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

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Any-angle Path Planning Algorithm considering Angular Constraint for Marine Robot (해양 로봇의 회전 반경을 고려한 경로 계획 알고리즘)

  • Kim, Han-Guen;Myung, Hyun;Choi, Hyun-Taek
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.4
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    • pp.365-370
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    • 2012
  • Most path planning algorithms for a marine robot in the ocean environment have been developed without considering the robot's heading angle. As a result, the robot has a difficulty in following the path correctly. In this paper, we propose a limit-cycle circle set that applies to the $Theta^*$ algorithm. The minimum turning radius of a marine robot is calculated using a limit-cycle circle set, and circles of this radius is used to generate a configuration space of an occupancy grid map. After applying $Theta^*$ to this configuration space, the limit-cycle circle set is also applied to the start and end nodes to find the appropriate path with specified heading angles. The benefit of this algorithm is its fast computation time compared to other 3-D ($x,y,{\theta}$) path planning algorithms, along with the fact that it can be applied to the 3-D kinematic state of the robot. We simulate the proposed algorithm and compare it with 3-D $A^*$ and 3-D $A^*$ with post smoothing algorithms.

Planning of Safe and Efficient Local Path based on Path Prediction Using a RGB-D Sensor (RGB-D센서 기반의 경로 예측을 적용한 안전하고 효율적인 지역경로 계획)

  • Moon, Ji-Young;Chae, Hee-Won;Song, Jae-Bok
    • The Journal of Korea Robotics Society
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    • v.13 no.2
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    • pp.121-128
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    • 2018
  • Obstacle avoidance is one of the most important parts of autonomous mobile robot. In this study, we proposed safe and efficient local path planning of robot for obstacle avoidance. The proposed method detects and tracks obstacles using the 3D depth information of an RGB-D sensor for path prediction. Based on the tracked information of obstacles, the paths of the obstacles are predicted with probability circle-based spatial search (PCSS) method and Gaussian modeling is performed to reduce uncertainty and to create the cost function of caution. The possibility of collision with the robot is considered through the predicted path of the obstacles, and a local path is generated. This enables safe and efficient navigation of the robot. The results in various experiments show that the proposed method enables robots to navigate safely and effectively.

Passage Planning in Coastal Waters for Maritime Autonomous Surface Ships using the D* Algorithm

  • Hyeong-Tak Lee;Hey-Min Choi
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.3
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    • pp.281-287
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    • 2023
  • Establishing a ship's passage plan is an essential step before it starts to sail. The research related to the automatic generation of ship passage plans is attracting attention because of the development of maritime autonomous surface ships. In coastal water navigation, the land, islands, and navigation rules need to be considered. From the path planning algorithm's perspective, a ship's passage planning is a global path-planning problem. Because conventional global path-planning methods such as Dijkstra and A* are time-consuming owing to the processes such as environmental modeling, it is difficult to modify a ship's passage plan during a voyage. Therefore, the D* algorithm was used to address these problems. The starting point was near Busan New Port, and the destination was Ulsan Port. The navigable area was designated based on a combination of the ship trajectory data and grid in the target area. The initial path plan generated using the D* algorithm was analyzed with 33 waypoints and a total distance of 113.946 km. The final path plan was simplified using the Douglas-Peucker algorithm. It was analyzed with a total distance of 110.156 km and 10 waypoints. This is approximately 3.05% less than the total distance of the initial passage plan of the ship. This study demonstrated the feasibility of automatically generating a path plan in coastal navigation for maritime autonomous surface ships using the D* algorithm. Using the shortest distance-based path planning algorithm, the ship's fuel consumption and sailing time can be minimized.

