• 제목/요약/키워드: Advanced Path Planning

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유니사이클 스웜 로봇의 자기조직화를 위한 LOS 기반의 국소 경로 계획 (LOS-based Local Path Planning for Self organization of Unicycle Swarm Robots)

  • 정하민;김동헌
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2009년도 제40회 하계학술대회
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    • pp.1881_1882
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    • 2009
  • Simple quadratic potential functions for unicycle robot path planning are presented, where proposed algorithm for path planning has the different environment for each robot based on LOS(Line Of Sight) between a target and an obstacle, unlike a conventional path planning. In doing so, the proposed algorithm assumes that each swarm robot equips its own vision instead of a ceiling camera. In particular, this paper presents that each robot follows its different local leader. As a result proposed algorithm reduces local minimum problems by the help of each local leader.

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METRO - 레이저 거리계를 장착한 자율 이동로봇 (METRO - A Free Ranging Mobile Robot with a Laser Range Finder)

  • 차영엽;권대갑
    • 제어로봇시스템학회논문지
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    • 제2권3호
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    • pp.200-208
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    • 1996
  • This paper describes the mechanism, guidance, sensor system, and navigation algorithm of METRO, a free ranging mobile robot. METRO is designed for use in structured surroundings or factory environments rather than unstructured natural environments. An overview of the physical configuration of the mobile robot is presented as well as a description of its sensor system, an omnidirectional laser range finder. Except for the global path planning algorithm, a guidance and a navigation algorithm with a local path planning algorithm are used to navigate the mobile robot. In METRO the computer support is divided into a supervisor with image processing and local path planning and a slave with motor control. The free ranging mobile robot is self-controlled and all processing being performed on board.

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Markov Decision Process-based Potential Field Technique for UAV Planning

  • MOON, CHAEHWAN;AHN, JAEMYUNG
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제25권4호
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    • pp.149-161
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    • 2021
  • This study proposes a methodology for mission/path planning of an unmanned aerial vehicle (UAV) using an artificial potential field with the Markov Decision Process (MDP). The planning problem is formulated as an MDP. A low-resolution solution of the MDP is obtained and used to define an artificial potential field, which provides a continuous UAV mission plan. A numerical case study is conducted to demonstrate the validity of the proposed technique.

자율주차 상황에서 차량 구속 조건 고려에 따른 경로 계획 및 추종 성능의 비교 분석 (A Comparative Analysis of Path Planning and Tracking Performance According to the Consideration of Vehicle's Constraints in Automated Parking Situations)

  • 김민수;안준우;김민성;신민용;박재흥
    • 로봇학회논문지
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    • 제16권3호
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    • pp.250-259
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    • 2021
  • Path planning is one of the important technologies for automated parking. It requires to plan a collision-free path considering the vehicle's kinematic constraints such as minimum turning radius or steering velocity. In a complex parking lot, Rapidly-exploring Random Tree* (RRT*) can be used for planning a parking path, and Reeds-Shepp or Hybrid Curvature can be applied as a tree-extension method to consider the vehicle's constraints. In this case, each of these methods may affect the computation time of planning the parking path, path-tracking error, and parking success rate. Therefore, in this study, we conduct comparative analysis of two tree-extension functions: Reeds-Shepp (RS) and Hybrid Curvature (HC), and show that HC is a more appropriate tree-extension function for parking path planning. The differences between the two functions are introduced, and their performances are compared by applying them with RRT*. They are tested at various parking scenarios in simulation, and their advantages and disadvantages are discussed by computation time, cross-track error while tracking the path, parking success rate, and alignment error at the target parking spot. These results show that HC generates the parking path that an autonomous vehicle can track without collisions and HC allows the vehicle to park with lower alignment error than those of RS.

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

  • 오수헌;김갑동;박준현
    • 한국항행학회논문지
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    • 제20권5호
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    • pp.401-407
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    • 2016
  • 본 논문에서는 태양광 장기체공 무인기의 전력모델을 포함한 3차원 경로계획과 유도에 대하여 기술한다. 본 논문에서 사용한 Dubins curve는 계산속도가 빨라 경로계획에 곧바로 적용이 가능하다는 장점이 있다. 하지만 Dubins curve의 경로생성 문제는 2차원 평면에서 정의되기 때문에 실제 항공기의 경로계획을 위해 Randal W. Beard에 의해 수행된 비행 경로각의 한계를 고려하여, 고도 차이에 따라 선회경로를 추가하는 방식의 3차원 Dubins 경로생성 알고리즘을 활용하였다. 본 논문에서 사용한 항공기 모델은 Aileron이 없기 때문에 Rudder를 사용하여 횡축 방향 제어기를 설계하였으며, 비선형 경로추종 유도기법을 사용하여 경로추종 시뮬레이션을 수행하였다. 고도조건에 따른 예제를 생성하였으며, 시뮬레이션 결과 생성된 경로를 잘 추종하는 것을 확인하였다. 마지막으로 태양에너지 수율에 대한 계산식을 통해 태양광 장기체공 무인기의 전력 시스템을 모델링하여 48시간 연속비행 시뮬레이션을 실시하였고, 이에 대한 시뮬레이션 결과를 제시하였다.

