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A central goal of robotics and AI is to be able to deploy an agent to act autonomously in the real world over an extended period of time. To operate in the real world, autonomous robots rely on sensory information. Despite the potential richness of visual information from on-board cameras, many...
Most recent robotic systems, capable of exploring unknown environments, use topological structures (graphs) as a spatial representation. Localization can be done by deriving an estimate of the global pose from landmark information. In this case navigation is tightly coupled to metric knowledge,...
We report our development of a vision-based motion planning system for an autonomous motorcycle designed for desert terrain, where uniform road surface and lane markings are not present. The motion planning is based on a vision vector space (V2-Space), which is a unitary vector set that...
In this paper an energy efficiency analysis of wave gaits is performed for a six-legged walking robot. A simulation model of the robot is used to obtain the data demonstrating the energy consumption while walking in different modes and with varying parameters. Based on the analysis of this data...
Gradient descent in image distances can lead a navigating agent to the goal location, but in environments with an anisotropic distribution of landmarks, gradient home vectors deviate from the true home direction. These deviations can be reduced by applying Newton’s method to matched-filter...
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