RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Oslo, Norway.
Department of Informatics, University of Oslo, Oslo, Norway.
Bioinspir Biomim. 2023 Jun 29;18(4). doi: 10.1088/1748-3190/ace017.
For a robot to be both autonomous and collaborative requires the ability to adapt its movement to a variety of external stimuli, whether these come from humans or other robots. Typically, legged robots have oscillation periods explicitly defined as a control parameter, limiting the adaptability of walking gaits. Here we demonstrate a virtual quadruped robot employing a bio-inspired central pattern generator (CPG) that can spontaneously synchronize its movement to a range of rhythmic stimuli. Multi-objective evolutionary algorithms were used to optimize the variation of movement speed and direction as a function of the brain stem drive and the centre of mass control respectively. This was followed by optimization of an additional layer of neurons that filters fluctuating inputs. As a result, a range of CPGs were able to adjust their gait pattern and/or frequency to match the input period. We show how this can be used to facilitate coordinated movement despite differences in morphology, as well as to learn new movement patterns.
要使机器人既具有自主性又具有协作性，就需要使其运动能够适应各种外部刺激，无论是来自人类还是其他机器人。通常，腿式机器人的振荡周期被明确定义为控制参数，从而限制了步行步态的适应性。在这里，我们展示了一种虚拟四足机器人，它采用了一种受生物启发的中央模式发生器（CPG），可以自发地将其运动与一系列节奏性刺激同步。多目标进化算法被用于优化运动速度和方向的变化，分别作为脑干驱动和质心控制的函数。然后，对过滤波动输入的额外一层神经元进行了优化。结果，一系列 CPG 能够调整其步态模式和/或频率以匹配输入周期。我们展示了如何利用这一点来促进协调运动，即使存在形态差异，以及如何学习新的运动模式。
