scholarly journals A Method of Enhancing Rapidly-Exploring Random Tree Robot Path Planning Using Midpoint Interpolation

2021 ◽  
Vol 11 (18) ◽  
pp. 8483
Author(s):  
Jin-Gu Kang ◽  
Yong-Sik Choi ◽  
Jin-Woo Jung
Keyword(s):  
Path Planning ◽  
Path Length ◽  
Interpolation Method ◽  
Optimal Path ◽  
Random Tree ◽  
Interpolation Process ◽  
Robot Path Planning ◽  
Planning Time ◽  
Robot Path

It is difficult to guarantee optimality using the sampling-based rapidly-exploring random tree (RRT) method. To solve the problem, this paper proposes the post triangular processing of the midpoint interpolation method to minimize the planning time and shorten the path length of the sampling-based algorithm. The proposed method makes a path that is closer to the optimal path and somewhat solves the sharp path problem through the interpolation process. Experiments were conducted to verify the performance of the proposed method. Applying the method proposed in this paper to the RRT algorithm increases the efficiency of optimization by minimizing the planning time.

scholarly journals An Enhancement Method of Rapidly-exploring Random Tree Robot Path Planning using Midpoint Interpolation

2021 ◽  
Author(s):  
Jin-Gu Kang ◽  
Yong-Sik Choi ◽  
Jin-Woo Jung
Keyword(s):  
Path Planning ◽  
Path Length ◽  
Interpolation Method ◽  
Optimal Path ◽  
Random Tree ◽  
Interpolation Process ◽  
Robot Path Planning ◽  
Planning Time ◽  
Enhancement Method ◽  
Robot Path

To solve the problem that sampling-based Rapidly-exploring Random Tree (RRT) method is difficult to guarantee optimality. This paper proposed the Post Triangular Processing of Midpoint Interpolation method minimized the planning time and shorter path length of the sampling-based algorithm. The proposed Post Triangular Processing of Midpoint Interpolation method makes a closer to the optimal path and somewhat solves the sharp path problem through the interpolation process. The experiments were conducted to verify the performance of the proposed method. Applying the method proposed in this paper to the RRT algorithm increases the efficiency of optimization compared to the planning time.

scholarly journals Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 333
Author(s):  
Jin-Gu Kang ◽  
Dong-Woo Lim ◽  
Yong-Sik Choi ◽  
Woo-Jin Jang ◽  
Jin-Woo Jung
Keyword(s):  
Path Planning ◽  
Path Length ◽  
Experimental Results ◽  
Random Tree ◽  
Robot Path Planning ◽  
Planning Time ◽  
Triangular Inequality ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Robot Path

This paper proposed a triangular inequality-based rewiring method for the rapidly exploring random tree (RRT)-Connect robot path-planning algorithm that guarantees the planning time compared to the RRT algorithm, to bring it closer to the optimum. To check the proposed algorithm’s performance, this paper compared the RRT and RRT-Connect algorithms in various environments through simulation. From these experimental results, the proposed algorithm shows both quicker planning time and shorter path length than the RRT algorithm and shorter path length than the RRT-Connect algorithm with a similar number of samples and planning time.

scholarly journals Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning

2020 ◽  
Author(s):  
Jin-Gu Kang ◽  
Dong-Woo Lim ◽  
Yong-Sik Choi ◽  
Woo-Jin Jang ◽  
Jin-Woo Jung
Keyword(s):  
Path Planning ◽  
Path Length ◽  
Experimental Results ◽  
Random Tree ◽  
Robot Path Planning ◽  
Planning Time ◽  
Triangular Inequality ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Robot Path

This paper proposed a triangular inequality-based rewiring method for the Rapidly exploring Random Tree (RRT)-Connect robot path-planning algorithm that guarantees the planning time compared to the RRT algorithm, to bring it closer to the optimum. To check the proposed algorithm’s performance, this paper compared the RRT and RRT-Connect algorithms in various environments through simulation. From these experimental results, the proposed algorithm shows both quicker planning time and shorter path length than the RRT algorithm and shorter path length than the RRT-Connect algorithm with a similar number of samples and planning time.

scholarly journals Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning

2020 ◽  
Author(s):  
Jin-Gu Kang ◽  
Dong-Woo Lim ◽  
Yong-Sik Choi ◽  
Woo-Jin Jang ◽  
Jin-Woo Jung
Keyword(s):  
Path Planning ◽  
Path Length ◽  
Experimental Results ◽  
Random Tree ◽  
Robot Path Planning ◽  
Planning Time ◽  
Triangular Inequality ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Robot Path

This paper proposed a triangular inequality-based rewiring method for the Rapidly exploring Random Tree (RRT)-Connect robot path-planning algorithm that guarantees the planning time compared to the RRT algorithm, to bring it closer to the optimum. To check the proposed algorithm’s performance, this paper compared the RRT and RRT-Connect algorithms in various environments through simulation. From these experimental results, the proposed algorithm shows both quicker planning time and shorter path length than the RRT algorithm and shorter path length than the RRT-Connect algorithm with a similar number of samples and planning time.

