ROOct 19, 2020

Autonomous Spot: Long-Range Autonomous Exploration of Extreme Environments with Legged Locomotion

arXiv:2010.09259v3157 citations
Originality Incremental advance
AI Analysis

This work addresses the problem of autonomous exploration in challenging terrains for applications like the DARPA Subterranean Challenge, representing an incremental advancement in legged robotics.

The paper tackles enabling long-range autonomous exploration in extreme environments using the Boston Dynamics Spot robot, demonstrating performance in real-world scenarios through integration of the NeBula autonomy architecture with advanced mobility systems.

This paper serves as one of the first efforts to enable large-scale and long-duration autonomy using the Boston Dynamics Spot robot. Motivated by exploring extreme environments, particularly those involved in the DARPA Subterranean Challenge, this paper pushes the boundaries of the state-of-practice in enabling legged robotic systems to accomplish real-world complex missions in relevant scenarios. In particular, we discuss the behaviors and capabilities which emerge from the integration of the autonomy architecture NeBula (Networked Belief-aware Perceptual Autonomy) with next-generation mobility systems. We will discuss the hardware and software challenges, and solutions in mobility, perception, autonomy, and very briefly, wireless networking, as well as lessons learned and future directions. We demonstrate the performance of the proposed solutions on physical systems in real-world scenarios.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes