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检索条件"主题词=Rapidly-exploring Random Tree"

共 102 条记录，以下是61-70 订阅

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A local trajectory planning and control method for autonomous vehicles based on the RRT algorithm

A local trajectory planning and control method for autonomou...

引用

AEIT International Conference of Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE)

作者： Feraco, Stefano Luciani, Sara Bonfitto, Angelo Amati, Nicola Tonoli, Andrea Politecn Torino Dept OfMech & Aerosp Engn Turin Italy

ISBN: (纸本)9788887237498

This paper presents a local trajectory planning and control method based on the rapidly-exploring random tree algorithm for autonomous racing vehicles. The paper aims to provide an algorithm allowing to compute the planned trajectory in an unknown environment, structured with non-crossable obstacles, such as traffic cones. The investigated method exploits a perception pipeline to sense the surrounding environment by means of a LIDAR-based sensor and a high-performance Graphic Processing Unit. The considered vehicle is a four-wheel drive electric racing prototype, which is modeled as a 3 Degree-of-Freedom bicycle model. A Stanley controller for both lateral and longitudinal vehicle dynamics is designed to perform the path tracking task. The performance of the proposed method is evaluated in simulation using real data recorded by on-board perception sensors. The algorithm can successfully compute a feasible trajectory in different driving scenarios.

关键词： Trajectory planning Autonomous driving rapidly-exploring random tree Vehicle control Environment perception Local planning

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Optimal Spline-based RRT Path Planning Using Probabilistic Map 14

Optimal Spline-based RRT Path Planning Using Probabilistic M...

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14th International Conference on Control, Automation and Systems (ICCAS)

作者： Yang, Kwangjin Gan, Seng Keat Huh, Jinwook Joo, Sanghyun Korea Air Force Acad Dept Mech Engn Chungbuk 363849 South Korea Univ Sydney Australian Ctr Field Robot Sydney NSW 2006 Australia Agcy Def Dev Daejeon 305600 South Korea

ISBN: (纸本)9788993215069

This paper presents an optimal path planning algorithm that adopts the rapidly-exploring random tree(RRT) as a path planner. The RRT generates a valid path quickly, but it does not have the ability to control the quality of the path. In this paper, the nonholonomic path planning and the optimal path planning are tackled simultaneously within the RRT framework. The spline-based RRT algorithm generates a feasible path satisfying the differential constraints, and the RRT* strategy is incorporated to guarantee the optimal solution. In addition, the probabilistic map combining 3D Lidar and visual camera is used as a map for the path planning. Simulation results show that the proposed spline-based RRT* outputs a dynamically feasible optimal path.

关键词： rapidly-exploring random tree Optimal Path Differential Constraints Probabilistic Map

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randomized Path Planning on Foliated Configuration Spaces 11

Randomized Path Planning on Foliated Configuration Spaces

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11th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

作者： Kim, Jinkyu Ko, Inyoung Park, Frank C. Seoul Natl Univ Dept Mech & Aerosp Engn Seoul 151742 South Korea

ISBN: (纸本)9781479953332

This paper presents a randomized planning algorithm for manipulation tasks that require the robot to release an object in different robot configurations. Such problems arise, for example, in robotic suturing and knot tying, and in certain assembly tasks where parts must be guided through cluttered environments. We show that the problem can be posed as one of planning on a foliated manifold. A randomized algorithm that involves sampling and tree propagation in both the robot's task and joint configuration space manifolds is developed. A key component of the algorithm is a path refining phase, in which the topological structure of the foliated manifold is first learned via a sampling and clustering procedure using Gaussian mixtures, and the number of release-regrasp sequences reduced. Comparative case studies evaluating the performance of our algorithm are presented.

关键词： path planning sampling-based planning foliation rapidly-exploring random tree

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A Path Planning Method for Autonomous Flying Vehicles Using an Improved RRT* Algorithm

A Path Planning Method for Autonomous Flying Vehicles Using ...

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International Conference on Autonomous Unmanned Systems (ICAUS)

作者： Qie, Tianqi Wang, Weida Yang, Chao Li, Ying Liu, Wenjie Beijing Inst Technol Beijing 100081 Peoples R China

ISBN: (纸本)9789819904815;9789819904792;9789819904785

Autonomous flying vehicles are promising transportation of the future, which have the function of ground vehicles and low-altitude aircraft. To plan a feasible path effectively, an improved optimal rapidly-exploring random tree (RRT*) method is proposed. Firstly, a cost function considering driving efficiency and the energy consumption is established. Then, the cost of a known feasible path, which flies from the start point to the goal point directly, is calculated as a benchmark. According to the benchmark, the planning area is reduced to an elliptical area. The proposed method is verified by simulations with an actual cross-country environment. Results show that the computation time decreased by 11.3% compared with the basic RRT* method.

