通过调整机器人形态设计，实现群体在光照下的高效聚集与多样化行为。
Aggregating swarms through morphology handling design contingencies: from the sweet spot to a rich expressivity
- 通过可调外骨骼控制机器人对环境力的对齐或反向对齐倾向。
- 在不停止条件下，对齐强度接近最优时光趋性成功率显著提升。
- 精准调控对齐强度可实现从高效聚集到丰富集体行为的表达能力。
形态计算——利用机器人物理设计简化任务实现——在群体机器人领域已被证实有效。本文通过实验与数值模拟表明，该策略的成功高度依赖于机器人的控制策略及物理设计细节。研究采用嵌入外骨骼的Kilobots群体，其设计决定了机器人对外部力方向的对齐或反向对齐倾向。实验发现，在光趋性任务中（机器人进入光照区域后停止），两种形态表现差异明显；而当机器人无法停止仅能减速时，差异更加剧烈。基于对机器人自对齐动力学的精确物理模型，数值模拟显示：仅在自对齐强度接近‘甜点’值时，才能实现高效的光趋性行为；而探索不同对齐强度范围，则可激发丰富的集体行为表达。结果揭示了形态设计与群体智能之间深刻的耦合关系。
原文摘要 · Abstract (English)
Morphological computing, the use of the physical design of a robot to ease the realization of a given task has been proven to be a relevant concept in the context of swarm robotics. Here we demonstrate both experimentally and numerically, that the success of such a strategy may heavily rely on the type of policy adopted by the robots, as well as on the details of the physical design. To do so, we consider a swarm of robots, composed of Kilobots embedded in an exoskeleton, the design of which controls the propensity of the robots to align or anti-align with the direction of the external force they experience. We find experimentally that the contrast that was observed between the two morphologies in the success rate of a simple phototactic task, where the robots were programmed to stop when entering a light region, becomes dramatic, if the robots are not allowed to stop, and can only slow down. Building on a faithful physical model of the self-aligning dynamics of the robots, we perform numerical simulations and demonstrate on one hand that a precise tuning of the self-aligning strength around a sweet spot is required to achieve an efficient phototactic behavior, on the other hand that exploring a range of self-alignment strength allows for a rich expressivity of collective behaviors.
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