Natural-artificial hybrid swarm: Cyborg-insect group navigation in unknown obstructed soft terrain
CoRR(2024)
摘要
Navigating multi-robot systems in complex terrains has always been a
challenging task. This is due to the inherent limitations of traditional robots
in collision avoidance, adaptation to unknown environments, and sustained
energy efficiency. In order to overcome these limitations, this research
proposes a solution by integrating living insects with miniature electronic
controllers to enable robotic-like programmable control, and proposing a novel
control algorithm for swarming. Although these creatures, called cyborg
insects, have the ability to instinctively avoid collisions with neighbors and
obstacles while adapting to complex terrains, there is a lack of literature on
the control of multi-cyborg systems. This research gap is due to the difficulty
in coordinating the movements of a cyborg system under the presence of insects'
inherent individual variability in their reactions to control input. In
response to this issue, we propose a novel swarm navigation algorithm
addressing these challenges. The effectiveness of the algorithm is demonstrated
through an experimental validation in which a cyborg swarm was successfully
navigated through an unknown sandy field with obstacles and hills. This
research contributes to the domain of swarm robotics and showcases the
potential of integrating biological organisms with robotics and control theory
to create more intelligent autonomous systems with real-world applications.
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