Layered Control Architectures: Constructive Theory and Application to Legged Robots

Citation

Csomay-Shanklin, Noel V. (2025) Layered Control Architectures: Constructive Theory and Application to Legged Robots. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/k0ns-c606. https://resolver.caltech.edu/CaltechTHESIS:06032025-023615578

Abstract

Fueled in part by the imagination of science fiction, every decade since the 1950s has expected robots to enter our everyday lives in the subsequent decade. Despite this anticipation, the widespread adoption of robots has consistently fallen short of societal expectations. This delay is attributable to the sheer variety of complexities in robotics --- perception, contact-rich dynamics, human-robot interactions. Each sub-discipline of robotics poses unique challenges that must be addressed to achieve general autonomy. As progress is made in these sub-fields, it is increasingly important to adopt a layered architecture perspective that combines isolated controller blocks into a unified framework.

This thesis argues that on the road to general autonomy, adopting layered architectures enables three key benefits: efficiency, feasibility, and generalizability. We root our discussion in a general problem in robotics: the design of a controller that navigates a robot to a goal state while satisfying all state and input constraints that are present. Throughout the thesis, we focus on solutions that are both general --- applicable across a wide variety of robotic platforms --- and concrete --- deployed and tested on specific hardware platforms. As such, we aim to not only propose a framework for reasoning about this problem, but also methods to synthesize controllers that solve it in practice for legged robots.

We begin by motivating and formalizing the notion of layered architectures and use this to build our control stack from the bottom up. We start with low-level planning and tracking layers that stabilize the system within a tracking tube for both the actuated and underactuated states of legged robots. We then introduce high-level planning and tracking layers that generate and follow sparse, dynamically feasible graphs for coarse global navigation through cluttered environments. By decomposing the global control problem into interacting levels and layers, each operating with disparate timescales and system abstractions, we enable tractable, reliable, and extensible robot autonomy.

Throughout this thesis, an emphasis will be placed on mathematical structure, constructive synthesis, and experimental validation. We demonstrate that adopting a layered architecture perspective is not merely an implementation convenience, but a fundamental organizing principle that can enable true robot autonomy.

Thesis Files