Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
J Exp Biol. 2022 May 15;225(10). doi: 10.1242/jeb.243605. Epub 2022 May 23.
To traverse complex terrain, animals often transition between locomotor modes. It is well known that locomotor transitions can be induced by switching in neural control circuits or driven by a need to minimize metabolic energetic cost. Recent work revealed that locomotor transitions in complex 3D terrain cluttered with large obstacles can emerge from physical interaction with the environment controlled by the nervous system. For example, to traverse cluttered, stiff grass-like beams, the discoid cockroach often transitions from using a strenuous pitch mode pushing across the beams to using a less strenuous roll mode rolling into and through the gaps. This transition can save mechanical energetic cost substantially (∼100-101 mJ) but requires overcoming a potential energy barrier (∼10-3-10-2 mJ). Previous robotic physical modeling demonstrated that kinetic energy fluctuation of body oscillation from self-propulsion can help overcome the barrier and facilitate this transition. However, the animal was observed to transition even when the barrier still exceeded kinetic energy fluctuation. Here, we further studied whether and how the cockroach makes active adjustments to facilitate this transition to traverse cluttered beams. The animal repeatedly flexed its head and abdomen, reduced hindleg sprawl, and depressed one hindleg and elevated the other during the pitch-to-roll transition, adjustments which were absent when running on a flat ground. Using a refined potential energy landscape with additional degrees of freedom to model these adjustments, we found that head flexion did not substantially reduce the transition barrier (by ∼10-3 mJ), whereas leg sprawl reduction did so dramatically (by ∼10-2 mJ). We speculate that head flexion is for sensing the terrain to guide the transition via sensory feedback control.
为了穿越复杂的地形,动物通常会在运动模式之间转换。众所周知,运动模式的转换可以通过切换神经控制回路来诱导,也可以通过最小化代谢能量成本的需求来驱动。最近的研究工作表明,在复杂的 3D 地形中,当与环境的物理相互作用受到神经系统的控制时,复杂的运动模式可以转换。例如,为了穿越杂乱的、僵硬的草状梁,圆盘状蟑螂通常会从使用费力的俯仰模式(推动横梁)转换为使用较省力的滚动模式(滚过横梁之间的间隙)。这种转换可以大大节省机械能量成本(约 100-101 mJ),但需要克服一个势能障碍(约 10-3-10-2 mJ)。之前的机器人物理模型表明,身体摆动的自推进产生的动能波动可以帮助克服障碍并促进这种过渡。然而,即使障碍仍然超过动能波动,动物也会观察到过渡。在这里,我们进一步研究了蟑螂是否以及如何主动调整以促进这种过渡,从而穿越杂乱的横梁。在俯仰到滚动的过渡过程中,蟑螂反复弯曲头部和腹部,减少后腿的伸展,压低一条后腿并抬起另一条后腿,而在平坦地面上奔跑时则没有这些调整。使用带有额外自由度的改进势能景观来模拟这些调整,我们发现头部弯曲并没有显著降低过渡障碍(降低约 10-3 mJ),而腿部伸展的减少则显著降低了过渡障碍(降低约 10-2 mJ)。我们推测头部弯曲是为了感知地形,通过感觉反馈控制来引导过渡。