# Mobile Robot Path Planning in Dynamic Environments: A Survey

**Authors:** Kuanqi Cai, Chaoqun Wang, Jiyu Cheng, Clarence W De Silva, Max Q. -H. Meng  
**arXiv:** [2006.14195](https://arxiv.org/abs/2006.14195)  
**Date:** 2020-06-25  
**Summary page:** https://www.summarizepaper.com/en/paper/2006.14195v2/

## Key points

- Comprehensive survey of path planning methods for mobile robots in densely populated dynamic environments
- Examination of global and local path planning components of navigation framework
- Discussion of recent progress in path planning methods, including strengths and weaknesses
- Velocity Obstacle method and its variants highlighted as effective local planners
- Reinforcement learning-based path planning algorithms detailed as widely used model-free method in current robot applications
- Authors: Kuanqi Cai, Chaoqun Wang, Jiyu Cheng, Clarence W De Silva, and Max Q.-H. Meng

## Summary

This paper provides a comprehensive survey of path planning methods for mobile robots in densely populated dynamic environments. The authors examine the global and local path planning components of the navigation framework, considering their scope and executability. They discuss recent progress in path planning methods, highlighting their strengths and weaknesses. Of particular interest is the Velocity Obstacle method and its variants which serve as effective local planners. Additionally, reinforcement learning-based path planning algorithms are detailed as a widely used model-free method in current robot applications. This survey is authored by Kuanqi Cai, Chaoqun Wang, Jiyu Cheng, Clarence W De Silva, and Max Q.-H. Meng.