Abstract:
The dynamics of complex chains of rigid solids present non-linear coupling effects (Coriolis, centrifugal, inertia). Such effects are leveraged during human and animal locomotion to produce complex agile behaviors. In robotics, classical control methods simplify the dynamics of the problem using reduced-order models. Many dynamic effects are absorbed during this simplification. The aim of this PhD thesis is to design a control strategy that leverages the intrinsic dynamic effects rather than simplifying them. The core idea is that the dimension of the problem can be greatly reduced by imposing virtual constraints on the system. Virtual constraints can be tuned to achieve desirable dynamic effects such as embedding the spring-like nature of a leg into an actuated chain of solids. Additionally, the use of set-based approaches to tackle the viability of the next step is proposed for improving the range of admissible dynamic behaviors.
Thesis supervisors:
