Bio-inspired robotics: efference copies and adaptive feedforward control
File(s)
Author(s)
Campbell, Benjamin
Type
Thesis
Abstract
This thesis investigates how insects control movement using adaptive feedforward control and efference copies, and how these principles can be applied to robotic systems. A phenomenological control architecture—the fully-separable-degrees-of-freedom (FSDoF) controller—is developed to formalise efference copies in a control-theoretic context. The FSDoF architecture is used in simulation to examine control advantages of efference copy-based systems. Specifically, it enables sensors to remain within their operating range, thereby optimising sensitivity to external disturbances, and is particularly effective in systems with time delays and significant sensor noise. When combined with high-pass-filter-like sensors, the FSDoF controller also exhibits a unique robustness to changes in sensor gain and bandwidth. Furthermore, a method is introduced to design FSDoF controllers for multi-input multi-output (MIMO) systems with multiple, distinct time delays. This work formalises the efference copy hypothesis in insects from an engineering perspective, offering a functional explanation for their evolutionary advantages, and enabling the generation of experimentally testable hypotheses.
One such hypothesis is that insect feedforward controllers adapt to changes in system dynamics. A series of free-flight experiments in Drosophila melanogaster supports this idea. Following unilateral wing damage, flies exhibited increased flight speeds in darkness compared to intact controls. When flying in light, with visual feedback, their speed was reduced to near-control levels. Altogether, the results indicate that the adaptation was not solely due to changes in mechanosensory feedback, but suggest adaptive feedforward control.
Building on these insights, an implicit adaptive feedforward (IAFF) control strategy is proposed and implemented on a quadrotor platform. This controller uses adaptive sensitivity derivatives, so that it could, in theory, cope with an inversion of the system dynamics. IAFF control improved the reference tracking in a Parrot Mambo mini-drone within minutes of operation, starting from a randomised feedforward controller.
One such hypothesis is that insect feedforward controllers adapt to changes in system dynamics. A series of free-flight experiments in Drosophila melanogaster supports this idea. Following unilateral wing damage, flies exhibited increased flight speeds in darkness compared to intact controls. When flying in light, with visual feedback, their speed was reduced to near-control levels. Altogether, the results indicate that the adaptation was not solely due to changes in mechanosensory feedback, but suggest adaptive feedforward control.
Building on these insights, an implicit adaptive feedforward (IAFF) control strategy is proposed and implemented on a quadrotor platform. This controller uses adaptive sensitivity derivatives, so that it could, in theory, cope with an inversion of the system dynamics. IAFF control improved the reference tracking in a Parrot Mambo mini-drone within minutes of operation, starting from a randomised feedforward controller.
Version
Open Access
Date Issued
2025-06-14
Date Awarded
01/01/2026
Advisor
Krapp, Holger
Lin, Huai-Ti
Sponsor
Defence Science and Technology Laboratory (Great Britain)
Grant Number
DSTLX1000161145
Publisher Department
Department of Bioengineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)