Autonomous Forest Inventory with Legged Robots: System Design and Field Deployment

作     者：Mattamala, Matias Chebrolu, Nived Casseau, Benoit Freißmuth, Leonard Frey, Jonas Tuna, Turcan Hutter, Marco Fallon, Maurice 

作者机构：Oxford Robotics Institute The University of Oxford United Kingdom Robotic Systems Lab ETH Zurich Switzerland Technical University of Munich Germany Autonomous Learning Group Max Planck Institute for Intelligent Systems Germany 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2024年

核心收录：

主　　题：Machine design 

摘      要：We present a solution for autonomous forest inventory with a legged robotic platform. Compared to their wheeled and aerial counterparts, legged platforms offer an attractive balance of endurance and low soil impact for forest applications. In this paper, we present the complete system architecture of our forest inventory solution which includes state estimation, navigation, mission planning, and real-time tree segmentation and trait estimation. We present preliminary results for three campaigns in forests in Finland and the UK and summarize the main outcomes, lessons, and challenges. Our UK experiment at the Forest of Dean with the ANYmal D legged platform, achieved an autonomous survey of a 0.96 ha plot in 20 min, identifying over 100 trees with typical DBH accuracy of 2 cm. © 2024, CC BY.