自组织躲避喷泉机动与生物启发水下机器人集体

F. Berlinger, Paula Wulkop, R. Nagpal
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引用次数: 7

摘要

一些动物物种自我组织成大群体,以利用觅食、建造或躲避捕食者等重要行为。随着机器人技术和自动化的进步,工程多智能体系统已经受到启发,通过分散和动态协调实现类似的高度可扩展、鲁棒和适应性自治。然而,到目前为止,它们最成功的演示是在地面上或在中央控制器和外部跟踪的部分协助下进行的。在这里,我们展示了一个水下机器人群体,实现了完全的时空协调。以鱼类为例,我们的机器人通过实时机载多机器人跟踪和本地决策来显示对齐、编队控制和协调逃生。伴随着定制模拟器,这个机器人平台推进了物理验证的算法开发,用于集体行为和未来的应用,包括集体探索、跟踪和捕获或环境采样。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Self-Organized Evasive Fountain Maneuvers with a Bioinspired Underwater Robot Collective
Several animal species self-organize into large groups to leverage vital behaviors such as foraging, construction, or predator evasion. With the advancement of robotics and automation, engineered multi-agent systems have been inspired to achieve similarly high degrees of scalable, robust, and adaptable autonomy through decentralized and dynamic coordination. So far however, they have been most successfully demonstrated above ground or with partial assistance from central controllers and external tracking. Here we demonstrate an underwater robot collective that realizes full spatiotemporal coordination. Using the example of fish-inspired evasive maneuvers, our robots display alignment, formation control, and coordinated escape, enabled by real-time on-board multi-robot tracking and local decision making. Accompanied by a custom simulator, this robotic platform advances the physically- validated development of algorithms for collective behaviors and future applications including collective exploration, tracking and capture, or environmental sampling.
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