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Kinematic Equations - III

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Related Experiment Video

Updated: May 12, 2026

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms

Published on: August 15, 2016

Improved RRT* Path-Planning Algorithm Based on the Clothoid Curve for a Mobile Robot Under Kinematic Constraints.

Kemeng Ran¹, Yujun Wang¹, Can Fang¹

¹College of Computer and Information Science, Southwest University, Chongqing 400715, China.

Sensors (Basel, Switzerland)

|December 17, 2024

Summary

This study introduces an improved Rapidly-exploring Random Trees* (RRT*) algorithm for mobile robot path planning. The enhanced algorithm generates faster, smoother, and more efficient collision-free paths while respecting kinematic constraints.

Keywords:

Clothoid curve RRT*obstacle avoidance path planning

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Last Updated: May 12, 2026

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Area of Science:

Robotics
Artificial Intelligence
Motion Planning

Background:

Mobile robot navigation requires efficient path planning algorithms.
Kinematic constraints significantly complicate path generation.
Existing algorithms may lack speed, smoothness, or efficiency.

Purpose of the Study:

To develop an improved path planning algorithm for mobile robots.
To generate efficient, smooth, and collision-free paths quickly.
To address limitations of existing path planning methods.

Main Methods:

Utilizes an enhanced Rapidly-exploring Random Trees* (RRT*) algorithm.
Incorporates a bidirectional expansion strategy for faster goal identification.
Employs a node reconnection strategy to optimize path length and memory usage.
Integrates a Clothoid curve-based path deformation for superior obstacle avoidance.

Main Results:

The proposed algorithm demonstrates simpler implementation and higher computational efficiency.
Achieves expedited pathfinding and increased success rates in simulations.
Generates smoother paths compared to conventional algorithms.
Ensures collision-free paths that adhere to mobile robot kinematic constraints.

Conclusions:

The enhanced RRT* algorithm offers significant improvements in mobile robot path planning.
It provides a more efficient, faster, and smoother solution for navigation under kinematic constraints.
The algorithm's strategies enhance obstacle avoidance and overall path-planning capability.