Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH 44106, United States of America.
Bioinspir Biomim. 2020 Sep 14;15(6):065003. doi: 10.1088/1748-3190/ab9e52.
This manuscript describes neuromechanical modeling of the fruit fly Drosophila melanogaster in the form of a hexapod robot, Drosophibot, and an accompanying dynamic simulation. Drosophibot is a testbed for real-time dynamical neural controllers modeled after the anatomy and function of the insect nervous system. As such, Drosophibot has been designed to capture features of the animal's biomechanics in order to better test the neural controllers. These features include: dynamically scaling the robot to match the fruit fly by designing its joint elasticity and movement speed; a biomimetic actuator control scheme that converts neural activity into motion in the same way as observed in insects; biomimetic sensing, including proprioception from all leg joints and strain sensing from all leg segments; and passively compliant tarsi that mimic the animal's passive compliance to the walking substrate. We incorporated these features into a dynamical simulation of Drosophibot, and demonstrate that its actuators and sensors perform in an animal-like way. We used this simulation to test a neural walking controller based on anatomical and behavioral data from insects. Finally, we describe Drosophibot's hardware and show that the animal-like features of the simulation transfer to the physical robot.
本文以六足机器人 Drosophibot 的形式描述了果蝇 Drosophila melanogaster 的神经机械建模及其伴随的动态模拟。Drosophibot 是一个实时动态神经控制器的测试平台，其模型基于昆虫神经系统的解剖结构和功能。因此，Drosophibot 的设计旨在捕捉动物生物力学的特征，以便更好地测试神经控制器。这些特征包括：通过设计关节弹性和运动速度，使机器人动态缩放以匹配果蝇；仿生执行器控制方案，将神经活动转换为与昆虫观察到的运动方式相同的运动；仿生传感，包括来自所有腿部关节的本体感受和来自所有腿部段的应变传感；以及模拟动物对行走基质的被动顺应性的被动顺应性跗骨。我们将这些特征整合到 Drosophibot 的动态模拟中，并证明其执行器和传感器以类似动物的方式运行。我们使用此模拟来测试基于昆虫解剖结构和行为数据的神经行走控制器。最后，我们描述了 Drosophibot 的硬件，并表明模拟中的类似动物的特征转移到了物理机器人上。