A Development of Simulation System for 3D Path Planning of UUV (무인잠수정의 3차원 경로계획을 위한 시뮬레이션 시스템 개발)

  • Shin, Seoung-Chul;Seon, Hwi-Joon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2010.10a
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    • pp.701-704
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    • 2010
  • In studying an autonomous navigation technique of UUV(Unmaned Underwater Vehicle), one of the many fundamental techniques is to plan a 3D path to complete the mission via realtime information received by sonar showing landscapes and obstacles. The simulation system is necessary to verify the algorithm in researching and developing 3D path planning of UUV. It is because 3D path planning of UUV should consider guide control, the dynamics, ocean environment, and search sonar models on the basis of obstacle avoidance technique. The simulation system developed in this paper visualizes the UUV's movement of avoiding obstacles, arriving at the goal position via waypoints by using C++ and OpenGL. Plus, it enables the user to setup the various underwater environment and obstacles by a user interface. It also provides a generalization that can verify path planning algorithm of UUV studied in any developing environment.

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3-Dimensional Path Planning and Guidance for High Altitude Long Endurance UAV Including a Solar Power Model (태양광 전력모델을 포함한 장기체공 무인기의 3차원 경로계획 및 유도)

  • Oh, Su-hun;Kim, Kap-dong;Park, Jun-hyun
    • Journal of Advanced Navigation Technology
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    • v.20 no.5
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    • pp.401-407
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    • 2016
  • This paper introduces 3-dimensional path planning and guidance including power model for high altitude long endurance (HALE) UAV using solar energy. Dubins curve used in this paper has advantage of being directly available to apply path planning. However, most of the path planning problems using Dubins curve are defined in a two-dimensional plan. So, we used 3-dimensional Dubins path generation algorithm which was studied by Randal W. Beard. The aircraft model which used in this paper does not have an aileron. So we designed lateral controller by using a rudder. And then, we were conducted path tracking simulations by using a nonlinear path tracking algorithm. We generate examples according to altitude conditions. From the path tracking simulation results, we confirm that the path tracking is well on the flight path. Finally, we were modeling the power system of HALE UAVs and conducting path tracking simulation during 48hours. Modeling the amount of power generated by the solar cell through the calculation of the solar energy yield. And, we show the 48hours path tracking simulation results.

An Algorithm for the Removing of Offset Loop Twists during the Tool Path Generation of FDM 3D Printer (FDM 3D 프린팅의 경로생성을 위한 옵?루프의 꼬임제거 알고리즘)

  • Olioul, Islam Md.;Kim, Ho-Chan
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.16 no.3
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    • pp.1-8
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    • 2017
  • Tool path generation is a part of process planning in 3D printing. This is done before actual printing by a computer rather than an AM machine. The mesh geometry of the 3D model is sliced layer-by-layer along the Z-axis and tool paths are generated from the sliced layers. Each 2-dimensional layer can have two types of printing paths: (i) shell and (ii) infill. Shell paths are made of offset loops. During shell generation, twists can be produced in offset loops which will cause twisted tool paths. As a twisted tool path cannot be printed, it is necessary to remove these twists during process planning. In this research, An algorithm is presented to remove twists from the offset loops. To do so the path segments are traversed to identify twisted points. Outer offset loops are represented in the counter-clockwise segment order and clockwise rotation for the inner offset loop to decide which twisted loop should be removed. After testing practical 3D models, the proposed algorithm is verified to use in tool path generation for 3D printing.

Parallelization of Probabilistic RoadMap for Generating UAV Path on a DTED Map (DTED 맵에서 무인기 경로 생성을 위한 Probabilistic RoadMap 병렬화)

  • Noh, Geemoon;Park, Jihoon;Min, Chanoh;Lee, Daewoo
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.50 no.3
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    • pp.157-164
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    • 2022
  • In this paper, we describe how to implement the mountainous terrain, radar, and air defense network for UAV path planning in a 3-D environment, and perform path planning and re-planning using the PRM algorithm, a sampling-based path planning algorithm. In the case of the original PRM algorithm, the calculation to check whether there is an obstacle between the nodes is performed 1:1 between nodes and is performed continuously, so the amount of calculation is greatly affected by the number of nodes or the linked distance between nodes. To improve this part, the proposed LineGridMask method simplifies the method of checking whether obstacles exist, and reduces the calculation time of the path planning through parallelization. Finally, comparing performance with existing PRM algorithms confirmed that computational time was reduced by up to 88% in path planning and up to 94% in re-planning.

