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集成模块化神经控制,实现类蜣螂机器人的多样化移动和物体搬运功能。

Integrated Modular Neural Control for Versatile Locomotion and Object Transportation of a Dung Beetle-Like Robot.

出版信息

IEEE Trans Cybern. 2024 Apr;54(4):2062-2075. doi: 10.1109/TCYB.2023.3249467. Epub 2024 Mar 18.

Abstract

Dung beetles can effectively transport dung pallets of various sizes in any direction across uneven terrain. While this impressive ability can inspire new locomotion and object transportation solutions in multilegged (insect-like) robots, to date, most existing robots use their legs primarily to perform locomotion. Only a few robots can use their legs to achieve both locomotion and object transportation, although they are limited to specific object types/sizes (10%-65% of leg length) on flat terrain. Accordingly, we proposed a novel integrated neural control approach that, like dung beetles, pushes state-of-the-art insect-like robots beyond their current limits toward versatile locomotion and object transportation with different object types/sizes and terrains (flat and uneven). The control method is synthesized based on modular neural mechanisms, integrating central pattern generator (CPG)-based control, adaptive local leg control, descending modulation control, and object manipulation control. We also introduced an object transportation strategy combining walking and periodic hind leg lifting for soft object transportation. We validated our method on a dung beetle-like robot. Our results show that the robot can perform versatile locomotion and use its legs to transport hard and soft objects of various sizes (60%-70% of leg length) and weights (approximately 3%-115% of robot weight) on flat and uneven terrains. The study also suggests possible neural control mechanisms underlying the dung beetle Scarabaeus galenus' versatile locomotion and small dung pallet transportation.

摘要

蜣螂能够有效地在不平坦的地形上以任意方向运输各种大小的粪便托盘。虽然这种令人印象深刻的能力可以为多足(类似昆虫)机器人的运动和物体运输提供新的解决方案,但迄今为止,大多数现有的机器人主要使用它们的腿来进行运动。只有少数机器人可以使用它们的腿来实现运动和物体运输,尽管它们仅限于在平坦地形上特定的物体类型/大小(腿长的 10%-65%)。因此,我们提出了一种新的集成神经控制方法,该方法类似于蜣螂,可以将最先进的类似昆虫的机器人推向超越当前限制的方向,实现具有不同物体类型/大小和地形(平坦和不平坦)的多功能运动和物体运输。控制方法基于模块化神经机制进行合成,整合基于中央模式发生器 (CPG) 的控制、自适应局部腿部控制、下降调制控制和物体操纵控制。我们还引入了一种将行走和周期性后腿抬起相结合的软物体运输策略。我们在一个类似蜣螂的机器人上验证了我们的方法。结果表明,机器人可以在平坦和不平坦的地形上进行多功能运动,并使用其腿部运输各种大小(腿长的 60%-70%)和重量(机器人重量的大约 3%-115%)的硬物体和软物体。该研究还表明了蜣螂 Scarabaeus galenus 多功能运动和小粪便托盘运输的可能神经控制机制。

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