This study is a part of a large scale research project investigating the motor control system of the octopus by referring to kinematic, biomechanical and neural aspects. Here we focus on the kinematics of octopus arm movements and its underlying principles, by processing digital recordings of live movements that are obtained while an octopus is held in a big glass tank. The project is aimed at better understanding the motor control of the octopus arm, and implementing some of the gained knowledge in biologically inspired hyper-redundant manipulators.;Modeling octopus arm movements is performed by a recently developed system (Yekutieli et al. 2007) dedicated to efficiently reconstruct the arm movements in 3D space from a pair of video records taken by two calibrated cameras. The system is based on a manual segmentation of the octopus arm in each frame of a video sequence. This is a time consuming process when a large data set is considered. During this work we have developed an algorithm for the automatic detection of the virtual backbone of the octopus arm in video records (Zelman et al. 2008) based on a recently presented segmentation algorithm (Galun et al. 2005). Utilizing the automatic detection together with the reconstruction system enables efficient reconstructions of a large set of octopus arm movements. Each movement is essentially modeled as a spatio-temporal profile which describes the configuration of the arm in 3D space as a function of time. A large data set of modeled octopus arm movements has been reconstructed from video sequences by the manual detection method. We believe that the automatic method is an essential tool in order to efficiently reconstruct octopus arm movements of different types.;Collaboration was established with the engineering group of Dr. Ian Walker (Clemson University, USA) in order to automatically operate a soft robot manipulator that was developed to have similar properties and behavior to that of the octopus arm (Walker 2000). It has been found that a quasi-static configuration of the octopus arm can be approximated by a compact geometric description to fit the parameters that control the robot. Both dynamic simulations and real-time experiments that were conducted with the robot have demonstrated that a soft manipulator can automatically mimic some of the behaviors of the octopus arm.;The non-rigid octopus arm which lacks any well-defined point requires an uncommon geometric representation. We used curvature and torsion surfaces as a unique description of octopus arm movements which has led to a novel analysis of the kinematics of octopus arm behaviors. We found that mathematical procedures allow to decompose the topographic nature of these surfaces into building blocks. These building blocks were clustered into kinematic primitives, which define temporal motor action in 3D space. Synthetic rules that utilize these primitives were found to characterize stereotypical behaviors of the arm, and arm movements were classified into sub-groups according to the rules they match. Our findings both suggest the existence of kinematic units as motor primitives used by motor control system of the octopus and give a clearer description of octopus arm behavior. Furthermore, the procedures we have applied establish a novel framework that should be used in the analysis of more octopus arm movements in future research. It may be also of general use by studies referring to biologically inspired hyper-redundant robots, or to other biological flexible appendages.;At the end of this work, we present a novel theoretical framework which examines the creation of primitives through an evolutionary process. We found that modular configurations may emerge and be preferred through the process of learning since they allow the octopus arm to easily adapt to different target point in a dynamic environment.
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