Flexible Supervised Autonomy for Exploration in Subterranean Environments

作     者：Harel Biggie Eugene R. Rush Danny G. Riley Shakeeb Ahmad Michael T. Ohradzansky Kyle Harlow Michael J. Miles Daniel Torres Steve McGuire Eric W. Frew Christoffer Heckman J. Sean Humbert 

作者机构：Computer Science University of Colorado Boulder Mechanical Engineering University of Colorado Boulder Aerospace Engineering Sciences University of Colorado Boulder Electrical & Computer Engineering University of California Santa Cruz 

出 版 物：《Field Robotics》 

年 卷 期：2025年第3卷

页      面：125-189页

主　　题：Robots Robot sensing systems Robot kinematics Location awareness Navigation Planning Robot vision systems Laser radar Cameras Three-dimensional displays 

摘      要：While the capabilities of autonomous systems have been steadily improving in recent years, these systems still struggle to rapidly explore previously unknown environments without the aid of GPS-assisted navigation. The DARPA Subterranean (SubT) Challenge aimed to fast track the development of autonomous exploration systems by evaluating their performance in real-world underground search-and-rescue scenarios. Subterranean environments present a plethora of challenges for robotic systems, such as limited communications, complex topology, visually-degraded sensing, and harsh terrain. The presented solution enables long-term autonomy with minimal human supervision by combining a powerful and independent single-agent autonomy stack, with higher level mission management operating over a flexible mesh network. The autonomy suite deployed on quadruped and wheeled robots was fully independent, freeing the human supervision to loosely supervise the mission, and make high-impact strategic decisions. We also discuss lessons learned from fielding our system at the SubT Final Event, relating to vehicle versatility, system adaptability, and reconfigurable communications.