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The goal of optimal reconfiguration planning (ORP) is to find a shortest reconfiguration sequence to transform a modular and reconfigurable robot from an arbitrary configuration into another. This paper investigates this challenging problem for chain-type robots based on graph representations and presents a series of theoretical results: (1) a formal proof that this is an NP-complete problem, (2)...
This paper presents a thorough analysis of the computational complexity of optimal reconfiguration planning problem for chain-type modular robots, i.e. finding the least number of reconfiguration steps to transform from the initial configuration into the goal configuration. It establishes a formal proof that this problem is NP-complete, even if the configurations are acyclic. This result gives a compelling...
This paper presents a dynamic and distributed reconfiguration planning algorithm for chain-type self-reconfigurable robots, by which a robot can autonomously self-reconfigure from one arbitrary acyclic configuration to another in a distributed way. The novel features of this algorithm include: (1) an efficient representation for unlabeled complex configurations; (2) a distributed comparison to detect...
Much work on self-reconfigurable robotics has been focused on motion planning and physical reconfiguration of the robot. Using the Superbot self-reconfigurable robot, we focus on the details of realizing locomotion gaits given that a single robot topology can be realized in a large number of different ways. That is, each module in the robot topology has 4 symmetric orientations that are functional...
In this paper, we present a general mathematical foundation of hormone-inspired control for the self-reconfigurable robotic system. Problem considered here is the lack of a mathematical description to analyze and explain the dynamic behavior of self-reconfigurable robots. In the global level, the idea of virtual disconnection is developed to abstract the low level module control away from the high...
This paper presents a Kalman filter approach for 3D motion estimation of an object that undergoes arbitrary rotational and translational motion. Problem considered here is error propagation from image features to 3D motion estimation. To this end, we have derived a new set of equations for motion estimation: (1) Lagrange interpolation and numerical integration are introduced to construct the dynamic...
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