Potentially Guided Bidirectionalized RRT* for Fast Optimal Path Planning in Cluttered Environments

by   Zaid Tahir, et al.

Rapidly-exploring Random Tree star (RRT*) has recently gained immense popularity in the motion planning community as it provides a probabilistically complete and asymptotically optimal solution without requiring the complete information of the obstacle space. In spite of all of its advantages, RRT* converges to an optimal solution very slowly. Hence to improve the convergence rate, its bidirectional variants were introduced, the Bi-directional RRT* (B-RRT*) and Intelligent Bi-directional RRT* (IB-RRT*). However, as both variants perform pure exploration, they tend to suffer in highly cluttered environments. In order to overcome these limitations, we introduce a new concept of potentially guided bidirectional trees in our proposed Potentially Guided Intelligent Bi-directional RRT* (PIB-RRT*) and Potentially Guided Bi-directional RRT* (PB-RRT*). The proposed algorithms greatly improve the convergence rate and have a more efficient memory utilization. Theoretical and experimental evaluation of the proposed algorithms have been made and compared to the latest state of the art motion planning algorithms under different challenging environmental conditions and have proven their remarkable improvement in efficiency and convergence rate.



There are no comments yet.


page 4

page 11

page 13

page 14

page 15

page 19


Potential Functions based Sampling Heuristic For Optimal Path Planning

Rapidly-exploring Random Tree Star(RRT*) is a recently proposed extensio...

Prediction of Bottleneck Points for Manipulation Planning in Cluttered Environment using a 3D Convolutional Neural Network

Latest research in industrial robotics is aimed at making human robot co...

Object Detection and Motion Planning for Automated Welding of Tubular Joints

Automatic welding of tubular TKY joints is an important and challenging ...

Learning to Predict Ego-Vehicle Poses for Sampling-Based Nonholonomic Motion Planning

Sampling-based motion planning is an effective tool to compute safe traj...

Optimised Informed RRTs for Mobile Robot Path Planning

Path planners based on basic rapidly-exploring random trees (RRTs) are q...

Accelerating Kinodynamic RRT* Through Dimensionality Reduction

Sampling-based motion planning algorithms such as RRT* are well-known fo...

Bi-Directional Grid Constrained Stochastic Processes' Link to Multi-Skew Brownian Motion

Bi-Directional Grid Constrained (BGC) stochastic processes (BGCSPs) cons...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.