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JAIR
2002
120views more  JAIR 2002»
14 years 11 months ago
Learning Geometrically-Constrained Hidden Markov Models for Robot Navigation: Bridging the Topological-Geometrical Gap
Hidden Markov models hmms and partially observable Markov decision processes pomdps provide useful tools for modeling dynamical systems. They are particularly useful for represent...
Hagit Shatkay, Leslie Pack Kaelbling
ICRA
2010
IEEE
106views Robotics» more  ICRA 2010»
14 years 10 months ago
Generalized direction changing fall control of humanoid robots among multiple objects
— Humanoid robots are expected to share human environments in the future and it is important to ensure safety of their operation. A serious threat to safety is the fall of a huma...
Umashankar Nagarajan, Ambarish Goswami
ATAL
2006
Springer
15 years 3 months ago
Multi-model motion tracking under multiple team member actuators
Autonomous robots need to track objects. Object tracking relies on predefined robot motion and sensory models. Tracking is particularly challenging if the robots can actuate on th...
Yang Gu, Manuela M. Veloso
ABIALS
2008
Springer
15 years 6 months ago
A Neurocomputational Model of Anticipation and Sustained Inattentional Blindness in Hierarchies
Anticipation and prediction have been identified as key functions of many brain areas facilitating recognition, perception, and planning. In this chapter we present a hierarchical ...
Anthony F. Morse, Robert Lowe, Tom Ziemke
ROBOCUP
2007
Springer
153views Robotics» more  ROBOCUP 2007»
15 years 5 months ago
Model-Based Reinforcement Learning in a Complex Domain
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
Shivaram Kalyanakrishnan, Peter Stone, Yaxin Liu