论文标题

协调的附属物积累了更多的能量,以使地面上的自我权利

Coordinated appendages accumulate more energy to self-right on the ground

论文作者

Xuan, Qihan, Li, Chen

论文摘要

动物和机器人在地面上翻转后必须纠正自己。盘状蟑螂将其翅膀推向了地面,以试图通过翻筋斗动态自我右翼。但是,由于这种动作很艰苦,因此动物通常无法克服势能障碍,并进行了持续的尝试。在此过程中,动物挥舞着腿,其侧向扰动最终导​​致其侧面倾斜到右翼。我们以前的工作开发了一种以蟑螂为灵感的机器人,能够通过腿辅助,有翼的自瞄准,机器人模拟研究表明,该策略的结果敏感地取决于翼腿协调(通过其运动之间的相位来衡量)。在这里,我们进一步阐明了为什么通过开发模板来建模不连续的接触和驱动引起的复杂混合动力学的情况。我们使用该模板来计算人体必须克服的势能屏障,而翼推力和腿部的机械能量贡献,以及由于机翼地面碰撞而引起的机械能量耗散。该模板显示,机翼协调(阶段)通过改变机械能预算强烈影响自我imply的结果。良好的协调附件运动(良好阶段)比不良协调的运动(不良阶段)积累了更多的机械能,从而更好地克服了自我权利的势能障碍。最后,我们证明了该模板的实际使用,以预测一种新的控制策略,以进一步提高自我impling性能并告知机器人设计。

Animals and robots must right themselves after flipping over on the ground. The discoid cockroach pushes its wings against the ground in an attempt to dynamically self-right by a somersault. However, because this maneuver is strenuous, the animal often fails to overcome the potential energy barrier and makes continual attempts. In this process, the animal flails its legs, whose lateral perturbation eventually leads it to roll to the side to self-right. Our previous work developed a cockroach-inspired robot capable of leg-assisted, winged self-righting, and a robot simulation study revealed that the outcome of this strategy depends sensitively on wing-leg coordination (measured by the phase between their motions). Here, we further elucidate why this is the case by developing a template to model the complex hybrid dynamics resulting from discontinuous contact and actuation. We used the template to calculate the potential energy barrier that the body must overcome to self-right, mechanical energy contribution by wing pushing and leg flailing, and mechanical energy dissipation due to wing-ground collision. The template revealed that wing-leg coordination (phase) strongly affects self-righting outcome by changing mechanical energy budget. Well-coordinated appendage motions (good phase) accumulate more mechanical energy than poorly-coordinated motions (bad phase), thereby better overcoming the potential energy barrier to self-right more successfully. Finally, we demonstrated practical use of the template for predicting a new control strategy to further increase self-righting performance and informing robot design.

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