Research/ PLANETARY ROBOTICS
Safe Active Navigation and Exploration for Planetary Environments Using Proprioceptive Measurements
Matthew Jiang, Shipeng Liu, Feifei Qian
Surface Mobility & TerramechanicsOpenAlex topic: Robotic Locomotion and Control · Perception & State EstimationOpenAlex topic: Robotics and Sensor-Based Localization · Learning-based MethodsOpenAlex topic: Reinforcement Learning in Robotics
arXivcs.ROOpenAlexRobotics and Sensor-Based Localization · Robotic Locomotion and Control · Reinforcement Learning in 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.