A Process Planning System for Machining of Dies for Auto-Body Production-Operation Planning and NC Code Post-Processing

  • Dongmok Sheen;Lee, Chang-Ho;Noh, Sang-Do;Lee, Kiwoo
    • International Journal of Precision Engineering and Manufacturing
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    • 제2권3호
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    • pp.69-78
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    • 2001
  • This paper presents a process and operation planning system and an NC code post-processor for effective machining of press dies for production of cars. Based on the machining feature, major parts of press dies are categorized into 15 groups and a standard process plan is defined for each group. The standard process plan consists of a series of processes where a process is defined as a group of operations that can be done with one setup. Details such as cutting tools, cutting conditions, and tool paths are decided at the operation planning stage. At the final stage of process and operation planning, the NC code post-processor adjusts feedrates along the tool path to reduce machining time while maintaining the quality. The adjustment rule is selected based on the machining load estimated by virtual machining.

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Genetic Algorithm-Based Approaches for Enhancing Multi-UAV Route Planning

  • Mohammed Abdulhakim Al-Absi;Hoon Jae Lee;Young-sil Lee
    • International journal of advanced smart convergence
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    • 제12권4호
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    • pp.8-19
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    • 2023
  • This paper presents advancement in multi- unmanned aerial vehicle (UAV) cooperative area surveillance, focusing on optimizing UAV route planning through the application of genetic algorithms. Addressing the complexities of comprehensive coverage, two real-time dynamic path planning methods are introduced, leveraging genetic algorithms to enhance surveillance efficiency while accounting for flight constraints. These methodologies adapt multi-UAV routes by encoding turning angles and employing coverage-driven fitness functions, facilitating real-time monitoring optimization. The paper introduces a novel path planning model for scenarios where UAVs navigate collaboratively without predetermined destinations during regional surveillance. Empirical evaluations confirm the effectiveness of the proposed methods, showcasing improved coverage and heightened efficiency in multi-UAV path planning. Furthermore, we introduce innovative optimization strategies, (Foresightedness and Multi-step) offering distinct trade-offs between solution quality and computational time. This research contributes innovative solutions to the intricate challenges of cooperative area surveillance, showcasing the transformative potential of genetic algorithms in multi-UAV technology. By enabling smarter route planning, these methods underscore the feasibility of more efficient, adaptable, and intelligent cooperative surveillance missions.

A path planning of free flying object and its application to the control of gymnastic robot

  • Nam, Taek-Kun;So, Myung-Ok
    • Journal of Advanced Marine Engineering and Technology
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    • 제27권4호
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    • pp.526-534
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    • 2003
  • Motions of animals and gymnasts in the air as well as free flying space robots without thruster are subject to nonholonomic constraints generated by the law of conservation of angular momentum. The interest in nonholonomic control problems is motivated by the fact that such systems can not stabilized to its equilibrium points by the smooth control input. The purpose of this paper is to derive analytical posture control laws for free flying objects in the air. We propose a control method using bang-bang control for trajectory planning of a 3 link mechanical system with initial angular momentum. We reduce the DOF (degrees of freedom) of control object in the first control phase and determine the control inputs to steer the reduced order system from its initial position to its desired position. Computer simulation for a motion planning of an athlete approximated by 3 link is presented to illustrate the effectiveness of the Proposed control scheme.

Ground Vehicle and Drone Collaborative Delivery Planning using Genetic Algorithm

  • Song, Kyowon;Moon, Jung-Ho
    • 항공우주시스템공학회지
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    • 제14권6호
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    • pp.1-9
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    • 2020
  • Global e-commerce and delivery companies are actively pursuing last-mile delivery service using drones, and various delivery schedule planning studies have been conducted. In this study, separate individual route networks were constructed to reflect drone route constraints such as prohibited airspace and truck route constraints such as rivers, which previous studies did not incorporate. The A* algorithm was used to calculate the shortest path distance matrix between the starting point and destinations. In addition, we proposed an optimal delivery schedule plan using genetic algorithms and applied it to compare the efficiency with that of vehicle-only delivery.

Mobile Robot navigation using an Multi-resolution Electrostatic Potential Filed

  • Kim, Cheol-Taek;Lee, Ju-Jang
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.690-693
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    • 2004
  • This paper proposes a multi-resolution electrostatic potential field (MREPF) based solution to the mobile robot path planning and collision avoidance problem in 2D dynamic environment. The MREPF is an environment method in calculation time and updating field map. The large scale resolution map is added to EPF and this resolution map interacts with the small scale resolution map to find an optimal solution in real time. This approach can be interpreted with Atlantis model. The simulation studies show the efficiency of the proposed algorithm.

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