让机器人像动物一样‘长大’，通过动态调整电机强度提升运动能力与多样性。
Time to Play: Simulating Early-Life Animal Dynamics Enhances Robotics Locomotion Discovery
- 模拟生物生长中的肌力变化，动态调节机器人电机扭矩。
- 在多种任务中显著提升运动表现与行为多样性，尤其早期优势促进后期技能发现。
- 适用于需要适应性与演化能力的机器人控制场景，如仿生设计与自适应学习。
动物体态发育深刻影响其运动方式，但传统机器人通常在静态物理参数下训练。受生物发育过程中肌肉功率变化的启发，我们提出寿命期内机械输出缩放（SMOL）课程，动态调节机器人执行器强度，以模拟成长与衰老过程中的功率-重量比变化。将SMOL融入MAP-Elites质量-多样性框架，在标准机器人任务中动态调整扭矩，模拟动物成长过程中的力量演化。全面实证表明，SMOL调度在不同控制场景中持续提升运动性能与行为多样性，使智能体能利用早期有利物理条件，为达到最终身体状态时的技能突破奠定基础。基于人类总功率输出研究，我们还构建了SMOL-Human调度，模拟青春期等非线性体形变化，并探究其对机器人运动的影响。
原文摘要 · Abstract (English)
Developmental changes in body morphology profoundly shape locomotion in animals, yet artificial agents and robots are typically trained under static physical parameters. Inspired by ontogenetic scaling of muscle power in biology, we propose Scaling Mechanical Output over Lifetime (SMOL), a novel curriculum that dynamically modulates robot actuator strength to mimic natural variations in power-to-weight ratio during growth and ageing. Integrating SMOL into the MAP-Elites quality-diversity framework, we vary the torque in standard robotics tasks to mimic the evolution of strength in animals as they grow up and as their body changes. Through comprehensive empirical evaluation, we show that the SMOL schedule consistently elevates both performance and diversity of locomotion behaviours across varied control scenarios, by allowing agents to leverage advantageous physics early on to discover skills that act as stepping stones when they reach their final standard body properties. Based on studies of the total power output in humans, we also implement the SMOL-Human schedule that models isometric body variations due to non-linear changes like puberty, and study its impact on robotics locomotion.
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