This research is concerned with the intelligent control of autonomous robot systems in unstructured, highly uncertain environments. We show that the theory of fractal sets is a useful tool for approximate machine reas...
This research is concerned with the intelligent control of autonomous robot systems in unstructured, highly uncertain environments. We show that the theory of fractal sets is a useful tool for approximate machine reasoning at multiple levels of precision. We first derive an algorithm for the classification and combination of incomplete and imprecise patterns of evidence. We also derive a new algorithm for belief propagation across incompatible frames. These algorithms are then applied to the sensorimotor control of roboticsystems. The first application is to a sensorfusion problem, involving the recognition of 3D objects from a combination of vision and touch data. The second application is to sensor based grasping with multifingered hands. These applications integrate high and low level representations of (i) irregular and sparse sensory patterns and (ii) preshaped grasp control under uncertainty.
The dynamically reconfigurable robotic system is a novel kind of robotic system that can reconfigure itself to optimal structure depending on purpose and environment. To realize this concept, the authors propose CEBOT...
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The dynamically reconfigurable robotic system is a novel kind of robotic system that can reconfigure itself to optimal structure depending on purpose and environment. To realize this concept, the authors propose CEBOT (cellular robotics). They explain the necessity of communication in both the docked and undocked states for CEBOT as an autonomousdecentralized coordinated system and propose a method for achieving this. They show the necessity of coordination control and compare two autonomous docking methods. They define a communication protocol in the undocked state and realize it by an optical sensor. They then choose and realize a communication protocol in the docked state.< >
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