Safe Active Navigation and Exploration for Planetary Environments Using Proprioceptive Measurements

Fuente: arXiv
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Main Authors: Jiang, Matthew, Liu, Shipeng, Qian, Feifei
Format: Preprint
Published: 2025
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author Jiang, Matthew
Liu, Shipeng
Qian, Feifei
author_facet Jiang, Matthew
Liu, Shipeng
Qian, Feifei
contents Legged robots can sense terrain through force interactions during locomotion, offering more reliable traversability estimates than remote sensing and serving as scouts for guiding wheeled rovers in challenging environments. However, even legged scouts face challenges when traversing highly deformable or unstable terrain. We present Safe Active Exploration for Granular Terrain (SAEGT), a navigation framework that enables legged robots to safely explore unknown granular environments using proprioceptive sensing, particularly where visual input fails to capture terrain deformability. SAEGT estimates the safe region and frontier region online from leg-terrain interactions using Gaussian Process regression for traversability assessment, with a reactive controller for real-time safe exploration and navigation. SAEGT demonstrated its ability to safely explore and navigate toward a specified goal using only proprioceptively estimated traversability in simulation.
format Preprint
id arxiv_https___arxiv_org_abs_2510_19101
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Safe Active Navigation and Exploration for Planetary Environments Using Proprioceptive Measurements
Jiang, Matthew
Liu, Shipeng
Qian, Feifei
Robotics
Legged robots can sense terrain through force interactions during locomotion, offering more reliable traversability estimates than remote sensing and serving as scouts for guiding wheeled rovers in challenging environments. However, even legged scouts face challenges when traversing highly deformable or unstable terrain. We present Safe Active Exploration for Granular Terrain (SAEGT), a navigation framework that enables legged robots to safely explore unknown granular environments using proprioceptive sensing, particularly where visual input fails to capture terrain deformability. SAEGT estimates the safe region and frontier region online from leg-terrain interactions using Gaussian Process regression for traversability assessment, with a reactive controller for real-time safe exploration and navigation. SAEGT demonstrated its ability to safely explore and navigate toward a specified goal using only proprioceptively estimated traversability in simulation.
title Safe Active Navigation and Exploration for Planetary Environments Using Proprioceptive Measurements
topic Robotics
url https://arxiv.org/abs/2510.19101