论文标题
动态英寸虫爬行：三连锁机器人的性能分析和优化
Dynamic Inchworm Crawling: Performance Analysis and Optimization of a Three-link Robot
论文作者
论文摘要
Inch虫爬行允许在广泛的致动频率下同时进行准危机和动态步态。这种运动机制在非骨骼动物中很常见，在以生物启发的软机器人技术领域进行了广泛利用。在这项工作中，我们开发并模拟了三连杆机器人的混合动态爬行，并具有被动的摩擦接触。我们在关节角度的周期性输入下进行实验测试并实验测试了这种机器人，并与理论预测很好地一致。这允许理解和利用惯性的影响，以便在输入参数中找到最佳性能。提出了对摩擦不确定性的鲁棒性的简单标准。根据此标准调整输入可以提高低频致动的鲁棒性，同时增加频率允许具有高进步速度和鲁棒性的步态。最后，研究了质量分布不平的优势。引入时间尺度技术以形成输入，这些输入在不重新组装机器人的情况下达到相似的效果。基于机器学习的优化被应用于这些输入，以进一步提高机器人在行进距离中的性能。
Inchworm crawling allows for both quasistatic and dynamic gaits at a wide range of actuation frequencies. This locomotion mechanism is common in nonskeletal animals and exploited extensively in the bio-inspired field of soft robotics. In this work we develop and simulate the hybrid dynamic crawling of a three-link robot, with passive frictional contacts. We fabricate and experimentally test such robot under periodic inputs of joints' angles, with good agreement to the theoretical predictions. This allows to comprehend and exploit the effects of inertia in order to find optimal performance in inputs' parameters. A simple criterion of robustness to uncertainties in friction is proposed. Tuning the inputs according to this criterion improves the robustness of low-frequency actuation, while increasing the frequency allows for gaits with both high advancement velocity and robustness. Finally, the advantages of uneven mass distribution are studied. Time-scaling technique is introduced to shape inputs that achieve similar effect without reassembling the robot. A machine-learning based optimization is applied to these inputs to further improve the robot's performance in traveling distance.
