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Title:Design and control of an origami-enabled soft crawling autonomous robot (OSCAR)
Author(s):Angatkina, Oyuna
Director of Research:Alleyne, Andrew; Wissa, Aimy
Doctoral Committee Chair(s):Alleyne, Andrew
Doctoral Committee Member(s):Tawfick, Sameh; Hsiao-Wecksler, Elizabeth; Chowdhary, Girish
Department / Program:Mechanical Sci & Engineering
Discipline:Mechanical Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):soft robot
origami
path following
path planning
autonomy
kinematic model
pure pursuit
feedback controller
mobile robots
crawling
modular robot
Abstract:Soft mobile robots offer unique benefits as they are highly adaptable to the terrain of travel and safe for interaction with humans. However, the lack of autonomy currently limits their practical applications. Autonomous navigation has been well studied for conventional rigid-bodied robots; however, it is underrepresented in the soft mobile robot research community. Its implementation in soft robots comes with multiple challenges. However, the major challenge is the significant motion uncertainties due to the robot compliance, ground interactions, and limited available sensing. These uncertainties prevent high-level control implementation, such as autonomous navigation, to be performed successfully. Therefore, soft robots require robust design methods, as well as path following and path planning algorithms, to mitigate these uncertainties and enable autonomy. This dissertation develops and implements autonomous navigation for a novel origami-enabled soft crawling autonomous robot called OSCAR. In order to implement autonomous navigation, it first mitigates the OSCAR’s motion uncertainties by a multi-step iterative design process. Analysis has shown that OSCAR’s motion uncertainties are the result of: (i) the ground-feet interaction, (ii) effectiveness of low-level closed-loop control and, (iii) variability in the manufacturing assembly process. The iterative control-oriented design allows a robust and reliable OSCAR performance and enables high-level path following control implementation. To design and implement path following control, this research presents an idealized kinematic model and introduces an empirically based correction to make the model predictions match the experimental data. The dissertation investigates two separate path-following controllers: a model-based pure pursuit and a feedback controller. The controllers are investigated in both simulation and experiment and the need for feedback is clearly demonstrated. Finally, this research presents the path planning in order to complete OSCAR’s autonomous navigation. The simulation and experimental results show that OSCAR can accurately navigate in a 2D environment while avoiding static obstacles. Lastly, the coupled locomotion of multiple OSCARs demonstrates an extension of functionality and expands the potential design and operation space for this promising type of soft robot.
Issue Date:2021-04-01
Type:Thesis
URI:http://hdl.handle.net/2142/110414
Rights Information:© 2021 Oyuna Angatkina
Date Available in IDEALS:2021-09-17
Date Deposited:2021-05


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