论文标题

由生物启发的多机器人自治

Bio-inspired Multi-robot Autonomy

论文作者

Nandakumar, Shivoh Chirayil, Harper, Samuel, Mitchell, Daniel, Blanche, Jamie, Lim, Theodore, Yamamoto, Ikuo, Flynn, David

论文摘要

越来越多的价值工业市场正在推动趋势,以提高居民自治系统的功能和弹性。这导致了多机器人车队的增加,旨在利用各种平台的互补属性。在本文中,我们介绍了一种新型的生物启发的系统方法共生系统(SSOSA),用于设计由地面四倍和轮式平台组成的多机器人车队的运营治理。 Ssosa将MR-Fleet融入了居民基础架构监测系统中,成为一个协作的数字共享。通过延迟双向通信网络实现的集成分布式系统的高度可见性,支持整个集成系统的协作,协调和佐证(3C)。在我们的实验中,我们演示了操作员如何激活预定的自主任务并利用SSOSA克服自主任务的内在风险和外部风险。我们证明了如何通过现场和沙哑之间的本地合作来增强弹性,我们可以检测到替换电池,并利用Spot的操纵器支架来支持Clearpath Husky Husky A200轮式机器人平台。由于机器人可以协作以确保赫斯基机器人的电池状态,因此可以提高自治任务的弹性。总体而言,这些初始结果证明了SSOSA方法在解决可扩展自主权(弹性)的关键操作障碍方面的价值。

Increasingly, high value industrial markets are driving trends for improved functionality and resilience from resident autonomous systems. This led to an increase in multi-robot fleets that aim to leverage the complementary attributes of the diverse platforms. In this paper we introduce a novel bio-inspired Symbiotic System of Systems Approach (SSOSA) for designing the operational governance of a multi-robot fleet consisting of ground-based quadruped and wheeled platforms. SSOSA couples the MR-fleet to the resident infrastructure monitoring systems into one collaborative digital commons. The hyper visibility of the integrated distributed systems, achieved through a latency bidirectional communication network, supports collaboration, coordination and corroboration (3C) across the integrated systems. In our experiment, we demonstrate how an operator can activate a pre-determined autonomous mission and utilize SSOSA to overcome intrinsic and external risks to the autonomous missions. We demonstrate how resilience can be enhanced by local collaboration between SPOT and Husky wherein we detect a replacement battery, and utilize the manipulator arm of SPOT to support a Clearpath Husky A200 wheeled robotic platform. This allows for increased resilience of an autonomous mission as robots can collaborate to ensure the battery state of the Husky robot. Overall, these initial results demonstrate the value of a SSOSA approach in addressing a key operational barrier to scalable autonomy, the resilience.

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