A Shortest Path Planning Algorithm for Mobile Robots Using a Modified Visibility Graph Method

  • Lee, Duk-Young;Koh, Kyung-Chul;Cho, Hyung-Suck
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1939-1944
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    • 2003
  • This paper presents a global path planning algorithm based on a visibility graph method, and applies additionally various constraints for constructing the reduced visibility graph. The modification algorithm for generating the rounded path is applied to the globally shortest path of the visibility graph using the robot size constraint in order to avoid the obstacle. In order to check the visibility in given 3D map data, 3D CAD data with VRML format is projected to the 2D plane of the mobile robot, and the projected map is converted into an image for easy map analysis. The image processing are applied to this grid map for extracting the obstacles and the free space. Generally, the tree size of visibility graph is proportional to the factorial of the number of the corner points. In order to reduce the tree size and search the shortest path efficiently, the various constraints are proposed. After short paths that crosses the corner points of obstacles lists up, the shortest path among these paths is selected and it is modified to the combination of the line path and the arc path for the mobile robot to avoid the obstacles and follow the rounded path in the environment. The proposed path planning algorithm is applied to the mobile robot LCAR-III.

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Single-Query Probabilistic Roadmap Planning Algorithm using Remembering Exploration Method (기억-탐험 방법을 이용한 단일-질의 확률 로드맵 계획 알고리즘)

  • Kim, Jung-Tae;Kim, Dae-Jin
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.4
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    • pp.487-491
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    • 2010
  • In this paper we propose a new single-query path planning algorithm for working well in high-dimensional configuration space. With the notice of the similarity between single-query algorithms with exploration algorithms, we propose a new path planning algorithm, which applies the Remembering Exploration method, which is one of exploration algorithms, to a path-planning problem by selecting a node from a roadmap, finding out the neighbor nodes from the node, and then inserting the neighbor nodes into the roadmap, recursively. For the performance comparison, we had experiments in 2D and 3D environments and compared the time to find out the path. In the results our algorithm shows the superior performance than other path planning algorithms.

Grasping a Target Object in Clutter with an Anthropomorphic Robot Hand via RGB-D Vision Intelligence, Target Path Planning and Deep Reinforcement Learning (RGB-D 환경인식 시각 지능, 목표 사물 경로 탐색 및 심층 강화학습에 기반한 사람형 로봇손의 목표 사물 파지)

  • Ryu, Ga Hyeon;Oh, Ji-Heon;Jeong, Jin Gyun;Jung, Hwanseok;Lee, Jin Hyuk;Lopez, Patricio Rivera;Kim, Tae-Seong
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.9
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    • pp.363-370
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    • 2022
  • Grasping a target object among clutter objects without collision requires machine intelligence. Machine intelligence includes environment recognition, target & obstacle recognition, collision-free path planning, and object grasping intelligence of robot hands. In this work, we implement such system in simulation and hardware to grasp a target object without collision. We use a RGB-D image sensor to recognize the environment and objects. Various path-finding algorithms been implemented and tested to find collision-free paths. Finally for an anthropomorphic robot hand, object grasping intelligence is learned through deep reinforcement learning. In our simulation environment, grasping a target out of five clutter objects, showed an average success rate of 78.8%and a collision rate of 34% without path planning. Whereas our system combined with path planning showed an average success rate of 94% and an average collision rate of 20%. In our hardware environment grasping a target out of three clutter objects showed an average success rate of 30% and a collision rate of 97% without path planning whereas our system combined with path planning showed an average success rate of 90% and an average collision rate of 23%. Our results show that grasping a target object in clutter is feasible with vision intelligence, path planning, and deep RL.