. Also, three projected 2D joint spaces are used in search of collision-free path. A proper example is provided to illustrate the proposed algorithm.

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Development of Vision based Autonomous Obstacle Avoidance System for a Humanoid Robot (휴머노이드 로봇을 위한 비전기반 장애물 회피 시스템 개발)

  • Kang, Tae-Koo;Kim, Dong-Won;Park, Gwi-Tae
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.1
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    • pp.161-166
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    • 2011
  • This paper addresses the vision based autonomous walking control system. To handle the obstacles which exist beyond the field of view(FOV), we used the 3d panoramic depth image. Moreover, to decide the avoidance direction and walking motion of a humanoid robot for the obstacle avoidance by itself, we proposed the vision based path planning using 3d panoramic depth image. In the vision based path planning, the path and walking motion are decided under environment condition such as the size of obstacle and available avoidance space. The vision based path planning is applied to a humanoid robot, URIA. The results from these evaluations show that the proposed method can be effectively applied to decide the avoidance direction and the walking motion of a practical humanoid robot.

Implementation of Wheelchair Robot Applying SLAM and Global Path Planning Methods Suitable for Indoor Autonomous Driving (실내 자율주행에 적합한 SLAM과 전역경로생성 방법을 적용한 휠체어로봇 구현)

  • Baek, Su-Jin;Kim, A-Hyeon;Kim, Jong-Wook
    • IEMEK Journal of Embedded Systems and Applications
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    • v.16 no.6
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    • pp.293-297
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    • 2021
  • This paper presents how to create a 3D map and solve problems related to generating a global path planning for navigation. Map creation and localization were performed using the RTAB-Map package to create a 3D map of the environment. In addition, when the target point is within the obstacle space, the problem of not generating a global path was solved using the asr_navfn package. The performance of the proposed system is validated through experiments with a wheelchair-type robot.

DL-RRT* algorithm for least dose path Re-planning in dynamic radioactive environments

  • Chao, Nan;Liu, Yong-kuo;Xia, Hong;Peng, Min-jun;Ayodeji, Abiodun
    • Nuclear Engineering and Technology
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    • v.51 no.3
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    • pp.825-836
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    • 2019
  • One of the most challenging safety precautions for workers in dynamic, radioactive environments is avoiding radiation sources and sustaining low exposure. This paper presents a sampling-based algorithm, DL-RRT*, for minimum dose walk-path re-planning in radioactive environments, expedient for occupational workers in nuclear facilities to avoid unnecessary radiation exposure. The method combines the principle of random tree star ($RRT^*$) and $D^*$ Lite, and uses the expansion strength of grid search strategy from $D^*$ Lite to quickly find a high-quality initial path to accelerate convergence rate in $RRT^*$. The algorithm inherits probabilistic completeness and asymptotic optimality from $RRT^*$ to refine the existing paths continually by sampling the search-graph obtained from the grid search process. It can not only be applied to continuous cost spaces, but also make full use of the last planning information to avoid global re-planning, so as to improve the efficiency of path planning in frequently changing environments. The effectiveness and superiority of the proposed method was verified by simulating radiation field under varying obstacles and radioactive environments, and the results were compared with $RRT^*$ algorithm output.

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.

Hybrid System Modeling and Control for Path Planning and Autonomous Navigation of Wheeled Mobile Robots (차륜형 이동로봇의 경로 계획과 자율 주행을 위한 하이브리드 시스템 모델과 제어)

  • Im, Mi-Seop;Im, Jun-Hong
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.49 no.1
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    • pp.33-40
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    • 2000
  • In this paper, an integrated method for the path planning and motion control of wheeled mobile robots using a hybrid system model and control is presented. The hybrid model including the continuous dynamics and discrete dynamics with the continuous and discrete state vector is derived for a two wheel driven mobile robot. The architecture of the hybrid control system for real time path planning and following is designed which has the 3-layered hierarchical structure : the discrete event system using the digital automata as the higher process, the continuous state system for the wheel velocity controls as the lower process, and the interface system as the interaction process between the continuous system as the low level and the discrete event system as the high level. The reference motion commands for autonomous navigation are generated by the abstracted motion in the discrete event system. The motion control tasks including the feasible path planning and autonomous motion control with various initial conditions are investigated as the applications by the simulation studies.

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An Analysis on the Influential Factors to Set the Path Planning Algorithm for Unmanned Ground Vehicle in Combat Environment (전장환경에서 무인전투차량의 경로계획 알고리즘설정 영향요인 분석)

  • Baek, Jong-Sung;Lee, Choon-Joo
    • The Journal of Korea Robotics Society
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    • v.4 no.3
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    • pp.233-242
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    • 2009
  • This paper briefly reviews the path planning methods that are applicable to the autonomous mobile robots for the military. Two distinct path search algorithms, $A^*$ and $D^*$ that are most popular and flexible in public applications, among those reviewed are coded and analyzed in terms of combat environment assessment factors called METT+TC for the area of operations. The results imply that it is important to consider the characteristics of defense acquisition process and the specific requirements of defense operation so that the successful technology development of the Robot products is directly linked to the defense procurement of Robot products.

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Improvement of RRT*-Smart Algorithm for Optimal Path Planning and Application of the Algorithm in 2 & 3-Dimension Environment (최적 경로 계획을 위한 RRT*-Smart 알고리즘의 개선과 2, 3차원 환경에서의 적용)

  • Tak, Hyeong-Tae;Park, Cheon-Geon;Lee, Sang-Chul
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.27 no.2
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    • pp.1-8
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    • 2019
  • Optimal path planning refers to find the safe route to the destination at a low cost, is a major problem with regard to autonomous navigation. Sampling Based Planning(SBP) approaches, such as Rapidly-exploring Random Tree Star($RRT^*$), are the most influential algorithm in path planning due to their relatively small calculations and scalability to high-dimensional problems. $RRT^*$-Smart introduced path optimization and biased sampling techniques into $RRT^*$ to increase convergent rate. This paper presents an improvement plan that has changed the biased sampling method to increase the initial convergent rate of the $RRT^*$-Smart, which is specified as m$RRT^*$-Smart. With comparison among $RRT^*$, $RRT^*$-Smart and m$RRT^*$-Smart in 2 & 3-D environments, m$RRT^*$-Smart showed similar or increased initial convergent rate than $RRT^*$ and $RRT^*$-Smart.

Fuzzy Footstep Planning for Humanoid Robots Using Locomotion Primitives (보행 프리미티브 기반 휴머노이드 로봇의 퍼지 보행 계획)

  • Kim, Yong-Tae;Noh, Su-Hee;Han, Nam-I
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.04a
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    • pp.7-10
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    • 2007
  • This paper presents a fuzzy footstep planner for humanoid robots in complex environments. First, we define locomotion primitives for humanoid robots. A global planner finds a global path from a navigation map that is generated based on a combination of 2.5 dimensional maps of the 3D workspace. A local planner searches for an optimal sequence of locomotion primitives along the global path by using fuzzy footstep 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.

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