Realization of multi-objective evolved continuum robots using 3D printing

Chee, Wei Shun (2016) Realization of multi-objective evolved continuum robots using 3D printing. Masters thesis, Universiti Malaysia Sabah.

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Continuum robots are recognized as one of the most flexible and versatile mobile robots that are capable of performing various kinds of motions to navigate in unknown and challenging environments. However, the large number of degrees of freedom leads to the difficulty in designing a continuum robot. Moreover, an open-ended synthesis problem arises whereby there exists no formal models thus far for a designer to determine the optimum control strategy, body structure, number of segments and suitable segment lengths during the design stage. Additionally, conventional methods for designing continuum robots do not consider the optimization of multiple objectives. As such, there has not been any research carried out thus far on co-evolving both the morphology and controller of continuum robots using a multi-objective evolutionary optimization approach. Therefore, in this research work, a system is developed to automatically design and optimize both the morphology and controller of continuum robots by employing a novel hybridized Genetic Programming and self-adaptive Differential Evolution algorithm. A multi-objective evolutionary algorithm is incorporated into the artificial evolutionary optimization process to simultaneously maximize the locomotion performance and minimize the complexity of the continuum robots. In addition, a novel GP tree-based encoding structure is proposed to allow for the representation of the continuum robot's morphology and controller to be optimized simultaneously during co-evolution. The artificial co-evolutionary process is carried out by using the Webots physics simulation software. Two types of continuum robots are to be evolved in this research, namely the snake-like continuum robot (SLCR) and multi-branching continuum robot (MBCR). The outcome of this work shows that the Pareto-optimal front of evolved solutions are successfully obtained for the simulated SLCRs where the evolved heterogeneous SLCRs can perform lateral undulation, narrow path crawling, vertical undulation and lateral rolling moving behaviours for locomotion. Additionally, the evolved solutions of the MBCRs are converging to a point where the MBCR with the least number of segments turns out to be the dominating solution. In order to validate the simulated results, the evolved SLCRs are transferred to real world for physical testing using 3D printing technology. The physical testing results demonstrate that the evolved SLCRs can be successfully transferred from simulation to the real world for actual physical deployment in its task environment. An 82.55% transference accuracy is achieved in this work which demonstrates that the proposed multi-objective co-evolutionary algorithm is feasible and practical to be employed for the automatic design of continuum robots

Item Type: Thesis (Masters)
Keyword: continuum robots, controller, hybridized Genetic Programming, Differential Evolution algorithm
Subjects: T Technology > TJ Mechanical engineering and machinery
Department: FACULTY > Faculty of Engineering
Date Deposited: 27 Oct 2017 16:11
Last Modified: 27 Oct 2017 16:11

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