# POA: Passable Obstacles Aware Path-planning Algorithm for Navigation of a Two-wheeled Robot in Highly Cluttered Environments

arXiv: https://arxiv.org/abs/2307.08141 · HTML: https://mlsanity.com/paper/2307.08141/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 22 references that are in the map.
- First posted on arXiv 16 Jul 2023.

## Builds on (most cited first, 4 of 4)

- [Mobile Robot Path Planning in Dynamic Environments: A Survey](https://mlsanity.com/paper/2006.14195/) (2020)
- [WareVR: Virtual Reality Interface for Supervision of Autonomous Robotic System Aimed at Warehouse Stocktaking](https://mlsanity.com/paper/2110.11052/) (2021)
- [MuCaSLAM: CNN-Based Frame Quality Assessment for Mobile Robot with Omnidirectional Visual SLAM](https://mlsanity.com/paper/2209.01936/) (2022)
- [CNN-based Omnidirectional Object Detection for HermesBot Autonomous Delivery Robot with Preliminary Frame Classification](https://mlsanity.com/paper/2110.11829/) (2021)

## Abstract (arXiv)

This paper focuses on Passable Obstacles Aware (POA) planner - a novel navigation method for two-wheeled robots in a highly cluttered environment. The navigation algorithm detects and classifies objects to distinguish two types of obstacles - passable and unpassable. Our algorithm allows two-wheeled robots to find a path through passable obstacles. Such a solution helps the robot working in areas inaccessible to standard path planners and find optimal trajectories in scenarios with a high number of objects in the robot's vicinity. The POA planner can be embedded into other planning algorithms and enables them to build a path through obstacles. Our method decreases path length and the total travel time to the final destination up to 43% and 39%, respectively, comparing to standard path planners such as GVD, A*, and RRT*