关键词： Autonomous flying vehicles Path planning rapidly-exploring random tree

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Seven-Degrees-of-Freedom Robotic Arm Path Planning Based on Improved RRT 20th

Seven-Degrees-of-Freedom Robotic Arm Path Planning Based on ...

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20th Chinese Intelligent Systems Conference

作者： Li, Xin Wang, Yuhang Yu, Liming Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China

ISBN: (纸本)9789819786565;9789819786541;9789819786534

With the development of automation technology, seven degrees of freedom robotic arms are widely used in industry, but the complex kinematic characteristics make path planning a challenge. In this paper, an improved RRT algorithm is proposed for seven-degrees-of-freedom robotic arm path planning to solve the high-dimensional complex constraint problem. Although the traditional RRT algorithm is efficient and adaptable, it suffers from non-optimal paths, redundancy and litter problems. For this reason, this paper introduces a goal strategy and heuristic term to reduce redundant nodes and improve the convergence speed by guiding the tree expansion with goal bias and stochastic probability. Meanwhile, collision detection and fifth-degree polynomial interpolation are used to ensure path safety and motion smoothing.

关键词： robotic arms rapidly-exploring random tree route planning

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Adaptively Dynamic RRT*-Connect: Path Planning for UAVs Against Dynamic Obstacles 7

Adaptively Dynamic RRT*-Connect: Path Planning for UAVs Agai...

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7th International Conference on Automation, Control and Robotics Engineering (CACRE)

作者： Chen, Yicheng Wang, Lingling Beihang Univ Sch Automat Sci & Elect Engn Beijing Peoples R China

ISBN: (数字)9781665403870

ISBN: (纸本)9781665403870

Path planning for Unmanned Aerial Vehicles (UAVs), especially in three-dimensional environments with dynamic obstacles, is an active area of research. In recent years, RRT-based algorithms have been attracting significant interest, and various improvements are introduced to RRT to make it applicable in such scenarios. Some methods leverage re-planning mechanisms to avoid collision with the dynamic threats, however, most of them fail to fully reuse historical information, hence having limitations in saving the planning costs. This paper presents Adaptively Dynamic RRT*-Connect (ADRRT*-Connect), a novel RRT-based path planning algorithm that enables UAVs to fly safely in three-dimensional environments with dynamic threats. To improve efficiency in sampling new nodes, we propose a strategy to automatically adjust the heuristic factor based on feedback from the sampling results. For avoiding collision with dynamic threats, we introduce a pruning-reconnecting mechanism to repair the path when new obstacles emerge. Our approach is economical in the consumption of tree nodes. In comparison to existing benchmarks, simulations have shown that our proposed algorithm only requires 3.5% new nodes to repair the path in re-planning.

关键词： Unmanned Aerial Vehicle Path Planning rapidly-exploring random tree Dynamic Environment

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Generation of RNP Approach Flight Procedures with an RRT* Path-Planning Algorithm 42

Generation of RNP Approach Flight Procedures with an RRT* Pa...

引用

IEEE/AIAA 42nd Digital Avionics Systems Conference (DASC)

作者： Saez, Raul Toratani, Daichi Mori, Ryota Prats, Xavier Elect Nav Res Inst ENRI Air Traff Management Dept Chofu Tokyo Japan Kobe Univ Grad Sch Maritime Sci Kobe Hyogo Japan Tech Univ Catalonia UPC Dept Phys Aerosp Div Barcelona Spain

ISBN: (纸本)9798350333572

We present a framework capable of generating required navigation performance authorization required approach (RNP AR APCH) procedures by using a combination of the optimal version of the path-planning rapidly-exploring random tree (RRT*) algorithm and Dubins paths. Procedures are generated by taking into account design constraints defined by the international civil aviation organization (ICAO) procedures for air navigation services - aircraft operations (PANS-OPS). The framework is used to compute several approach procedures for two airports in Japan, Kumamoto and Kitakyushu airports. Several feasible procedures are successfully obtained in a low amount of computational time, many of them resembling the actual procedures published in the selected airports. The output of our framework represents a valuable input for procedure designers, who could later refine the obtained results with specific flight-procedure-design software.

