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Title: A Multi-timescale Paradigm for Control of Robotic Systems
Committee:
Dr. F. Zhang, Advisor
Dr. Coogan, Chair
Dr. Wardi
Dr. Tao
Abstract:
The objective of the proposed research is to design a control paradigm for a swarm of robots to achieve emergent complex behaviors without sharing measurements through communication channels. Reliable communication channels cannot be always guaranteed especially for robots with severe resource limitations such as underwater robotics. The paradigm consists of an interplay of geometrical and swarming algorithms that evolve in different timescales. The geometrical algorithm leverages the value of available relative positions by extracting a geometrical information through Principal Component Analysis. This geometrical information is used by the swarming algorithm to design motion control laws to accomplish desired collective behaviors. Remarkably, the paradigm enables a swarm of various sizes and graph structures to perform collective source seeking and level curve tracking of a scalar field without the need to estimate the field gradient or share measurements among the agents. The successful removal of the challenging requirement of estimation and communication is attributed to the locally extracted geometrical information and the design of the control law. The proposed paradigm offers a new method that enables robots with limited resources to perform various swarming activities with only local information. Additionally, it provides a new model to quantitatively describe a collective behavior of some biological phenomena which are of great importance in behavioral and computational biology.
