@ Max Planck Institute for Intelligent Systems, Germany
Title: Implementing and Testing Bioinspired Mechanisms on Robots to Understand Legged Locomotion
Abstract: Animals run dynamically yet with high robustness. The underlying principles of legged locomotion are still poorly understood. Interdisciplinary research indicates the existence of mechanisms – blueprints – embedded in mechanics and neurocontrol. Such blueprints are found in the morphological design of mammalian legs as leg segmentation ratios, pantographic leg structures, multiarticulate muscles-tendons, and compliant muscle-tendon structures. Neuromuscular control blueprints are for example pattern generators responsible for locomotion rhythm generation. Blueprints could have evolved to counter performance limitations due to mechanical and neurocontrol restrictions of i.e. biological tissue.
Here we base our discussion on findings and insights from implementing biomechanical and control blueprints into legged robots. I.e. Cheetah-cub robot is the first quadruped robot between 0.5kg and 30kg to reach a dynamic speed of Froude 1.3, while trotting in 3D, and in a feed-forward control mode. We apply bioinspired robot- and controller designs to produce rich and biomechanically relevant locomotion data. Recordings from running robotic experiments help us analyzing and comparing robotic and biological legged systems. We will discuss these and other examples also from Biology and Biomechanics indicating the existence of dynamic legged locomotion modes which can rely on feed-forward control patters, in combination with potentially bioinspired leg and robot designs.
Biography: Alexander Spröwitz received his PhD in 2010 working with Modular Robots at EPFL in Switzerland, after studying Mechatronics in Ilmenau, Germany. He runs an independent research group at the Max Planck Institute for Intelligent Systems in Stuttgart, Germany. His group develops new robotic and control approaches to understand the underlying principles of legged locomotion. This interdisciplinary approach includes cooperative work i.e. with Biologists, by designing and running robots and their simulations, and comparing data of running robots with that of running animals.