mlsanityData to 14 Oct 2026

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

arXiv 2307.08141 ↗First posted 16 Jul 2023cs.RO cs.AIcited by 0

Not on the map. Why?

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*

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

4 of 22 references.

References · 4

  1. 2020Mobile Robot Path Planning in Dynamic Environments: A Surveycited by 5
  2. 2021WareVR: Virtual Reality Interface for Supervision of Autonomous Robotic System Aimed at Warehouse Stocktakingcited by 5
  3. 2022MuCaSLAM: CNN-Based Frame Quality Assessment for Mobile Robot with Omnidirectional Visual SLAMcited by 3
  4. 2021CNN-based Omnidirectional Object Detection for HermesBot Autonomous Delivery Robot with Preliminary Frame Classificationcited by 2

Built on by

Not cited yet.