# Improved Bidirectional RRT* Algorithm for Robot Path Planning

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Relate Work

#### 2.1. Principle of RRT*

#### 2.2. Principle of Bidirectional RRT*

## 3. Improved Bidirectional RRT* Algorithm

#### 3.1. Adding Artificial Potential Field Ideas

#### 3.2. Adjusting the Sampling Direction of a Random Tree Growing at a Target Point

#### 3.3. Path Optimization

- Put all the nodes into the set $\{{P}_{1},{P}_{2},{P}_{3}\dots {P}_{n}\}$ in order.
- Connect the nodes in the set one by one from the starting node ${P}_{t}$ until the connection between the node with ${P}_{t+1}$ passes the obstacle and ${P}_{t}$ is the key point in the set. At this point, starting from ${P}_{t}$, connect the remaining nodes in turn until all the key points are found.
- Connect the key points and target points in sequence from the starting point to plan the new path, as shown in Figure 8.

## 4. The Incorporation of the Dynamic Window Method

#### 4.1. Robot Kinematic Models

#### 4.2. Velocity Sampling

## 5. Fusion Algorithm

## 6. Simulation Verification

## 7. Conclusions

## Author Contributions

## Funding

## Data Availability Statement

## Conflicts of Interest

## References

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**Figure 1.**Principle of RRT* extension (

**a**) Path planned by traditional RRT algorithm, (

**b**) Optimized path.

**Figure 6.**Comparison of two algorithms in obstacle-free environment. (

**a**) Traditional bidirectional RRT* algorithm, (

**b**) Improved bidirectional RRT* algorithm.

**Figure 7.**Comparison of two algorithms in obstacle-strewn environment. (

**a**) Traditional bidirectional RRT* algorithm, (

**b**) Improved bidirectional RRT* algorithm.

**Figure 13.**Five algorithms for planning the path. (

**a**) Traditional RRT, (

**b**) Traditional A*, (

**c**) Traditional bidirectional RRT*, (

**d**) Improved bidirectional RRT*, (

**e**) Fusion algorithm.

Path-Planning Algorithms | Path Length | Number of Path Inflection Points |
---|---|---|

Improved bidirectional RRT* | 35.4754 | 9 |

After optimizing the path | 32.8269 | 2 |

Path-Planning Algorithms | Path Length | Planning Time(s) | Number of Path Inflection Points |
---|---|---|---|

Traditional RRT | 39.2132 | 1.3745 | 25 |

Traditional A* | 33.6985 | 0.4971 | 2 |

Traditional bidirectional RRT* | 35.0956 | 0.1178 | 10 |

Improved bidirectional RRT* | 32.9230 | 0.0513 | 1 |

Fusion algorithm | 32.7300 | 377.0923 | none |

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**MDPI and ACS Style**

Xin, P.; Wang, X.; Liu, X.; Wang, Y.; Zhai, Z.; Ma, X.
Improved Bidirectional RRT* Algorithm for Robot Path Planning. *Sensors* **2023**, *23*, 1041.
https://doi.org/10.3390/s23021041

**AMA Style**

Xin P, Wang X, Liu X, Wang Y, Zhai Z, Ma X.
Improved Bidirectional RRT* Algorithm for Robot Path Planning. *Sensors*. 2023; 23(2):1041.
https://doi.org/10.3390/s23021041

**Chicago/Turabian Style**

Xin, Peng, Xiaomin Wang, Xiaoli Liu, Yanhui Wang, Zhibo Zhai, and Xiqing Ma.
2023. "Improved Bidirectional RRT* Algorithm for Robot Path Planning" *Sensors* 23, no. 2: 1041.
https://doi.org/10.3390/s23021041