Stochastic Motion Planning for the Telebot
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Abstract
This paper evaluates stochastic motion planning in a three dimensional space for T eleBot#, Florida International Universitys telepresence robot. Stochastic motion planning is necessary in an operator controlled robot due to device latency, device failure, connection failure, or user error. As such, three different modeling methods and their corresponding motion planning algorithms are evaluated for use in stochastic motion planning. The modeling and planning algorithms used are Configuration Spaces (C-Spaces) with Sampling Based Motion Planning, DenavitHartenberg (DH) Parameters with Inverse Kinematics, and the Universal Robot Description Format (URDF) with the Open Motion Planning Library (OMPL).
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How to Cite
Elorza, Y. ., Sundarapandian, S. ., & Jerry Miller. (2017). Stochastic Motion Planning for the Telebot. International Journal of Next-Generation Computing, 8(1), 99–107. https://doi.org/10.47164/ijngc.v8i1.124
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