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Sampling-based finger gaits planning for multifingered robotic hand

AUTONOMOUS ROBOTS 2010年第4期28卷 385-402页

作者： Xu, Jijie Koo, Tak-Kuen John Li, Zexiang Rochester Inst Technol B Thomas Golisano Coll Comp & Informat Sci Rochester NY 14623 USA Chinese Acad Sci Shenzhen Inst Adv Technol Ctr Embedded Software Syst Shenzhen Peoples R China Hong Kong Univ Sci & Technol Dept Elect & Comp Engn Hong Kong Hong Kong Peoples R China

To perform large scale or complicated manipulation tasks, a multi-fingered robotic hand sometimes has to sequentially adjust its grasp status to overcome constraints of the manipulation, such as workspace limits, force balance requirement, etc. Such a strategy of changing grasping status is called a finger gait, which exhibits strong hybrid characteristics due to the discontinuity caused by relocating limited fingers and the continuity caused by manipulating objects. This paper aims to explore the complicated finger gaits planning problem and provide a method for robotic hands to autonomously generate feasible finger gaits to accomplish given tasks. Based on the hybrid automaton formulation of a popular finger gaiting primitive, finger substitution, we formulate the finger gait planning problem into a classic motion planning problem with a hybrid configuration space. Inspired by the rapidly-exploring random tree (RRT) techniques, we develop a finger gait planner to quickly search for a feasible manipulation strategy with finger substitution primitives. To increase the search performance of the planner, we further develop a refined sampling strategy, a novel hybrid distance and an efficient exploring strategy with the consideration of the problem's hybrid nature. Finally, we use a representative numerical example to verify the validity of our problem formulation and the performance of the RRT based finger gait planner.

关键词： Dextrous manipulation Finger gaits Manipulation planning Hybrid automaton rapidly-exploring random tree

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Euler-Lagrange as Pseudo-metric of the RRT algorithm for optimal-time trajectory of flight simulation model in high-density obstacle environment

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ROBOTICA 2017年第5期35卷 1138-1156页

作者： Altaher, Mohammad Nomir, Andomaima Univ Mansoura CS Dept Mansoura Egypt

This paper introduces a solution to the problem of steering an aerodynamical system, with non-holonomic constraints superimposed on dynamic equations of motion. The proposed approach is a dimensionality reduction of the Optimal Control Problem (OCP) with heavy path constraints to be solved by rapidly-exploring random tree (RRT) algorithm. In this research, we formulated and solved the OCP with Euler-Lagrange formula in order to find the optimal-time trajectory. The RRT constructs a non-collision path in static, high-dense obstacle environment (i.e. heavy path constraint). Based on a real-world aircraft model, our simulation results found the collision-free path and gave improvements of time and fuel consumption of the optimized Hamiltonian-based model over the original non-optimized model.

关键词： Optimal trajectory generation rapidly-exploring random tree Euler-Lagrange equation

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Online planning for relative optimal and safe paths for USVs using a dual sampling domain reduction-based RRT* method

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INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS 2020年第12期11卷 2665-2687页

作者： Wen, Naifeng Zhang, Rubo Wu, Junwei Liu, Guanqun Dalian Minzu Univ Sch Electromech Engn Dalian Peoples R China

A heuristic Dual sampling domain Reduction-based Optimal rapidly-exploring random tree scheme is proposed by guiding the planning procedure of the optimal rapidly-exploring random tree (RRT*) method through learning environmental knowledge. The scheme aims to plan low fuel expenditure, easy-execution, and low collision probability paths online for an unmanned surface vehicle (USV) under constraints. First, an elliptic sampling domain, which is subject to an elliptic equation and the shortest obstacle avoidance path estimation, is created to plan short paths. Second, by the consideration of the USV motion states, obstacles and external interferences of the current, the near sampling domains of tree nodes are reduced to exclude high-cost sampling domains. Path feasibility is ensured by explicitly handling motion constraints. Third, a safe distance-based collision detection (CD) scheme and a velocity-based bounding box of USV are proposed to decrease the path collision probability. Additionally, a layered USV online path planning framework is built in accordance with the model predictive control method, and the path smoothing scheme is applied via the Dubins curve under the curvature constraint. Results demonstrate that the proposed dual sampling domain reduction method outperforms traditional reduction schemes in terms of improving the execution efficiency of RRT*. Meanwhile, the proposed CD method is more reliable than the conventional one.

