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» Randomized model predictive control for robot navigation
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ICRA
2007
IEEE
171views Robotics» more  ICRA 2007»
15 years 6 months ago
Design and Philosophy of the BiMASC, a Highly Dynamic Biped
Abstract— This paper discusses the design principles and philosophy of the BiMASC, a biped with Mechanically Adjustable Series Compliance which incorporates tuned mechanical leg ...
Jonathan W. Hurst, Joel E. Chestnutt, Alfred A. Ri...
ICNC
2009
Springer
15 years 6 months ago
Model-Free Learning and Control in a Mobile Robot
A model-free, biologically-motivated learning and control algorithm called S-learning is described as implemented in an Surveyor SRV-1 mobile robot. S-learning demonstrated learni...
Brandon Rohrer, Michael Bernard, J. Daniel Morrow,...
IROS
2008
IEEE
142views Robotics» more  IROS 2008»
15 years 6 months ago
Probabilistic mapping of dynamic obstacles using Markov chains for replanning in dynamic environments
— Robots acting in populated environments must be capable of safe but also time efficient navigation. Trying to completely avoid regions resulting from worst case predictions of...
Florian Rohrmüller, Matthias Althoff, Dirk Wo...
ICRA
2009
IEEE
188views Robotics» more  ICRA 2009»
14 years 9 months ago
Onboard contextual classification of 3-D point clouds with learned high-order Markov Random Fields
Contextual reasoning through graphical models such as Markov Random Fields often show superior performance against local classifiers in many domains. Unfortunately, this performanc...
Daniel Munoz, Nicolas Vandapel, Martial Hebert
ICRA
2006
IEEE
130views Robotics» more  ICRA 2006»
15 years 5 months ago
Mathematical Foundation for Hormone-inspired Control for Self-reconfigurable Robotic Systems
– In this paper, we present a general mathematical foundation of hormone-inspired control for the selfreconfigurable robotic system. Problem considered here is the lack of a math...
Feili Hou, Wei-Min Shen