日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

週刊ニュースレター購読
arXiv:2510.19101

Safe Active Navigation and Exploration for Planetary Environments Using Proprioceptive Measurements

Safe Active Navigation and Exploration for Planetary Environments Using Proprioceptive Measurements

シェア:XThreadsFacebookLINEはてブBluesky

著者: Matthew Jiang, Shipeng Liu, Feifei Qian

分類: cs.RO

原文アブストラクト

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.