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- W2903388512 abstract "Continuum robots are recognized as one of the most flexible and versatile mobilerobots that are capable of performing various kinds of motions to navigate inunknown and challenging environments. However, the large number of degrees offreedom leads to the difficulty in designing a continuum robot. Moreover, an open-endedsynthesis problem arises whereby there exists no formal models thus far fora designer to determine the optimum control strategy, body structure, number ofsegments and suitable segment lengths during the design stage. Additionally,conventional methods for designing continuum robots do not consider theoptimization of multiple objectives. As such, there has not been any researchcarried out thus far on co-evolving both the morphology and controller ofcontinuum robots using a multi-objective evolutionary optimization approach.Therefore, in this research work, a system is developed to automatically design andoptimize both the morphology and controller of continuum robots by employing anovel hybridized Genetic Programming and self-adaptive Differential Evolutionalgorithm. A multi-objective evolutionary algorithm is incorporated into the artificialevolutionary optimization process to simultaneously maximize the locomotionperformance and minimize the complexity of the continuum robots. In addition, anovel GP tree-based encoding structure is proposed to allow for the representationof the continuum robot's morphology and controller to be optimized simultaneouslyduring co-evolution. The artificial co-evolutionary process is carried out by using theWebots physics simulation software. Two types of continuum robots are to beevolved in this research, namely the snake-like continuum robot (SLCR) and multi-branchingcontinuum robot (MBCR). The outcome of this work shows that thePareto-optimal front of evolved solutions are successfully obtained for the simulatedSLCRs where the evolved heterogeneous SLCRs can perform lateral undulation,narrow path crawling, vertical undulation and lateral rolling moving behaviours forlocomotion. Additionally, the evolved solutions of the MBCRs are converging to apoint where the MBCR with the least number of segments turns out to be thedominating solution. In order to validate the simulated results, the evolved SLCRsare transferred to real world for physical testing using 3D printing technology. Thephysical testing results demonstrate that the evolved SLCRs can be successfullytransferred from simulation to the real world for actual physical deployment in itstask environment. An 82.55% transference accuracy is achieved in this work whichdemonstrates that the proposed multi-objective co-evolutionary algorithm isfeasible and practical to be employed for the automatic design of continuum robots" @default.
- W2903388512 created "2018-12-11" @default.
- W2903388512 creator A5055508618 @default.
- W2903388512 date "2016-01-01" @default.
- W2903388512 modified "2023-09-27" @default.
- W2903388512 title "Realization of multi-objective evolved continuumrobots using 3D printing" @default.
- W2903388512 hasPublicationYear "2016" @default.
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