DTA

Digital Theses Archive

 

Tesi etd-01122017-165223

Type of thesis
Perfezionamento
Author
CORUCCI, FRANCESCO
URN
etd-01122017-165223
Title
Evolutionary Developmental Soft Robotics: Towards Adaptive and Intelligent Machines Following Nature's Approach to Design
Scientific disciplinary sector
ING-IND/34
Course
INGEGNERIA - Biorobotics
Committee
relatore Prof.ssa LASCHI, CECILIA
Keywords
  • automated design
  • design automation
  • developmental robotics
  • embodied cognition
  • embodied intelligence
  • evo-devo
  • evo-devo-soro
  • evo-robo
  • evolutionary developmental soft robotics
  • evolutionary robotics
  • morphological computation
  • morphological plasticity
  • morphology
  • optimization
  • ottimizzazione
  • robotica evolutiva
  • robotica soft
  • simulation
  • soft robotics
  • virtual environments
Exam session start date
;
Availability
completa
Abstract
One of the dreams of researchers in fields such as bionics and artificial intelligence is to be able one day to build adaptive machines approaching the complexity and sophistication of biological creatures, both in terms of life-like morphology and behavior. To this end roboticists have designed increasingly complex machines following a mechatronic approach, later realizing that it was indeed extremely difficult to have them solving even the simplest tasks, such as walking, or grasping an object. Simultaneously, artificial intelligence researchers have traditionally focused their attention on high level cognition, abstract symbol processing, and neural computation, later coming to the conclusion that intelligence starts, in fact, with the body and its dynamic interaction with the surrounding environment. The realization that morphology, and, particularly, a "soft" one, may play a fundamental role in the emergence of intelligence and adaptive behavior has led to research fields such as embodied intelligence and soft robotics, whose premises are to revolutionize both the traditional mechatronic approach to robotics, as well as the study of biological and artificial intelligence. Soft robots are built out of all sorts of compliant and smart materials, that will soon integrate distributed sensing and actuation, as well as unprecedented capabilities that will allow them to grow, change shape and mechanical properties, self-heal, gradually bridging the existing complexity gap among living beings and machines. Nevertheless, soft robotics is also bringing countless problems to the table, related to design, sensing, control and fabrication methodologies. As for the study of intelligence, despite many intuitions, the relationship between softness and intelligence and the conditions under which adaptive and intelligent behavior might emerge in a soft-bodied creature are, to date, still largely unclear. If we look at Nature, however, there is one fundamental, conceptual aspect which motivates the research presented in this thesis, which is the following: biological complexity has emerged from bottom-up, self-organizing, adaptive processes, such as evolution and development. Researchers and engineers tend to approach issues from a top-down perspective instead. They break down problems, they build machines starting from high-level requirements: this approach does not always work when the goal is to study or replicate biological phenomena. We try to understand what intelligence is, how it can be quantified, we struggle trying to understand how the brain works. In the midst of countless models and theories, there is one simple truth we can rely on: brains, bodies, intelligence, adaptive strategies, have all emerged from self-organizing adaptive processes, such as, again, evolution and development. In the spirit of bio-inspiration, i.e. of taking inspiration from Nature in order to devise new engineering solutions, it thus makes sense to replicate natural processes, instead of their products. With all this in mind, in this thesis we present a number of results in the field of evolutionary developmental soft robotics (evo-devo-soro, for brevity), a broad research area drawing ideas from and contributing to a number of neighboring disciplines, such as soft robotics, artificial life, artificial intelligence, cognitive sciences, evolutionary and developmental biology. The main idea of evo-devo-soro is to employ biologically-inspired computational processes in order to design robots, which can be characterized by complex dynamic morphologies composed of multiple materials, including compliant ones. While providing several possibilities for simulation studies targeting phenomena involved in the emergence of intelligent and adaptive behavior, these tools represent at the same time extremely powerful design automation techniques, which may soon allow the automated design and fabrication of complete, self-sufficient, optimized, adaptive machines for different tasks and environments. Reported in order of increasing technical and conceptual complexity, different application scenarios of these techniques will be presented in this work, ranging from engineering applications of evolutionary algorithms in the first chapters, to the implementation of very general evolutionary and developmental system in the last ones. These more general tools are exploited in order to perform extensive simulation studies which attempt to shed light on various phenomena involved in the emergence of adaptive and intelligent behavior, such as the effects of material properties on the evolution of soft locomotion and morphological computation, or the evolution adaptive laws of morphological developmental plasticity in soft machines, and their implications in terms of robustness and resilience. Taking the bottom-up approach to its extreme consequences, and with the aim of isolating different phenomena and effects, our investigations will focus on morphology evolution, with control being kept deliberately simple. Overall, with this work we hope to bring new evidences in fields such as soft robotics and embodied intelligence, which may help unleash the full potential of these disciplines.
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