关键词： Unmanned surface vehicle Online path planning Obstacle avoidance Sampling space reduction rapidly-exploring random tree Collision detection

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Research on Robot Motion Planning Based on RRT Algorithm with Nonholonomic Constraints

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NEURAL PROCESSING LETTERS 2021年第4期53卷 3011-3029页

作者： Gan, Yi Zhang, Bin Ke, Chao Zhu, Xiaofeng He, Weiming Ihara, Tohru Univ Shanghai Sci & Technol Coll Mech Engn Shanghai Peoples R China Chuo Univ Fac Sci & Engn Dept Precis Mech Tokyo Japan Shanghai Univ Engn Sci Adv Vocat Tech Coll Shanghai Peoples R China

A 1-0 Bg-RRT algorithm is proposed to reduce computational time and complexity, even in complex environments. Different from rapidly-exploring random tree (RRT) and Bias-goal rapidly-exploring random tree (Bg-RRT), using 1-0 Bg-RRT with 1 and 0 change probability biased to the target to construct the tree is faster and can jump out of the local minimum in time. Although unknown space path planning problem based on RRT is difficult to obtain satisfactory performance, but the improved algorithm provides a more superior compared with the basic RRT algorithm and Bg-RRT algorithm. The simulation results show that the 1-0 Bg-RRT algorithm has shorter computational time and shorter path than the traditional RRT algorithm.

关键词： rapidly-exploring random tree Path planning Nonholonomic constraint Goal bias Robot motion

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FAST RRT* 3D-Sliced Planner for Autonomous Exploration Using MAVs

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UNMANNED SYSTEMS 2022年第2期10卷 175-186页

作者： Martinez Novo, A. Lu, Liang Campoy, Pascual Univ Politecn Madrid UPM CSIC Ctr Automat & Robot CAR Comp Vis & Aerial Robot CVAR Grp Calle Jose Gutierrez Abascal 2 Madrid 28006 Spain

This paper addresses the challenge to build an autonomous exploration system using Micro-Aerial Vehicles (MAVs). MAVs are capable of flying autonomously, generating collision-free paths to navigate in unknown areas and also reconstructing the environment at which they are deployed. One of the contributions of our system is the "3D-Sliced Planner" for exploration. The main innovation is the low computational resources needed. This is because Optimal-Frontier-Points (OFP) to explore are computed in 2D slices of the 3D environment using a global rapidly-exploring random tree (RRT) frontier detector. Then, the MAV can plan path routes to these points to explore the surroundings with our new proposed local "FAST RRT* Planner" that uses a tree reconnection algorithm based on cost, and a collision checking algorithm based on Signed Distance Field (SDF). The results show the proposed explorer takes 43.95% less time to compute exploration points and paths when compared with the State-of-the-Art represented by the Receding Horizon Next Best View Planner (RH-NBVP) in Gazebo simulations.

关键词： Autonomous exploration Signed Distance Field rapidly-exploring random tree Fast RRT

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Improved Informed RRT* Using Gridmap Skeletonization for Mobile Robot Path Planning

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INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING 2019年第11期20卷 2033-2039页

作者： Ryu, Hyejeong Park, Younghoon Kangwon Natl Univ Dept Mechatron Engn Chunchon 24341 South Korea

An improved Informed RRT* algorithm was proposed to reduce computational time, even in complex environments. Unlike RRT* used for Informed RRT* to find an initial solution for the whole configuration space, the gridmap skeletonization approach is applied to generate the initial solution. Because the skeletonization process can be performed faster and more robustly than a process where the tree is constructed by random sampling of RRT*, the initial solution is obtained efficiently and is optimized earlier compared with conventional Informed RRT* algorithms. The simulation results of the proposed improved Informed RRT* algorithm show that the computational time is shorter, with a smaller standard deviation than that of the conventional Informed RRT*.

关键词： rapidly-exploring random tree Path planning Mobile robots

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Path Planning and Optimization of Humanoid Manipulator in Cartesian Space

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Journal of Shanghai Jiaotong university(Science) 2022年第5期27卷 614-620页

作者： LI Shiqi LI Xiao KE Han XIONG Youjun XIE Zheng CHEN Jinliang School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan430074China Ubtech Robotics Co. Ltd.Shenzhen518000GuangdongChina

To solve the problems of low efficiency and multi-solvability of humanoid manipulator Cartesian space path planning in physical human-robot interaction,an improved bi-directional rapidly-exploring random tree algorithm based on greedy growth strategy in 3D space is *** workspace of manipulator established based on Monte Carlo method is used as the sampling space of the rapidly-exploring random tree,and the opposite expanding greedy growth strategy is added in the random tree expansion process to improve the path planning *** the generated path is reversely optimized to shorten the length of the planned path,and the optimized path is interpolated and pose searched in Cartesian space to form a collision-free optimized path suitable for humanoid manipulator ***,the validity and reliability of the algorithm are verified in an intelligent elderly care service scenario based on Walker2,a large humanoid service robot.

关键词： humanoid manipulator path planning rapidly-exploring random tree greedy growth reverse optimization pose search

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Interactive Locomotion Animation using Path Planning

Interactive Locomotion Animation using Path Planning

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16th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Flavigne, David Taix, Michel UPMC Univ Paris 06 ISIR UMR 7222 F-75005 Paris France CNRS LAAS F-31077 Toulouse France Univ Toulouse LAAS UPS INSA INP ISAE F-31077 Toulouse France

ISBN: (纸本)9781457700187

This paper presents a method aimed at enhancing interaction between a path planning algorithm and a user to guide a robot motion task in a virtual environment. Existing works use a two-step decomposition which limits the interaction between the user and the ongoing process. We propose a modification of a classic motion planning method, the rapidly-exploring random tree to build a Interactive-RRT. This method is based on exchanging forces between the algorithm and the user, and on data gathering (labels) from the virtual scene. The Interactive-RRT is combined with a locomotion controller and then applied to a virtual character for generating a locomotion movement along a path suggested by the user.

关键词： Animation Force Haptic interfaces Mice Planning Trajectory data gathering interactive locomotion animation interactive-RRT locomotion controller motion control motion planning path planning path planning rapidly-exploring random tree robot motion task rob

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An Improved RRT Algorithm for Rendezvous Problem in Complex Environment

An Improved RRT Algorithm for Rendezvous Problem in Complex ...

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IEEE CSAA Guidance, Navigation and Control Conference (CGNCC)

作者： Wang, Siqiang Yao, Yu He, Fenghua Zhang, Xinran Harbin Inst Technol Harbin 150001 Peoples R China

ISBN: (纸本)9781538611715

In this paper, a rendezvous problem in complex environment is investigated where a quadrotor is required to rendezvous with a moving target while avoiding a moving obstacle. A lime-based RRT algorithm is proposed to generate a collision free route from quadrotor's current position to the rendezvous point, and a feed-forward based RID controller is designed to track the route. Simulation results show the effectiveness of the proposed algorithm and its superiority compared to the original RRT algorithm.

关键词： Rendezvous rapidly-exploring random tree Time-based

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An Efficient Obstacle Avoidance Approach For USV Considering The Heading Angle Constraint 36

An Efficient Obstacle Avoidance Approach For USV Considering...

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36th Chinese Control and Decision Conference (CCDC)

作者： Shu, Hao Huang, Haibin Chen, Zhi Zhuang, Yufei Bi, Dongkui Harbin Inst Technol Sch Informat Sci & Engn Weihai Peoples R China Harbin Inst Technol Weihai Key Lab Autonomous Control & Collaborat Te Key Lab Cross Domain Collaborat & Comprehens Supp Minist Ind & Informat TechnolSch Informat Sci & Weihai 264209 Peoples R China China Classificat Soc Weihai Survey Stn Weihai Peoples R China

ISBN: (纸本)9798350387780;9798350387797

The application of Unmanned Surface Vessel (USV) is gaining a lot of attraction in military, commercial, and scientific researches. However, due to various potential obstacles in the actual ocean, USV must be able to detect these obstacles in real-time, and take measures to avoid them safely. In this paper, we propose a novel method: Gradient and Node Optimal rapidly-exploring random trees (GO-RRT) algorithm, which leverages the principles of APF (Artificial Potential Field) algorithm and RRT( rapidly-exploring random tree) algorithm, incorporating gradient vectors within the framework of RRT algorithm while optimizing node placements. This work includes: (i) thoroughly considering the constraints in USV path planning based on the advantages of RRT;(ii) adopting an improved RRT based on APF potential function, significantly improving the efficiency of path search, and optimizing the generated path to make the actual distance of the path shorter;(iii) a dynamic obstacle detection algorithm that enables USV to prevent the initiation of obstacle avoidance algorithms in unobstructed sea conditions, thereby saving computational resources. In this work, GO-RRT can improve the quality of generated paths, and effectively reduce the consumption of computational resources. Our algorithm obtains superior performance, and achieves efficient results in simulation experiments.

关键词： obstacle detection unmanned surface vessel rapidly-exploring random tree artificial potential field node optimization heading angle

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