# Real-Time Polygonal Semantic Mapping for Humanoid Robot Stair Climbing

arXiv: https://arxiv.org/abs/2411.01919 · HTML: https://mlsanity.com/paper/2411.01919/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 23 references that are in the map.
- First posted on arXiv 4 Nov 2024.

## Builds on (most cited first, 7 of 7)

- [A General Optimization-based Framework for Global Pose Estimation with Multiple Sensors](https://mlsanity.com/paper/1901.03642/) (2019)
- [Elevation Mapping for Locomotion and Navigation using GPU](https://mlsanity.com/paper/2204.12876/) (2022)
- [Stair Climbing Stabilization of the HRP-4 Humanoid Robot using Whole-body Admittance Control](https://mlsanity.com/paper/1809.07073/) (2018)
- [Fast Cylinder and Plane Extraction from Depth Cameras for Visual Odometry](https://mlsanity.com/paper/1803.02380/) (2018)
- [CDM-MPC: An Integrated Dynamic Planning and Control Framework for Bipedal Robots Jumping](https://mlsanity.com/paper/2405.11773/) (2024)
- [Polytopic Planar Region Characterization of Rough Terrains for Legged Locomotion](https://mlsanity.com/paper/2207.03098/) (2022)
- [RGB-D SLAM in Indoor Planar Environments with Multiple Large Dynamic Objects](https://mlsanity.com/paper/2203.02882/) (2022)

## Abstract (arXiv)

We present a novel algorithm for real-time planar semantic mapping tailored for humanoid robots navigating complex terrains such as staircases. Our method is adaptable to any odometry input and leverages GPU-accelerated processes for planar extraction, enabling the rapid generation of globally consistent semantic maps. We utilize an anisotropic diffusion filter on depth images to effectively minimize noise from gradient jumps while preserving essential edge details, enhancing normal vector images' accuracy and smoothness. Both the anisotropic diffusion and the RANSAC-based plane extraction processes are optimized for parallel processing on GPUs, significantly enhancing computational efficiency. Our approach achieves real-time performance, processing single frames at rates exceeding 30~Hz, which facilitates detailed plane extraction and map management swiftly and efficiently. Extensive testing underscores the algorithm's capabilities in real-time scenarios and demonstrates its practical application in humanoid robot gait planning, significantly improving its ability to navigate dynamic environments.