New Approach for Mobile Robot Path Planning

2013 ◽  
Vol 467 ◽  
pp. 475-478
Author(s):  
Feng Yun Lin
Keyword(s):  
Path Planning ◽  
Optimal Path ◽  
Dc Motor ◽  
Robot Path Planning ◽  
New Approach ◽  
Kinematic Constraints ◽  
Optimal Path Planning ◽  
Kinematic Limit ◽  
Time Optimal ◽  
Robot Path

This paper presents a method of time optimal path planning under kinematic, limit heat characteristics of DC motor and dynamic constrain for a 2-DOF wheeled. Firstly the shortest path is planned by using the geometric method under kinematic constraints. Then, in order to make full use of motors capacity we have the torque limits under limit heat characteristics of DC motor, finally the velocity limit and the boundary acceleration (deceleration) are determined to generate a time optimal path.

scholarly journals Mobile Robot Path Planning Based on a Generalized Wavefront Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Sifan Wu ◽  
Yu Du ◽  
Yonghua Zhang
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Path Length ◽  
Computation Time ◽  
Target Point ◽  
Multiple Target ◽  
Robot Path Planning ◽  
Practical Applications ◽  
Real Time Applications ◽  
Robot Path

This study develops a generalized wavefront algorithm for conducting mobile robot path planning. The algorithm combines multiple target point sets, multilevel grid costs, logarithmic expansion around obstacles, and subsequent path optimization. The planning performances obtained with the proposed algorithm, the A∗ algorithm, and the rapidly exploring random tree (RRT) algorithm optimized using a Bézier curve are compared using simulations with different grid map environments comprising different numbers of obstacles with varying shapes. The results demonstrate that the generalized wavefront algorithm generates smooth and safe paths around obstacles that meet the required kinematic conditions associated with the actual maneuverability of mobile robots and significantly reduces the planned path length compared with the results obtained with the A∗ algorithm and the optimized RRT algorithm with a computation time acceptable for real-time applications. Therefore, the generated path is not only smooth and effective but also conforms to actual robot maneuverability in practical applications.

The Study on Mobile Robot Path Planning Based on Frog Leaping Algorithm

2012 ◽  
Vol 490-495 ◽  
pp. 808-812
Author(s):  
Zheng Ran Zhang ◽  
Ji Ying Yin
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Optimization Problem ◽  
Optimal Path ◽  
Robot Path Planning ◽  
Unknown Environment ◽  
Simulation Results ◽  
Robot Path

We have proposed a method of robot path planning in a partially unknown environment in this paper. We regard the problem of robot path planning as an optimization problem and solve it with the SFL algorithm. The position of globally best frog in each iterative is selected, and reached by the robot in sequence. The obstacles are detected by the robot sensors are applied to update the information of the environment. The optimal path is generated until the robot reaches its target. The simulation results validate the feasibility of the proposed method.

Path Planning Based on Heuristic Rapidly-Exploring Random Tree for Nonholonomic Mobile Robot

2014 ◽  
Vol 494-495 ◽  
pp. 1161-1164
Author(s):  
Liang Kang ◽  
Lian Cheng Mao
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Random Tree ◽  
Robot Path Planning ◽  
Heuristic Function ◽  
Kinematic Constraints ◽  
Nonholonomic Mobile Robot ◽  
Calculation Results ◽  
Trajectory Tracking Controller ◽  
Robot Path

The RRT algorithm and the heuristic function are combined in the mobile robot path planning, so a novel path planning is proposed. Based on the dynamic model and kinematic constraints of the nonholonomic mobile robot, a trajectory tracking controller is designed. Theory and calculation results prove that, as a new method for mobile robot path planning, the heuristic Rapidly-Exploring Random Tree for nonholonomic mobile robot path planning is feasible and effective.

Multi-Robot Fish Path Planning Based on the Modified A* Algorithm

2014 ◽  
Vol 568-570 ◽  
pp. 1054-1058 ◽  
Author(s):  
Qiang Hong ◽  
Mei Xiao Chen ◽  
Yan Song Deng
Keyword(s):  
Path Planning ◽  
Optimal Path ◽  
Experimental Results ◽  
Robot Path Planning ◽  
A Algorithm ◽  
Optimal Path Planning ◽  
2D Simulation ◽  
Robot Fish ◽  
Robot Path ◽  
Multi Robot

Based on improved A* algorithm, this paper proposes the optimal path planning of robot fish in globally known environment, so as to achieve better coordination between the robot fish by means of improving their path planning. In the known obstacle environment which is rasterized, target nodes are generated via smoothing A* algorithm. The unnecessary connection points are removed then and the path is smoothed at the turning points. That improved algorithm, in combination with distributed scroll algorithms, is applied to multi-robot path planning in an effort to optimize the path with the avoidance of collision. The experimental results on the 2D simulation platform have verified the feasibility of that method.

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