关键词： Path Planning Required Navigation Performance Performance Based Navigation Route Design rapidly-exploring random tree

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Dynamic Motion Planning Algorithm in Human-Robot Collision Avoidance 12th

Dynamic Motion Planning Algorithm in Human-Robot Collision A...

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12th International Conference on Intelligent Robotics and Applications (ICIRA)

作者： Zhu, Lei Chi, Zijing Zhou, Fan Zhuang, Chungang Shanghai Jiao Tong Univ Sch Mech Engn State Key Lab Mech Syst & Vibrat Shanghai 200240 Peoples R China

ISBN: (纸本)9783030275297;9783030275280

The collision-free robotic motion planning algorithm in a dynamic environment is an effective method for the prevention of collision in a human-robot interaction scenario. In this paper, an improvement of the rapidly-exploring random tree (RRT) algorithm is proposed to avoid the potential collision between robot and human by taking the costmap of robot workspace into consideration. The depth camera and Kalman filter are applied to estimate the positions and velocities of dynamic obstacles. The main contribution of this paper is that the spatiotemporal information of moving obstacles is integrated into the robotic motion planning algorithm with the costmap of workspace. Besides, a new costmap generation method is designed based on the velocities of moving obstacles. Finally, a local replanning method is used to accelerate the robotic motion planning algorithm. Experimental results show that the proposed method can efficiently protect human workers from colliding with the robot and the robot can dynamically generate a collision-free path in the human-robot coexisting environment.

关键词： Motion planning rapidly-exploring random tree Dynamic environment Human-Robot Interaction

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Route Planning for Unmanned Aerial Vehicle Based on Rolling RRT in Unknown Environment

Route Planning for Unmanned Aerial Vehicle Based on Rolling ...

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7th IEEE International Conference on Computational Intelligence and Computing Research (ICCIC)

作者： Li Meng Song Qing Zhao Qinjun Zhang Yongliang Univ Jinan Sch Elect Engn Jinan Peoples R China Shandong Inst Metrol Jinan Peoples R China

ISBN: (纸本)9781509006120

For the problem of unmanned aerial vehicle route planning in unknown environment, a rolling rapidly-exploring random tree algorithm is proposed. According to the current environment information, the local route planning is carried out in the rolling window. Unmanned aerial vehicle flight in accordance with the planning results. At the same time, the new environment information is detected and the next stage of the route is generated. This process is repeated, until the unmanned aerial vehicle reaches the target position. The implementation method of the rolling rapidly-exploring random tree algorithm is discussed in detail, including the rolling window design, the local target setting, random node selection, route pruning and smoothing and so on. A new random node selection strategy is proposed, which can guide the rapidly-exploring random tree grows rapidly to the boundary of the rolling window. Finally, the simulation results show that the proposed method can meet the demand of online route planning in unknown environment.

关键词： Route planning rapidly-exploring random tree Unmanned Aerial Vehicle Rolling optimization

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Research on Multi-UUV Path Planning Method Based on Recycling Task

Research on Multi-UUV Path Planning Method Based on Recyclin...

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OCEANS Hampton Roads Conference

作者： Zhang, Wei Zhang, Kaihang Li, Yu Han, Peiyu Harbin Engn Univ Coll Intelligent Sci & Engn Harbin Heilongjiang Peoples R China

ISBN: (数字)9781665468091

ISBN: (纸本)9781665468091

This paper addresses the path planning process with various uncertainties in the multi-UUV recycling. According to the amount of environmental information obtained, it can be divided into global planning for the entire recycling task and local planning for unknown threats. As a result, different from the traditional path planning method, the proposed method can be described as comprising two distinct phases: (1) combined with artificial potential field method, an improved algorithm based on "domain" is proposed, and the fish population trust domain algorithm is used to obtain the sub-target points that meet the requirements and complete the global track planning. (2) a bidirectional RRT* local path planning algorithm based on the concept of rolling optimization under incomplete constraints is proposed to deal with the unknown threats that appear during navigation. Finally, the effectiveness and feasibility of the algorithm are verified by simulation.

关键词： multi-unmanned underwater vehicle recycling task path planning improved artificial potential field method rapidly-exploring random tree

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