论文标题

部分可观测时空混沌系统的无模型预测

Team CERBERUS Wins the DARPA Subterranean Challenge: Technical Overview and Lessons Learned

论文作者

Tranzatto, Marco, Dharmadhikari, Mihir, Bernreiter, Lukas, Camurri, Marco, Khattak, Shehryar, Mascarich, Frank, Pfreundschuh, Patrick, Wisth, David, Zimmermann, Samuel, Kulkarni, Mihir, Reijgwart, Victor, Casseau, Benoit, Homberger, Timon, De Petris, Paolo, Ott, Lionel, Tubby, Wayne, Waibel, Gabriel, Nguyen, Huan, Cadena, Cesar, Buchanan, Russell, Wellhausen, Lorenz, Khedekar, Nikhil, Andersson, Olov, Zhang, Lintong, Miki, Takahiro, Dang, Tung, Mattamala, Matias, Montenegro, Markus, Meyer, Konrad, Wu, Xiangyu, Briod, Adrien, Mueller, Mark, Fallon, Maurice, Siegwart, Roland, Hutter, Marco, Alexis, Kostas

论文摘要

储层计算是预测湍流的有力工具,其简单的架构具有处理大型系统的计算效率。然而,其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间,然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用,该系统模拟了湍流的若干特征。我们表明,使用径向基函数作为非线性投影器,即使只有部分观测并且不知道控制方程,也能稳健地捕捉复杂的系统非线性。最后,我们表明,当测量稀疏、不完整且带有噪声,甚至控制方程变得不准确时,我们的网络仍然可以产生相当准确的预测,从而为实际湍流系统的无模型预测铺平了道路。

This article presents the CERBERUS robotic system-of-systems, which won the DARPA Subterranean Challenge Final Event in 2021. The Subterranean Challenge was organized by DARPA with the vision to facilitate the novel technologies necessary to reliably explore diverse underground environments despite the grueling challenges they present for robotic autonomy. Due to their geometric complexity, degraded perceptual conditions combined with lack of GPS support, austere navigation conditions, and denied communications, subterranean settings render autonomous operations particularly demanding. In response to this challenge, we developed the CERBERUS system which exploits the synergy of legged and flying robots, coupled with robust control especially for overcoming perilous terrain, multi-modal and multi-robot perception for localization and mapping in conditions of sensor degradation, and resilient autonomy through unified exploration path planning and local motion planning that reflects robot-specific limitations. Based on its ability to explore diverse underground environments and its high-level command and control by a single human supervisor, CERBERUS demonstrated efficient exploration, reliable detection of objects of interest, and accurate mapping. In this article, we report results from both the preliminary runs and the final Prize Round of the DARPA Subterranean Challenge, and discuss highlights and challenges faced, alongside lessons learned for the benefit of the community.

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