Journal ArticleDOI
Research on Robot Motion Planning Based on RRT Algorithm with Nonholonomic Constraints
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TLDR
The improved algorithm provides a more superior compared with the basic RRT algorithm and Bg-RRT algorithm, and has shorter computational time and shorter path than the traditional R RT algorithm.Abstract:
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.read more
Citations
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Journal ArticleDOI
Grasping posture of humanoid manipulator based on target shape analysis and force closure
Ying Liu,Du Jiang,Bo Tao,Jinxian Qi,Guozhang Jiang,Juntong Yun,Li Huang,Xiliang Tong,Baojia Chen,Gongfa Li +9 more
TL;DR: In this paper, a method for determining the grasping posture of a manipulator based on shape analysis and force closure is proposed, where the irregular or complex objects are reduced to a combination of some basic shapes.
Journal ArticleDOI
Grasping posture of humanoid manipulator based on target shape analysis and force closure
TL;DR: In this article , a method for determining the grasping posture of a manipulator based on shape analysis and force closure is proposed, where the irregular or complex objects are reduced to a combination of some basic shapes.
Journal ArticleDOI
Complex Environment Path Planning for Unmanned Aerial Vehicles.
TL;DR: In this article, a branch-selected rapidly-exploring random tree (BS-RRT) algorithm is proposed to solve the global path planning problem in environments with narrow passages.
Journal ArticleDOI
Autonomous Vehicle Path Planning Based on Driver Characteristics Identification and Improved Artificial Potential Field
TL;DR: Based on the drivers' characteristics and artificial potential field (APF), an improved local path planning algorithm is proposed in this article , where a large amount of driver data are collected through tests and classified by the K-means algorithm.
Journal ArticleDOI
Local Path Planning of Autonomous Vehicle Based on an Improved Heuristic Bi-RRT Algorithm in Dynamic Obstacle Avoidance Environment
TL;DR: Simulation analysis clarifies the efficient performance and experiments on dynamic environments show that the improved heuristic Bi-RRT algorithm can generate a differentiable coherence path, ensuring the ride comfort and stability of the vehicle.
References
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Proceedings ArticleDOI
Randomized kinodynamic planning
TL;DR: A state-space perspective on the kinodynamic planning problem is presented, and a randomized path planning technique that computes collision-free kinodynamic trajectories for high degree-of-freedom problems is introduced.
Proceedings ArticleDOI
Approaches for heuristically biasing RRT growth
Chris Urmson,Reid Simmons +1 more
TL;DR: This paper presents several modifications to the basic rapidly-exploring random tree (RRT) search algorithm to utilize a heuristic quality function to guide the search.
Proceedings ArticleDOI
Learning Sampling Distributions for Robot Motion Planning
TL;DR: This paper proposes a methodology for nonuniform sampling, whereby a sampling distribution is learned from demonstrations, and then used to bias sampling, resulting in an order of magnitude improvement in terms of success rate and convergence to the optimal cost.
Proceedings ArticleDOI
3D smooth path planning for a UAV in cluttered natural environments
Kwangjin Yang,Salah Sukkarieh +1 more
TL;DR: This paper presents a 3D path planing algorithm for an unmanned aerial vehicle (UAV) operating in cluttered natural environments that satisfies the upper bounded curvature constraint and the continuous curvature requirement.
Proceedings ArticleDOI
Motion Planning Networks
TL;DR: This work presents Motion Planning Networks (MPNet), a neural network-based novel planning algorithm that encodes the given workspaces directly from a point cloud measurement and generates the end-to-end collision-free paths for the given start and goal configurations.
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